diff --git a/README.md b/README.md
index 0a78be803b60b94e92d8d0cfa4b2b6beccffcc70..e5b75c5ff9e86681f05c452d99206336daa35752 100644
--- a/README.md
+++ b/README.md
@@ -16,98 +16,98 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework,
| Domain | Sub Domain | Network | Ascend | GPU | CPU |
|:------ |:------| :----------- |:------: |:------: |:-----: |
-|Computer Vision (CV) | Image Classification | [AlexNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/alexnet) | 鉁� | 鉁� | |
-| Computer Vision (CV) | Image Classification | [CNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/cnn_direction_model) | 鉁� | | |
-| Computer Vision (CV) | Image Classification | [DenseNet100](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/densenet) | | | 鉁� |
-| Computer Vision (CV) | Image Classification | [DenseNet121](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/densenet) | 鉁� | | |
-| Computer Vision (CV) | Image Classification | [DPN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/dpn) | 鉁� | | |
-| Computer Vision (CV) | Image Classification | [EfficientNet-B0](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/efficientnet) | | 鉁� | |
-| Computer Vision (CV) | Image Classification | [GoogLeNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/googlenet) | 鉁� | 鉁� | |
-| Computer Vision (CV) | Image Classification | [InceptionV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/inceptionv3) | 鉁� | | |
-| Computer Vision (CV) | Image Classification | [InceptionV4](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/inceptionv4) | 鉁� | | |
-| Computer Vision (CV) | Image Classification | [LeNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/lenet) | 鉁� | 鉁� | 鉁� |
-| Computer Vision (CV) | Image Classification | [LeNet (Quantization)](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/lenet_quant) | 鉁� | 鉁� | |
-| Computer Vision (CV) | Image Classification | [MobileNetV1](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv1) | 鉁� | | |
-| Computer Vision (CV) | Image Classification | [MobileNetV2](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv2) | 鉁� | 鉁� | 鉁� |
-| Computer Vision (CV) | Image Classification | [MobileNetV2 (Quantization)](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv2_quant) | 鉁� | 鉁� | |
-| Computer Vision (CV) | Image Classification | [MobileNetV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv3) | | 鉁� | |
-| Computer Vision (CV) | Image Classification | [NASNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/nasnet) | | 鉁� | |
-| Computer Vision (CV) | Image Classification | [ResNet-18](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) | 鉁� | | |
-| Computer Vision (CV) | Image Classification | [ResNet-50](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) | 鉁� | 鉁� | 鉁� |
-| Computer Vision (CV) | Image Classification | [ResNet-50 (Quantization)](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet50_quant) | 鉁� | | |
-|Computer Vision (CV) | Image Classification | [ResNet-101](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) | 鉁� | 鉁� | |
-|Computer Vision (CV) | Image Classification | [ResNeXt50](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnext) | 鉁� | 鉁� | |
-|Computer Vision (CV) | Image Classification | [SE-ResNet50](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) | 鉁� | | |
-| Computer Vision (CV) | Image Classification | [ShuffleNetV1](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/shufflenetv1) | 鉁� | | |
-| Computer Vision (CV) | Image Classification | [ShuffleNetV2](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/shufflenetv2) | | 鉁� | |
-| Computer Vision (CV) | Image Classification | [SqueezeNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/squeezenet) | 鉁� | | |
-| Computer Vision (CV) | Image Classification | [Tiny-DarkNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/tinydarknet) | 鉁� | | |
-| Computer Vision (CV) | Image Classification | [VGG16](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/vgg16) | 鉁� | 鉁� | |
-| Computer Vision (CV) | Image Classification | [Xception](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/xception) | 鉁� | | |
-| Computer Vision (CV) | Object Detection | [CenterFace](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/centerface) | 鉁� | | |
-| Computer Vision (CV) | Object Detection | [CTPN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ctpn) | 鉁� | | |
-| Computer Vision (CV) | Object Detection | [Faster R-CNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/faster_rcnn) | 鉁� | 鉁� | |
-| Computer Vision (CV) | Object Detection | [Mask R-CNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/maskrcnn) | 鉁� | | |
-| Computer Vision (CV) | Object Detection | [Mask R-CNN (MobileNetV1)](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/maskrcnn_mobilenetv1) | 鉁� | | |
-| Computer Vision (CV) | Object Detection | [RetinaFace-ResNet50](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/retinaface_resnet50) | | 鉁� | |
-| Computer Vision (CV) | Object Detection | [SSD](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd) | 鉁� | 鉁� | 鉁� |
-| Computer Vision (CV) | Object Detection | [SSD-MobileNetV1-FPN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd) | 鉁� | | |
-| Computer Vision (CV) | Object Detection | [SSD-Resnet50-FPN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd) | 鉁� | | |
-| Computer Vision (CV) | Object Detection | [SSD-VGG16](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd) | 鉁� | | |
-| Computer Vision (CV) | Object Detection | [WarpCTC](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/warpctc) | 鉁� | 鉁� | |
-| Computer Vision (CV) | Object Detection | [YOLOv3-ResNet18](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_resnet18) | 鉁� | | |
-| Computer Vision (CV) | Object Detection | [YOLOv3-DarkNet53](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_darknet53) | 鉁� | 鉁� | |
-| Computer Vision (CV) | Object Detection | [YOLOv3-DarkNet53 (Quantization)](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_darknet53_quant) | 鉁� | | |
-| Computer Vision (CV) | Object Detection | [YOLOv4](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov4) | 鉁� | | |
-| Computer Vision (CV) | Text Detection | [DeepText](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/deeptext) | 鉁� | | |
-| Computer Vision (CV) | Text Detection | [PSENet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/psenet) | 鉁� | | |
-| Computer Vision (CV) | Text Recognition | [CNN+CTC](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/cnnctc) | 鉁� | | |
-| Computer Vision (CV) | Semantic Segmentation | [DeepLabV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/deeplabv3) | 鉁� | | 鉁� |
-| Computer Vision (CV) | Semantic Segmentation | [U-Net2D (Medical)](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/unet) | 鉁� | | |
-| Computer Vision (CV) | Semantic Segmentation | [U-Net3D (Medical)](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/unet3d) | 鉁� | | |
-| Computer Vision (CV) | Semantic Segmentation | [U-Net++](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/unet) | 鉁� | | |
-| Computer Vision (CV) | Keypoint Detection | [OpenPose](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/openpose) | 鉁� | | |
-| Computer Vision (CV) | Keypoint Detection | [SimplePoseNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/simple_pose) | 鉁� | | |
-| Computer Vision (CV) | Optical Character Recognition | [CRNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/crnn) | 鉁� | | |
-| Natural Language Processing (NLP) | Natural Language Understanding | [BERT](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/bert) | 鉁� | 鉁� | |
-| Natural Language Processing (NLP) | Natural Language Understanding | [FastText](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/fasttext) | 鉁� | | |
-| Natural Language Processing (NLP) | Natural Language Understanding | [GNMT v2](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/gnmt_v2) | 鉁� | | |
-| Natural Language Processing (NLP) | Natural Language Understanding | [GRU](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/gru) | 鉁� | | |
-| Natural Language Processing (NLP) | Natural Language Understanding | [MASS](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/mass) | 鉁� | 鉁� | |
-| Natural Language Processing (NLP) | Natural Language Understanding | [SentimentNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/lstm) | 鉁� | 鉁� | 鉁� |
-| Natural Language Processing (NLP) | Natural Language Understanding | [Transformer](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/transformer) | 鉁� | 鉁� | |
-| Natural Language Processing (NLP) | Natural Language Understanding | [TinyBERT](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/tinybert) | 鉁� | 鉁� | |
-| Natural Language Processing (NLP) | Natural Language Understanding | [TextCNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/textcnn) | 鉁� | | |
-| Recommender | Recommender System, CTR prediction | [DeepFM](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/recommend/deepfm) | 鉁� | 鉁� | 鉁� |
-| Recommender | Recommender System, Search, Ranking | [Wide&Deep](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/recommend/wide_and_deep) | 鉁� | 鉁� | |
-| Recommender | Recommender System | [NAML](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/recommend/naml) | 鉁� | | |
-| Recommender | Recommender System | [NCF](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/recommend/ncf) | 鉁� | | |
-| Graph Neural Networks (GNN) | Text Classification | [GCN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/gnn/gcn) | 鉁� | | |
-| Graph Neural Networks (GNN) | Text Classification | [GAT](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/gnn/gat) | 鉁� | | |
-| Graph Neural Networks (GNN) | Recommender System | [BGCF](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/gnn/bgcf) | 鉁� | | |
+|Computer Vision (CV) | Image Classification | [AlexNet](https://gitee.com/mindspore/models/tree/master/official/cv/alexnet) | 鉁� | 鉁� | |
+| Computer Vision (CV) | Image Classification | [CNN](https://gitee.com/mindspore/models/tree/master/official/cv/cnn_direction_model) | 鉁� | | |
+| Computer Vision (CV) | Image Classification | [DenseNet100](https://gitee.com/mindspore/models/tree/master/official/cv/densenet) | | | 鉁� |
+| Computer Vision (CV) | Image Classification | [DenseNet121](https://gitee.com/mindspore/models/tree/master/official/cv/densenet) | 鉁� | | |
+| Computer Vision (CV) | Image Classification | [DPN](https://gitee.com/mindspore/models/tree/master/official/cv/dpn) | 鉁� | | |
+| Computer Vision (CV) | Image Classification | [EfficientNet-B0](https://gitee.com/mindspore/models/tree/master/official/cv/efficientnet) | | 鉁� | |
+| Computer Vision (CV) | Image Classification | [GoogLeNet](https://gitee.com/mindspore/models/tree/master/official/cv/googlenet) | 鉁� | 鉁� | |
+| Computer Vision (CV) | Image Classification | [InceptionV3](https://gitee.com/mindspore/models/tree/master/official/cv/inceptionv3) | 鉁� | | |
+| Computer Vision (CV) | Image Classification | [InceptionV4](https://gitee.com/mindspore/models/tree/master/official/cv/inceptionv4) | 鉁� | | |
+| Computer Vision (CV) | Image Classification | [LeNet](https://gitee.com/mindspore/models/tree/master/official/cv/lenet) | 鉁� | 鉁� | 鉁� |
+| Computer Vision (CV) | Image Classification | [LeNet (Quantization)](https://gitee.com/mindspore/models/tree/master/official/cv/lenet_quant) | 鉁� | 鉁� | |
+| Computer Vision (CV) | Image Classification | [MobileNetV1](https://gitee.com/mindspore/models/tree/master/official/cv/mobilenetv1) | 鉁� | | |
+| Computer Vision (CV) | Image Classification | [MobileNetV2](https://gitee.com/mindspore/models/tree/master/official/cv/mobilenetv2) | 鉁� | 鉁� | 鉁� |
+| Computer Vision (CV) | Image Classification | [MobileNetV2 (Quantization)](https://gitee.com/mindspore/models/tree/master/official/cv/mobilenetv2_quant) | 鉁� | 鉁� | |
+| Computer Vision (CV) | Image Classification | [MobileNetV3](https://gitee.com/mindspore/models/tree/master/official/cv/mobilenetv3) | | 鉁� | |
+| Computer Vision (CV) | Image Classification | [NASNet](https://gitee.com/mindspore/models/tree/master/official/cv/nasnet) | | 鉁� | |
+| Computer Vision (CV) | Image Classification | [ResNet-18](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) | 鉁� | | |
+| Computer Vision (CV) | Image Classification | [ResNet-50](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) | 鉁� | 鉁� | 鉁� |
+| Computer Vision (CV) | Image Classification | [ResNet-50 (Quantization)](https://gitee.com/mindspore/models/tree/master/official/cv/resnet50_quant) | 鉁� | | |
+|Computer Vision (CV) | Image Classification | [ResNet-101](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) | 鉁� | 鉁� | |
+|Computer Vision (CV) | Image Classification | [ResNeXt50](https://gitee.com/mindspore/models/tree/master/official/cv/resnext) | 鉁� | 鉁� | |
+|Computer Vision (CV) | Image Classification | [SE-ResNet50](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) | 鉁� | | |
+| Computer Vision (CV) | Image Classification | [ShuffleNetV1](https://gitee.com/mindspore/models/tree/master/official/cv/shufflenetv1) | 鉁� | | |
+| Computer Vision (CV) | Image Classification | [ShuffleNetV2](https://gitee.com/mindspore/models/tree/master/official/cv/shufflenetv2) | | 鉁� | |
+| Computer Vision (CV) | Image Classification | [SqueezeNet](https://gitee.com/mindspore/models/tree/master/official/cv/squeezenet) | 鉁� | | |
+| Computer Vision (CV) | Image Classification | [Tiny-DarkNet](https://gitee.com/mindspore/models/tree/master/official/cv/tinydarknet) | 鉁� | | |
+| Computer Vision (CV) | Image Classification | [VGG16](https://gitee.com/mindspore/models/tree/master/official/cv/vgg16) | 鉁� | 鉁� | |
+| Computer Vision (CV) | Image Classification | [Xception](https://gitee.com/mindspore/models/tree/master/official/cv/xception) | 鉁� | | |
+| Computer Vision (CV) | Object Detection | [CenterFace](https://gitee.com/mindspore/models/tree/master/official/cv/centerface) | 鉁� | | |
+| Computer Vision (CV) | Object Detection | [CTPN](https://gitee.com/mindspore/models/tree/master/official/cv/ctpn) | 鉁� | | |
+| Computer Vision (CV) | Object Detection | [Faster R-CNN](https://gitee.com/mindspore/models/tree/master/official/cv/faster_rcnn) | 鉁� | 鉁� | |
+| Computer Vision (CV) | Object Detection | [Mask R-CNN](https://gitee.com/mindspore/models/tree/master/official/cv/maskrcnn) | 鉁� | | |
+| Computer Vision (CV) | Object Detection | [Mask R-CNN (MobileNetV1)](https://gitee.com/mindspore/models/tree/master/official/cv/maskrcnn_mobilenetv1) | 鉁� | | |
+| Computer Vision (CV) | Object Detection | [RetinaFace-ResNet50](https://gitee.com/mindspore/models/tree/master/official/cv/retinaface_resnet50) | | 鉁� | |
+| Computer Vision (CV) | Object Detection | [SSD](https://gitee.com/mindspore/models/tree/master/official/cv/ssd) | 鉁� | 鉁� | 鉁� |
+| Computer Vision (CV) | Object Detection | [SSD-MobileNetV1-FPN](https://gitee.com/mindspore/models/tree/master/official/cv/ssd) | 鉁� | | |
+| Computer Vision (CV) | Object Detection | [SSD-Resnet50-FPN](https://gitee.com/mindspore/models/tree/master/official/cv/ssd) | 鉁� | | |
+| Computer Vision (CV) | Object Detection | [SSD-VGG16](https://gitee.com/mindspore/models/tree/master/official/cv/ssd) | 鉁� | | |
+| Computer Vision (CV) | Object Detection | [WarpCTC](https://gitee.com/mindspore/models/tree/master/official/cv/warpctc) | 鉁� | 鉁� | |
+| Computer Vision (CV) | Object Detection | [YOLOv3-ResNet18](https://gitee.com/mindspore/models/tree/master/official/cv/yolov3_resnet18) | 鉁� | | |
+| Computer Vision (CV) | Object Detection | [YOLOv3-DarkNet53](https://gitee.com/mindspore/models/tree/master/official/cv/yolov3_darknet53) | 鉁� | 鉁� | |
+| Computer Vision (CV) | Object Detection | [YOLOv3-DarkNet53 (Quantization)](https://gitee.com/mindspore/models/tree/master/official/cv/yolov3_darknet53_quant) | 鉁� | | |
+| Computer Vision (CV) | Object Detection | [YOLOv4](https://gitee.com/mindspore/models/tree/master/official/cv/yolov4) | 鉁� | | |
+| Computer Vision (CV) | Text Detection | [DeepText](https://gitee.com/mindspore/models/tree/master/official/cv/deeptext) | 鉁� | | |
+| Computer Vision (CV) | Text Detection | [PSENet](https://gitee.com/mindspore/models/tree/master/official/cv/psenet) | 鉁� | | |
+| Computer Vision (CV) | Text Recognition | [CNN+CTC](https://gitee.com/mindspore/models/tree/master/official/cv/cnnctc) | 鉁� | | |
+| Computer Vision (CV) | Semantic Segmentation | [DeepLabV3](https://gitee.com/mindspore/models/tree/master/official/cv/deeplabv3) | 鉁� | | 鉁� |
+| Computer Vision (CV) | Semantic Segmentation | [U-Net2D (Medical)](https://gitee.com/mindspore/models/tree/master/official/cv/unet) | 鉁� | | |
+| Computer Vision (CV) | Semantic Segmentation | [U-Net3D (Medical)](https://gitee.com/mindspore/models/tree/master/official/cv/unet3d) | 鉁� | | |
+| Computer Vision (CV) | Semantic Segmentation | [U-Net++](https://gitee.com/mindspore/models/tree/master/official/cv/unet) | 鉁� | | |
+| Computer Vision (CV) | Keypoint Detection | [OpenPose](https://gitee.com/mindspore/models/tree/master/official/cv/openpose) | 鉁� | | |
+| Computer Vision (CV) | Keypoint Detection | [SimplePoseNet](https://gitee.com/mindspore/models/tree/master/official/cv/simple_pose) | 鉁� | | |
+| Computer Vision (CV) | Optical Character Recognition | [CRNN](https://gitee.com/mindspore/models/tree/master/official/cv/crnn) | 鉁� | | |
+| Natural Language Processing (NLP) | Natural Language Understanding | [BERT](https://gitee.com/mindspore/models/tree/master/official/nlp/bert) | 鉁� | 鉁� | |
+| Natural Language Processing (NLP) | Natural Language Understanding | [FastText](https://gitee.com/mindspore/models/tree/master/official/nlp/fasttext) | 鉁� | | |
+| Natural Language Processing (NLP) | Natural Language Understanding | [GNMT v2](https://gitee.com/mindspore/models/tree/master/official/nlp/gnmt_v2) | 鉁� | | |
+| Natural Language Processing (NLP) | Natural Language Understanding | [GRU](https://gitee.com/mindspore/models/tree/master/official/nlp/gru) | 鉁� | | |
+| Natural Language Processing (NLP) | Natural Language Understanding | [MASS](https://gitee.com/mindspore/models/tree/master/official/nlp/mass) | 鉁� | 鉁� | |
+| Natural Language Processing (NLP) | Natural Language Understanding | [SentimentNet](https://gitee.com/mindspore/models/tree/master/official/nlp/lstm) | 鉁� | 鉁� | 鉁� |
+| Natural Language Processing (NLP) | Natural Language Understanding | [Transformer](https://gitee.com/mindspore/models/tree/master/official/nlp/transformer) | 鉁� | 鉁� | |
+| Natural Language Processing (NLP) | Natural Language Understanding | [TinyBERT](https://gitee.com/mindspore/models/tree/master/official/nlp/tinybert) | 鉁� | 鉁� | |
+| Natural Language Processing (NLP) | Natural Language Understanding | [TextCNN](https://gitee.com/mindspore/models/tree/master/official/nlp/textcnn) | 鉁� | | |
+| Recommender | Recommender System, CTR prediction | [DeepFM](https://gitee.com/mindspore/models/tree/master/official/recommend/deepfm) | 鉁� | 鉁� | 鉁� |
+| Recommender | Recommender System, Search, Ranking | [Wide&Deep](https://gitee.com/mindspore/models/tree/master/official/recommend/wide_and_deep) | 鉁� | 鉁� | |
+| Recommender | Recommender System | [NAML](https://gitee.com/mindspore/models/tree/master/official/recommend/naml) | 鉁� | | |
+| Recommender | Recommender System | [NCF](https://gitee.com/mindspore/models/tree/master/official/recommend/ncf) | 鉁� | | |
+| Graph Neural Networks (GNN) | Text Classification | [GCN](https://gitee.com/mindspore/models/tree/master/official/gnn/gcn) | 鉁� | | |
+| Graph Neural Networks (GNN) | Text Classification | [GAT](https://gitee.com/mindspore/models/tree/master/official/gnn/gat) | 鉁� | | |
+| Graph Neural Networks (GNN) | Recommender System | [BGCF](https://gitee.com/mindspore/models/tree/master/official/gnn/bgcf) | 鉁� | | |
### Research
| Domain | Sub Domain | Network | Ascend | GPU | CPU |
|:------ |:------| :----------- |:------: |:------: |:-----: |
-| Computer Vision (CV) | Image Classification | [FaceAttributes](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/FaceAttribute) | 鉁� | | |
-| Computer Vision (CV) | Object Detection | [FaceDetection](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/FaceDetection) | 鉁� | | |
-| Computer Vision (CV) | Image Classification | [FaceQualityAssessment](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/FaceQualityAssessment) | 鉁� | | |
-| Computer Vision (CV) | Image Classification | [FaceRecognition](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/FaceRecognition) | 鉁� | | |
-| Computer Vision (CV) | Image Classification | [FaceRecognitionForTracking](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/FaceRecognitionForTracking) | 鉁� | | |
-| Computer Vision (CV) | Object Detection | [Spnas](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/Spnas) | 鉁� | | |
-| Computer Vision (CV) | Object Detection | [SSD-GhostNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/ssd_ghostnet) | 鉁� | | |
-| Computer Vision (CV) | Key Point Detection | [CenterNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/centernet) | 鉁� | | 鉁� |
-| Computer Vision (CV) | Image Style Transfer | [CycleGAN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/CycleGAN) | | | 鉁� |
-| Natural Language Processing (NLP) | Natural Language Understanding | [DS-CNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/nlp/dscnn) | 鉁� | | |
-| Natural Language Processing (NLP) | Natural Language Understanding | [TextRCNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/nlp/textrcnn) | 鉁� | | |
-| Natural Language Processing (NLP) | Natural Language Understanding | [TPRR](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/nlp/tprr) | 鉁� | | |
-| Recommender | Recommender System, CTR prediction | [AutoDis](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/recommend/autodis) | 鉁� | | |
-| Audio | Audio Tagging | [FCN-4](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/audio/fcn-4) | 鉁� | | |
-| High Performance Computing | Molecular Dynamics | [DeepPotentialH2O](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/hpc/molecular_dynamics) | 鉁� | | |
-| High Performance Computing | Ocean Model | [GOMO](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/hpc/ocean_model) | | 鉁� | |
-
-- [Community](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/community)
+| Computer Vision (CV) | Image Classification | [FaceAttributes](https://gitee.com/mindspore/models/tree/master/research/cv/FaceAttribute) | 鉁� | | |
+| Computer Vision (CV) | Object Detection | [FaceDetection](https://gitee.com/mindspore/models/tree/master/research/cv/FaceDetection) | 鉁� | | |
+| Computer Vision (CV) | Image Classification | [FaceQualityAssessment](https://gitee.com/mindspore/models/tree/master/research/cv/FaceQualityAssessment) | 鉁� | | |
+| Computer Vision (CV) | Image Classification | [FaceRecognition](https://gitee.com/mindspore/models/tree/master/research/cv/FaceRecognition) | 鉁� | | |
+| Computer Vision (CV) | Image Classification | [FaceRecognitionForTracking](https://gitee.com/mindspore/models/tree/master/research/cv/FaceRecognitionForTracking) | 鉁� | | |
+| Computer Vision (CV) | Object Detection | [Spnas](https://gitee.com/mindspore/models/tree/master/research/cv/Spnas) | 鉁� | | |
+| Computer Vision (CV) | Object Detection | [SSD-GhostNet](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_ghostnet) | 鉁� | | |
+| Computer Vision (CV) | Key Point Detection | [CenterNet](https://gitee.com/mindspore/models/tree/master/research/cv/centernet) | 鉁� | | 鉁� |
+| Computer Vision (CV) | Image Style Transfer | [CycleGAN](https://gitee.com/mindspore/models/tree/master/research/cv/CycleGAN) | | | 鉁� |
+| Natural Language Processing (NLP) | Natural Language Understanding | [DS-CNN](https://gitee.com/mindspore/models/tree/master/research/nlp/dscnn) | 鉁� | | |
+| Natural Language Processing (NLP) | Natural Language Understanding | [TextRCNN](https://gitee.com/mindspore/models/tree/master/research/nlp/textrcnn) | 鉁� | | |
+| Natural Language Processing (NLP) | Natural Language Understanding | [TPRR](https://gitee.com/mindspore/models/tree/master/research/nlp/tprr) | 鉁� | | |
+| Recommender | Recommender System, CTR prediction | [AutoDis](https://gitee.com/mindspore/models/tree/master/research/recommend/autodis) | 鉁� | | |
+| Audio | Audio Tagging | [FCN-4](https://gitee.com/mindspore/models/tree/master/research/audio/fcn-4) | 鉁� | | |
+| High Performance Computing | Molecular Dynamics | [DeepPotentialH2O](https://gitee.com/mindspore/models/tree/master/research/hpc/molecular_dynamics) | 鉁� | | |
+| High Performance Computing | Ocean Model | [GOMO](https://gitee.com/mindspore/models/tree/master/research/hpc/ocean_model) | | 鉁� | |
+
+- [Community](https://gitee.com/mindspore/models/tree/master/community)
## Announcements
diff --git a/README_CN.md b/README_CN.md
index 107a83ac453248daa61d06e345f5eedebaf1e30d..d5a0b79644938784a4379bf9e2d0c086674a0f5c 100644
--- a/README_CN.md
+++ b/README_CN.md
@@ -16,98 +16,98 @@
| 棰嗗煙 | 瀛愰鍩� | 缃戠粶 | Ascend | GPU | CPU |
|:---- |:------- |:---- |:----: |:----: |:----: |
-|璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [AlexNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/alexnet) | 鉁� | 鉁� | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [CNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/cnn_direction_model) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [DenseNet100](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/densenet) | | | 鉁� |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [DenseNet121](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/densenet) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [DPN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/dpn) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [EfficientNet-B0](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/efficientnet) | | 鉁� | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [GoogLeNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/googlenet) | 鉁� | 鉁� | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [InceptionV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/inceptionv3) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [InceptionV4](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/inceptionv4) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [LeNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/lenet) | 鉁� | 鉁� | 鉁� |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [LeNet锛堥噺鍖栵級](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/lenet_quant) | 鉁� | 鉁� | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [MobileNetV1](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv1) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [MobileNetV2](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv2) | 鉁� | 鉁� | 鉁� |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [MobileNetV2锛堥噺鍖栵級](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv2_quant) | 鉁� | 鉁� | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [MobileNetV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv3) | | 鉁� | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [NASNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/nasnet) | | 鉁� | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [ResNet-18](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [ResNet-50](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) | 鉁� | 鉁� | 鉁� |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [ResNet-50锛堥噺鍖栵級](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet50_quant) | 鉁� | | |
-|璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [ResNet-101](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) | 鉁� | 鉁� | |
-|璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [ResNeXt50](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnext) | 鉁� | 鉁� | |
-|璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [SE-ResNet50](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [ShuffleNetV1](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/shufflenetv1) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [ShuffleNetV2](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/shufflenetv2) | | 鉁� | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� |[SqueezeNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/squeezenet) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [Tiny-DarkNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/tinydarknet) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [VGG16](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/vgg16) | 鉁� | 鉁� | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [Xception](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/xception) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [CenterFace](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/centerface) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [CTPN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ctpn) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [Faster R-CNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/faster_rcnn) | 鉁� | 鉁� | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [Mask R-CNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/maskrcnn) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� |[Mask R-CNN (MobileNetV1)](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/maskrcnn_mobilenetv1) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [RetinaFace-ResNet50](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/retinaface_resnet50) | | 鉁� | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [SSD](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd) | 鉁� | 鉁� | 鉁� |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [SSD-MobileNetV1-FPN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [SSD-Resnet50-FPN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [SSD-VGG16](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [WarpCTC](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/warpctc) | 鉁� | 鉁� | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [YOLOv3-ResNet18](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_resnet18) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [YOLOv3-DarkNet53](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_darknet53) | 鉁� | 鉁� | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [YOLOv3-DarkNet53锛堥噺鍖栵級](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_darknet53_quant) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� |[YOLOv4](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov4) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鏂囨湰妫€娴嬶紙Text Detection锛� | [DeepText](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/deeptext) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鏂囨湰妫€娴嬶紙Text Detection锛� | [PSENet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/psenet) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鏂囨湰璇嗗埆锛圱ext Recognition锛� | [CNN+CTC](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/cnnctc) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 璇箟鍒嗗壊锛圫emantic Segmentation锛� | [DeepLabV3](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/deeplabv3) | 鉁� | | 鉁� |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 璇箟鍒嗗壊锛圫emantic Segmentation锛� | [U-Net2D (Medical)](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/unet) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 璇箟鍒嗗壊锛圫emantic Segmentation锛� | [U-Net3D (Medical)](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/unet3d) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 璇箟鍒嗗壊锛圫emantic Segmentation锛� | [U-Net++](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/unet) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍏抽敭鐐规娴嬶紙Keypoint Detection锛� |[OpenPose](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/openpose) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍏抽敭鐐规娴嬶紙Keypoint Detection锛� |[SimplePoseNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/simple_pose) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍏夊瀛楃璇嗗埆锛圤ptical Character Recognition锛� |[CRNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/crnn) | 鉁� | | |
-| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [BERT](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/bert) | 鉁� | 鉁� | |
-| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [FastText](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/fasttext) | 鉁� | | |
-| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [GNMT v2](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/gnmt_v2) | 鉁� | | |
-| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [GRU](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/gru) | 鉁� | | |
-| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [MASS](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/mass) | 鉁� | 鉁� | |
-| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [SentimentNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/lstm) | 鉁� | 鉁� | 鉁� |
-| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [Transformer](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/transformer) | 鉁� | 鉁� | |
-| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [TinyBERT](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/tinybert) | 鉁� | 鉁� | |
-| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [TextCNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/textcnn) | 鉁� | | |
-| 鎺ㄨ崘锛圧ecommender锛� | 鎺ㄨ崘绯荤粺銆佺偣鍑荤巼棰勪及锛圧ecommender System, CTR prediction锛� | [DeepFM](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/recommend/deepfm) | 鉁� | 鉁� | 鉁� |
-| 鎺ㄨ崘锛圧ecommender锛� | 鎺ㄨ崘绯荤粺銆佹悳绱€€佹帓搴忥紙Recommender System, Search, Ranking锛� | [Wide&Deep](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/recommend/wide_and_deep) | 鉁� | 鉁� | |
-| 鎺ㄨ崘锛圧ecommender锛� | 鎺ㄨ崘绯荤粺锛圧ecommender System锛� | [NAML](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/recommend/naml) | 鉁� | | |
-| 鎺ㄨ崘锛圧ecommender锛� | 鎺ㄨ崘绯荤粺锛圧ecommender System锛� | [NCF](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/recommend/ncf) | 鉁� | | |
-| 鍥剧缁忕綉缁滐紙GNN锛� | 鏂囨湰鍒嗙被锛圱ext Classification锛� | [GCN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/gnn/gcn) | 鉁� | | |
-| 鍥剧缁忕綉缁滐紙GNN锛� | 鏂囨湰鍒嗙被锛圱ext Classification锛� | [GAT](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/gnn/gat) | 鉁� | | |
-| 鍥剧缁忕綉缁滐紙GNN锛� | 鎺ㄨ崘绯荤粺锛圧ecommender System锛� | [BGCF](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/gnn/bgcf) | 鉁� | | |
+|璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [AlexNet](https://gitee.com/mindspore/models/tree/master/official/cv/alexnet) | 鉁� | 鉁� | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [CNN](https://gitee.com/mindspore/models/tree/master/official/cv/cnn_direction_model) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [DenseNet100](https://gitee.com/mindspore/models/tree/master/official/cv/densenet) | | | 鉁� |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [DenseNet121](https://gitee.com/mindspore/models/tree/master/official/cv/densenet) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [DPN](https://gitee.com/mindspore/models/tree/master/official/cv/dpn) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [EfficientNet-B0](https://gitee.com/mindspore/models/tree/master/official/cv/efficientnet) | | 鉁� | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [GoogLeNet](https://gitee.com/mindspore/models/tree/master/official/cv/googlenet) | 鉁� | 鉁� | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [InceptionV3](https://gitee.com/mindspore/models/tree/master/official/cv/inceptionv3) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [InceptionV4](https://gitee.com/mindspore/models/tree/master/official/cv/inceptionv4) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [LeNet](https://gitee.com/mindspore/models/tree/master/official/cv/lenet) | 鉁� | 鉁� | 鉁� |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [LeNet锛堥噺鍖栵級](https://gitee.com/mindspore/models/tree/master/official/cv/lenet_quant) | 鉁� | 鉁� | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [MobileNetV1](https://gitee.com/mindspore/models/tree/master/official/cv/mobilenetv1) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [MobileNetV2](https://gitee.com/mindspore/models/tree/master/official/cv/mobilenetv2) | 鉁� | 鉁� | 鉁� |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [MobileNetV2锛堥噺鍖栵級](https://gitee.com/mindspore/models/tree/master/official/cv/mobilenetv2_quant) | 鉁� | 鉁� | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [MobileNetV3](https://gitee.com/mindspore/models/tree/master/official/cv/mobilenetv3) | | 鉁� | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [NASNet](https://gitee.com/mindspore/models/tree/master/official/cv/nasnet) | | 鉁� | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [ResNet-18](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [ResNet-50](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) | 鉁� | 鉁� | 鉁� |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [ResNet-50锛堥噺鍖栵級](https://gitee.com/mindspore/models/tree/master/official/cv/resnet50_quant) | 鉁� | | |
+|璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [ResNet-101](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) | 鉁� | 鉁� | |
+|璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [ResNeXt50](https://gitee.com/mindspore/models/tree/master/official/cv/resnext) | 鉁� | 鉁� | |
+|璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [SE-ResNet50](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [ShuffleNetV1](https://gitee.com/mindspore/models/tree/master/official/cv/shufflenetv1) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [ShuffleNetV2](https://gitee.com/mindspore/models/tree/master/official/cv/shufflenetv2) | | 鉁� | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� |[SqueezeNet](https://gitee.com/mindspore/models/tree/master/official/cv/squeezenet) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [Tiny-DarkNet](https://gitee.com/mindspore/models/tree/master/official/cv/tinydarknet) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [VGG16](https://gitee.com/mindspore/models/tree/master/official/cv/vgg16) | 鉁� | 鉁� | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� | [Xception](https://gitee.com/mindspore/models/tree/master/official/cv/xception) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [CenterFace](https://gitee.com/mindspore/models/tree/master/official/cv/centerface) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [CTPN](https://gitee.com/mindspore/models/tree/master/official/cv/ctpn) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [Faster R-CNN](https://gitee.com/mindspore/models/tree/master/official/cv/faster_rcnn) | 鉁� | 鉁� | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [Mask R-CNN](https://gitee.com/mindspore/models/tree/master/official/cv/maskrcnn) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� |[Mask R-CNN (MobileNetV1)](https://gitee.com/mindspore/models/tree/master/official/cv/maskrcnn_mobilenetv1) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [RetinaFace-ResNet50](https://gitee.com/mindspore/models/tree/master/official/cv/retinaface_resnet50) | | 鉁� | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [SSD](https://gitee.com/mindspore/models/tree/master/official/cv/ssd) | 鉁� | 鉁� | 鉁� |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [SSD-MobileNetV1-FPN](https://gitee.com/mindspore/models/tree/master/official/cv/ssd) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [SSD-Resnet50-FPN](https://gitee.com/mindspore/models/tree/master/official/cv/ssd) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [SSD-VGG16](https://gitee.com/mindspore/models/tree/master/official/cv/ssd) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [WarpCTC](https://gitee.com/mindspore/models/tree/master/official/cv/warpctc) | 鉁� | 鉁� | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [YOLOv3-ResNet18](https://gitee.com/mindspore/models/tree/master/official/cv/yolov3_resnet18) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [YOLOv3-DarkNet53](https://gitee.com/mindspore/models/tree/master/official/cv/yolov3_darknet53) | 鉁� | 鉁� | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [YOLOv3-DarkNet53锛堥噺鍖栵級](https://gitee.com/mindspore/models/tree/master/official/cv/yolov3_darknet53_quant) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� |[YOLOv4](https://gitee.com/mindspore/models/tree/master/official/cv/yolov4) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鏂囨湰妫€娴嬶紙Text Detection锛� | [DeepText](https://gitee.com/mindspore/models/tree/master/official/cv/deeptext) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鏂囨湰妫€娴嬶紙Text Detection锛� | [PSENet](https://gitee.com/mindspore/models/tree/master/official/cv/psenet) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鏂囨湰璇嗗埆锛圱ext Recognition锛� | [CNN+CTC](https://gitee.com/mindspore/models/tree/master/official/cv/cnnctc) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 璇箟鍒嗗壊锛圫emantic Segmentation锛� | [DeepLabV3](https://gitee.com/mindspore/models/tree/master/official/cv/deeplabv3) | 鉁� | | 鉁� |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 璇箟鍒嗗壊锛圫emantic Segmentation锛� | [U-Net2D (Medical)](https://gitee.com/mindspore/models/tree/master/official/cv/unet) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 璇箟鍒嗗壊锛圫emantic Segmentation锛� | [U-Net3D (Medical)](https://gitee.com/mindspore/models/tree/master/official/cv/unet3d) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 璇箟鍒嗗壊锛圫emantic Segmentation锛� | [U-Net++](https://gitee.com/mindspore/models/tree/master/official/cv/unet) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍏抽敭鐐规娴嬶紙Keypoint Detection锛� |[OpenPose](https://gitee.com/mindspore/models/tree/master/official/cv/openpose) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍏抽敭鐐规娴嬶紙Keypoint Detection锛� |[SimplePoseNet](https://gitee.com/mindspore/models/tree/master/official/cv/simple_pose) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍏夊瀛楃璇嗗埆锛圤ptical Character Recognition锛� |[CRNN](https://gitee.com/mindspore/models/tree/master/official/cv/crnn) | 鉁� | | |
+| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [BERT](https://gitee.com/mindspore/models/tree/master/official/nlp/bert) | 鉁� | 鉁� | |
+| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [FastText](https://gitee.com/mindspore/models/tree/master/official/nlp/fasttext) | 鉁� | | |
+| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [GNMT v2](https://gitee.com/mindspore/models/tree/master/official/nlp/gnmt_v2) | 鉁� | | |
+| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [GRU](https://gitee.com/mindspore/models/tree/master/official/nlp/gru) | 鉁� | | |
+| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [MASS](https://gitee.com/mindspore/models/tree/master/official/nlp/mass) | 鉁� | 鉁� | |
+| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [SentimentNet](https://gitee.com/mindspore/models/tree/master/official/nlp/lstm) | 鉁� | 鉁� | 鉁� |
+| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [Transformer](https://gitee.com/mindspore/models/tree/master/official/nlp/transformer) | 鉁� | 鉁� | |
+| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [TinyBERT](https://gitee.com/mindspore/models/tree/master/official/nlp/tinybert) | 鉁� | 鉁� | |
+| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [TextCNN](https://gitee.com/mindspore/models/tree/master/official/nlp/textcnn) | 鉁� | | |
+| 鎺ㄨ崘锛圧ecommender锛� | 鎺ㄨ崘绯荤粺銆佺偣鍑荤巼棰勪及锛圧ecommender System, CTR prediction锛� | [DeepFM](https://gitee.com/mindspore/models/tree/master/official/recommend/deepfm) | 鉁� | 鉁� | 鉁� |
+| 鎺ㄨ崘锛圧ecommender锛� | 鎺ㄨ崘绯荤粺銆佹悳绱€€佹帓搴忥紙Recommender System, Search, Ranking锛� | [Wide&Deep](https://gitee.com/mindspore/models/tree/master/official/recommend/wide_and_deep) | 鉁� | 鉁� | |
+| 鎺ㄨ崘锛圧ecommender锛� | 鎺ㄨ崘绯荤粺锛圧ecommender System锛� | [NAML](https://gitee.com/mindspore/models/tree/master/official/recommend/naml) | 鉁� | | |
+| 鎺ㄨ崘锛圧ecommender锛� | 鎺ㄨ崘绯荤粺锛圧ecommender System锛� | [NCF](https://gitee.com/mindspore/models/tree/master/official/recommend/ncf) | 鉁� | | |
+| 鍥剧缁忕綉缁滐紙GNN锛� | 鏂囨湰鍒嗙被锛圱ext Classification锛� | [GCN](https://gitee.com/mindspore/models/tree/master/official/gnn/gcn) | 鉁� | | |
+| 鍥剧缁忕綉缁滐紙GNN锛� | 鏂囨湰鍒嗙被锛圱ext Classification锛� | [GAT](https://gitee.com/mindspore/models/tree/master/official/gnn/gat) | 鉁� | | |
+| 鍥剧缁忕綉缁滐紙GNN锛� | 鎺ㄨ崘绯荤粺锛圧ecommender System锛� | [BGCF](https://gitee.com/mindspore/models/tree/master/official/gnn/bgcf) | 鉁� | | |
### 鐮旂┒缃戠粶
| 棰嗗煙 | 瀛愰鍩� | 缃戠粶 | Ascend | GPU | CPU |
|:---- |:------- |:---- |:----: |:----: |:----: |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� |[FaceAttributes](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/FaceAttribute) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [FaceDetection](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/FaceDetection) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� |[FaceQualityAssessment](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/FaceQualityAssessment) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� |[FaceRecognition](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/FaceRecognition) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� |[FaceRecognitionForTracking](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/FaceRecognitionForTracking) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [Spnas](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/Spnas) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [SSD-GhostNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/ssd_ghostnet) | 鉁� | | |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍏抽敭鐐规娴嬶紙Key Point Detection锛� | [CenterNet](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/centernet) | 鉁� | | 鉁� |
-| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚椋庢牸杩佺Щ锛圛mage Style Transfer锛� | [CycleGAN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/CycleGAN) | | | 鉁� |
-| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [DS-CNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/nlp/dscnn) | 鉁� | | |
-| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [TextRCNN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/nlp/textrcnn) | 鉁� | | |
-| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [TPRR](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/nlp/tprr) | 鉁� | | |
-| 鎺ㄨ崘锛圧ecommender锛� | 鎺ㄨ崘绯荤粺銆佺偣鍑荤巼棰勪及锛圧ecommender System, CTR prediction锛� | [AutoDis](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/recommend/autodis) | 鉁� | | |
-|璇煶锛圓udio锛� | 闊抽鏍囨敞锛圓udio Tagging锛� | [FCN-4](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/audio/fcn-4) | 鉁� | | |
-|楂樻€ц兘璁＄畻锛圚PC锛� | 鍒嗗瓙鍔ㄥ姏瀛︼紙Molecular Dynamics锛� | [DeepPotentialH2O](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/hpc/molecular_dynamics) | 鉁� | | |
-|楂樻€ц兘璁＄畻锛圚PC锛� | 娴锋磱妯″瀷锛圤cean Model锛� | [GOMO](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/hpc/ocean_model) | | 鉁� | |
-
-- [绀惧尯](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/community)
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� |[FaceAttributes](https://gitee.com/mindspore/models/tree/master/research/cv/FaceAttribute) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [FaceDetection](https://gitee.com/mindspore/models/tree/master/research/cv/FaceDetection) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� |[FaceQualityAssessment](https://gitee.com/mindspore/models/tree/master/research/cv/FaceQualityAssessment) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� |[FaceRecognition](https://gitee.com/mindspore/models/tree/master/research/cv/FaceRecognition) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚鍒嗙被锛圛mage Classification锛� |[FaceRecognitionForTracking](https://gitee.com/mindspore/models/tree/master/research/cv/FaceRecognitionForTracking) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [Spnas](https://gitee.com/mindspore/models/tree/master/research/cv/Spnas) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鐩爣妫€娴嬶紙Object Detection锛� | [SSD-GhostNet](https://gitee.com/mindspore/models/tree/master/research/cv/ssd_ghostnet) | 鉁� | | |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍏抽敭鐐规娴嬶紙Key Point Detection锛� | [CenterNet](https://gitee.com/mindspore/models/tree/master/research/cv/centernet) | 鉁� | | 鉁� |
+| 璁＄畻鏈鸿瑙夛紙CV锛� | 鍥惧儚椋庢牸杩佺Щ锛圛mage Style Transfer锛� | [CycleGAN](https://gitee.com/mindspore/models/tree/master/research/cv/CycleGAN) | | | 鉁� |
+| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [DS-CNN](https://gitee.com/mindspore/models/tree/master/research/nlp/dscnn) | 鉁� | | |
+| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [TextRCNN](https://gitee.com/mindspore/models/tree/master/research/nlp/textrcnn) | 鉁� | | |
+| 鑷劧璇█澶勭悊锛圢LP锛� | 鑷劧璇█鐞嗚В锛圢atural Language Understanding锛� | [TPRR](https://gitee.com/mindspore/models/tree/master/research/nlp/tprr) | 鉁� | | |
+| 鎺ㄨ崘锛圧ecommender锛� | 鎺ㄨ崘绯荤粺銆佺偣鍑荤巼棰勪及锛圧ecommender System, CTR prediction锛� | [AutoDis](https://gitee.com/mindspore/models/tree/master/research/recommend/autodis) | 鉁� | | |
+|璇煶锛圓udio锛� | 闊抽鏍囨敞锛圓udio Tagging锛� | [FCN-4](https://gitee.com/mindspore/models/tree/master/research/audio/fcn-4) | 鉁� | | |
+|楂樻€ц兘璁＄畻锛圚PC锛� | 鍒嗗瓙鍔ㄥ姏瀛︼紙Molecular Dynamics锛� | [DeepPotentialH2O](https://gitee.com/mindspore/models/tree/master/research/hpc/molecular_dynamics) | 鉁� | | |
+|楂樻€ц兘璁＄畻锛圚PC锛� | 娴锋磱妯″瀷锛圤cean Model锛� | [GOMO](https://gitee.com/mindspore/models/tree/master/research/hpc/ocean_model) | | 鉁� | |
+
+- [绀惧尯](https://gitee.com/mindspore/models/tree/master/community)
## 鍏憡
diff --git a/how_to_contribute/README_template.md b/how_to_contribute/README_template.md
index bf96899e0abbe1962fc2f3d7bb04fd653abd5f49..4d3046245f0b2bcd7aecdcf06d1808e0542c5bf4 100644
--- a/how_to_contribute/README_template.md
+++ b/how_to_contribute/README_template.md
@@ -96,4 +96,4 @@ epoch: 12 step: 7393 ,rpn_loss: 0.00547, rcnn_loss: 0.39258, rpn_cls_loss: 0.002
## ModeZoo Homepage
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
\ No newline at end of file
+Please check the official [homepage](https://gitee.com/mindspore/models).
\ No newline at end of file
diff --git a/official/cv/Deepsort/README_CN.md b/official/cv/Deepsort/README_CN.md
index f80c2433b9e17eb1dcdebb6243c0651578a16de8..611cf329ee80934ee807d52ec29e710bb54e8e30 100644
--- a/official/cv/Deepsort/README_CN.md
+++ b/official/cv/Deepsort/README_CN.md
@@ -88,7 +88,7 @@ python evaluate_motchallenge.py --data_url="" --train_url="" --detection_url=""
bash scripts/run_distribute_train.sh train_code_path RANK_TABLE_FILE DATA_PATH
```
-Ascend璁粌锛氱敓鎴怺RANK_TABLE_FILE](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)
+Ascend璁粌锛氱敓鎴怺RANK_TABLE_FILE](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)
## 鑴氭湰璇存槑
@@ -267,4 +267,4 @@ train.py涓缃簡闅忔満绉嶅瓙銆�
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/FCN8s/README.md b/official/cv/FCN8s/README.md
index 741d6ef269f225ab702064f4fa0ea06b5f5c59dd..558112e36b8e8db4715e7bbdee03397cb860c00f 100644
--- a/official/cv/FCN8s/README.md
+++ b/official/cv/FCN8s/README.md
@@ -228,7 +228,7 @@ ckpt_file: /home/FCN8s/ckpt/FCN8s_1-133_300.ckpt
# example: bash scripts/run_train.sh 8 ~/hccl_8p.json
```
- 鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢,璇烽伒寰猍閾炬帴璇存槑](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)
+ 鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢,璇烽伒寰猍閾炬帴璇存槑](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)
- running on GPU with gpu default parameters
@@ -446,7 +446,7 @@ python export.py
| outputs | probability | probability |
| Loss | 0.038 | 0.036 |
| Speed | 1pc: 564.652 ms/step; | 1pc: 455.460 ms/step; |
-| Scripts | [FCN script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/FCN8s)
+| Scripts | [FCN script](https://gitee.com/mindspore/models/tree/master/official/cv/FCN8s)
### Inference Performance
@@ -536,5 +536,5 @@ python export.py
# [ModelZoo 涓婚〉](#contents)
- 璇锋煡鐪嬪畼鏂圭綉绔� [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ 璇锋煡鐪嬪畼鏂圭綉绔� [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/MCNN/README.md b/official/cv/MCNN/README.md
index de835793afdb712129f75764c4c2e249131cd06d..04b053d0e9c24ebf7f763d9026887d119dd4f043 100644
--- a/official/cv/MCNN/README.md
+++ b/official/cv/MCNN/README.md
@@ -184,7 +184,7 @@ Before running the command below, please check the checkpoint path used for eval
| Speed | 5.79 ms/step |
| Total time | 23 mins |
| Checkpoint for Fine tuning | 500.94KB (.ckpt file) |
-| Scripts | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/MCNN | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/alexnet |
+| Scripts | https://gitee.com/mindspore/models/tree/master/official/cv/MCNN | https://gitee.com/mindspore/models/tree/master/official/cv/alexnet |
# [Description of Random Situation](#contents)
@@ -192,4 +192,4 @@ In dataset.py, we set the seed inside ```create_dataset``` function.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/alexnet/README.md b/official/cv/alexnet/README.md
index 6e22c95c4f02fc11cdb70ff8fda85157bf7248c7..f3a8fd192510411014b46523c0bbf6b857e7fadf 100644
--- a/official/cv/alexnet/README.md
+++ b/official/cv/alexnet/README.md
@@ -422,7 +422,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Speed | 7.3 ms/step | 16.8 ms/step |
| Total time | 6 mins | 14 mins |
| Checkpoint for Fine tuning | 445M (.ckpt file) | 445M (.ckpt file) |
-| Scripts | [AlexNet Script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/alexnet) | [AlexNet Script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/alexnet) |
+| Scripts | [AlexNet Script](https://gitee.com/mindspore/models/tree/master/official/cv/alexnet) | [AlexNet Script](https://gitee.com/mindspore/models/tree/master/official/cv/alexnet) |
## [Description of Random Situation](#contents)
@@ -430,4 +430,4 @@ In dataset.py, we set the seed inside ```create_dataset``` function.
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/alexnet/README_CN.md b/official/cv/alexnet/README_CN.md
index 5b9ad7a73f8cf7d4684c6724c2fa35af4daf5588..45666ad11e08f09d7c02a4324e76438d3f680b1c 100644
--- a/official/cv/alexnet/README_CN.md
+++ b/official/cv/alexnet/README_CN.md
@@ -348,7 +348,7 @@ bash run_infer_310.sh [MINDIR_PATH] [DATASET_NAME] [DATASET_PATH] [NEED_PREPROCE
| 閫熷害 | 7姣/姝� | 16.8姣/姝� |
| 鎬绘椂闂� | 6鍒嗛挓 | 14鍒嗛挓|
| 寰皟妫€鏌ョ偣 | 445M 锛�.ckpt鏂囦欢锛� | 445M 锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | [AlexNet鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/alexnet) | [AlexNet鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/alexnet) |
+| 鑴氭湰 | [AlexNet鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/alexnet) | [AlexNet鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/alexnet) |
## 闅忔満鎯呭喌璇存槑
@@ -356,4 +356,4 @@ dataset.py涓缃簡鈥渃reate_dataset鈥濆嚱鏁板唴鐨勭瀛愩€�
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/brdnet/README_CN.md b/official/cv/brdnet/README_CN.md
index 8d5124dcdde9cbd18c3c34b9fee9072ac372ccfc..9c49d57b7b738a9b5515cffcc6a0f208f885180d 100644
--- a/official/cv/brdnet/README_CN.md
+++ b/official/cv/brdnet/README_CN.md
@@ -96,7 +96,7 @@ python eval.py \
sh run_eval.sh [train_code_path] [test_dir] [sigma] [channel] [pretrain_path] [ckpt_name]
```
-Ascend璁粌锛氱敓鎴怺RANK_TABLE_FILE](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)
+Ascend璁粌锛氱敓鎴怺RANK_TABLE_FILE](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)
## 鑴氭湰璇存槑
@@ -521,7 +521,7 @@ BRDNet on 鈥渨aterloo5050step40colorimage鈥�
| Speed | 8p about 7000FPS to 7400FPS |
| Total time | 8p about 2h 14min |
| Checkpoint for Fine tuning | 8p: 13.68MB , 1p: 19.76MB (.ckpt file) |
-| Scripts | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/brdnet |
+| Scripts | https://gitee.com/mindspore/models/tree/master/official/cv/brdnet |
## 闅忔満鎯呭喌璇存槑
@@ -529,4 +529,4 @@ train.py涓缃簡闅忔満绉嶅瓙銆�
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/centerface/README.md b/official/cv/centerface/README.md
index 441553e5812b0f36a6753de70df861303cfcc566..9286d286e54d813ff0e580c393ae38dceeb1872a 100644
--- a/official/cv/centerface/README.md
+++ b/official/cv/centerface/README.md
@@ -120,7 +120,7 @@ step3 (ASCEND ONLY): prepare user rank_table
```python
# user can use your own rank table file
-# or use the [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools) to generate rank table file
+# or use the [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools) to generate rank table file
# e.g., python hccl_tools.py --device_num "[0,8)"
python hccl_tools.py --device_num "[0,8)"
```
@@ -457,7 +457,7 @@ Major parameters eval.py as follows:
```python
# user can use your own rank table file
- # or use the [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools) to generate rank table file
+ # or use the [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools) to generate rank table file
# e.g., python hccl_tools.py --device_num "[0,8)"
python hccl_tools.py --device_num "[0,8)"
```
@@ -829,7 +829,7 @@ CenterFace on 13K images(The annotation and data format must be the same as wide
| Speed | 1p 65 img/s, 8p 475 img/s | 1gpu 80 img/s, 8gpu 480 img/s |
| Total time | train(8p) 1.1h, test 50min, eval 5-10min | train(8gpu) 1.0h, test 35 min, eval 5-10min |
| Checkpoint for Fine tuning | 22M (.ckpt file) | 23M (.ckpt file) |
-| Scripts | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/centerface> | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/centerface> |
+| Scripts | <https://gitee.com/mindspore/models/tree/master/official/cv/centerface> | <https://gitee.com/mindspore/models/tree/master/official/cv/centerface> |
### Inference Performance
@@ -869,4 +869,4 @@ In var_init.py, we set seed for weight initialization
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/cnn_direction_model/README.md b/official/cv/cnn_direction_model/README.md
index aa22415581a9ee04cbe3b618d5f9a2a68e409c73..1d2d989ea3cf9e60a419535882c4c75632504620 100644
--- a/official/cv/cnn_direction_model/README.md
+++ b/official/cv/cnn_direction_model/README.md
@@ -168,7 +168,7 @@ Results of evaluation will be printed after evaluation process is completed.
Please follow the instructions in the link below:
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>.
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>.
Run `scripts/run_distribute_train_ascend.sh` to train the model distributed. The usage of the script is:
@@ -311,4 +311,4 @@ In train.py, we set some seeds before training.
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/cnnctc/README.md b/official/cv/cnnctc/README.md
index 80671a1a13eb4286eefbc9892c2c7132b1157432..7606795b7c0beb0c5e73a4bac8f11c875ed24bd9 100644
--- a/official/cv/cnnctc/README.md
+++ b/official/cv/cnnctc/README.md
@@ -261,7 +261,7 @@ bash scripts/run_distribute_train_ascend.sh [RANK_TABLE_FILE] [PRETRAINED_CKPT(o
Please follow the instructions in the link below:
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>.
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>.
Results and checkpoints are written to `./train_parallel_{i}` folder for device `i` respectively.
Log can be found in `./train_parallel_{i}/log_{i}.log` and loss values are recorded in `./train_parallel_{i}/loss.log`.
@@ -468,7 +468,7 @@ accuracy: 0.8533
| Speed | 1pc: 250 ms/step; 8pcs: 260 ms/step |
| Total time | 1pc: 15 hours; 8pcs: 1.92 hours |
| Parameters (M) | 177 |
-| Scripts | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/cnnctc> |
+| Scripts | <https://gitee.com/mindspore/models/tree/master/official/cv/cnnctc> |
| Parameters | CNNCTC |
| -------------------------- | ----------------------------------------------------------- |
@@ -483,7 +483,7 @@ accuracy: 0.8533
| Speed | 1pc: 1180 ms/step; 8pcs: 1180 ms/step |
| Total time | 1pc: 62.9 hours; 8pcs: 8.67 hours |
| Parameters (M) | 177 |
-| Scripts | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/cnnctc> |
+| Scripts | <https://gitee.com/mindspore/models/tree/master/official/cv/cnnctc> |
### Evaluation Performance
@@ -588,4 +588,4 @@ If you need to use the trained model to perform inference on multiple hardware p
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/cnnctc/README_CN.md b/official/cv/cnnctc/README_CN.md
index a40fd1c09b940f5604dd4fd3692cf70cedfe6e99..31b0e62578eb0cefd576a035a84b473750a1cf96 100644
--- a/official/cv/cnnctc/README_CN.md
+++ b/official/cv/cnnctc/README_CN.md
@@ -250,7 +250,7 @@ bash scripts/run_distribute_train_ascend.sh [RANK_TABLE_FILE] [PRETRAINED_CKPT(o
> 娉ㄦ剰:
- RANK_TABLE_FILE鐩稿叧鍙傝€冭祫鏂欒[閾炬帴](https://www.mindspore.cn/docs/programming_guide/zh-CN/master/distributed_training_ascend.html), 鑾峰彇device_ip鏂规硶璇﹁[閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+ RANK_TABLE_FILE鐩稿叧鍙傝€冭祫鏂欒[閾炬帴](https://www.mindspore.cn/docs/programming_guide/zh-CN/master/distributed_training_ascend.html), 鑾峰彇device_ip鏂规硶璇﹁[閾炬帴](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
### 璁粌缁撴灉
@@ -415,7 +415,7 @@ bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DVPP] [DEVICE_ID]
| 閫熷害 | 1鍗★細300姣/姝ワ紱8鍗★細310姣/姝� |
| 鎬绘椂闂� | 1鍗★細18灏忔椂锛�8鍗★細2.3灏忔椂 |
| 鍙傛暟(M) | 177 |
-| 鑴氭湰 | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/cnnctc> |
+| 鑴氭湰 | <https://gitee.com/mindspore/models/tree/master/official/cv/cnnctc> |
### 璇勪及鎬ц兘
@@ -520,4 +520,4 @@ bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DVPP] [DEVICE_ID]
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/crnn/README.md b/official/cv/crnn/README.md
index 8fc7069a6597bccb83ffa09ecf34a78fe8aa3c2c..ab364096e3cb5f6847af7625e076caa088d05b54 100644
--- a/official/cv/crnn/README.md
+++ b/official/cv/crnn/README.md
@@ -121,7 +121,7 @@ We provide `convert_ic03.py`, `convert_iiit5k.py`, `convert_svt.py` as exmples f
For distributed training, a hccl configuration file with JSON format needs to be created in advance.
Please follow the instructions in the link below:
- [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+ [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
- Run on docker
@@ -446,7 +446,7 @@ result CRNNAccuracy is: 0.7933333333333
| Total time | 557 mins | 189 mins |
| Parameters (M) | 83M (.ckpt file) | 96M |
| Checkpoint for Fine tuning | 20.3M (.ckpt file) | |
-| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/crnn) | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/crnn) |
+| Scripts | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/crnn) | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/crnn) |
#### [Evaluation Performance](#contents)
@@ -468,4 +468,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)
+Please check the official [homepage](https://gitee.com/mindspore/models)
diff --git a/official/cv/crnn_seq2seq_ocr/README.md b/official/cv/crnn_seq2seq_ocr/README.md
index aa6148957d909dba6e615bec6d85477e3897ddd4..14f7774f58641a7e6339be99b72b4e2934d56f0d 100644
--- a/official/cv/crnn_seq2seq_ocr/README.md
+++ b/official/cv/crnn_seq2seq_ocr/README.md
@@ -68,7 +68,7 @@ For training and evaluation, we use the French Street Name Signs (FSNS) released
For distributed training, a hccl configuration file with JSON format needs to be created in advance.
Please follow the instructions in the link below:
- [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+ [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
- Running on ModelArts
@@ -270,7 +270,7 @@ Annotation precision precision = 0.746213
| Speed | 1pc: 355 ms/step; 8pcs: 385 ms/step |
| Total time | 1pc: 64 hours; 8pcs: 9 hours |
| Parameters (M) | 12 |
-| Scripts | [crnn_seq2seq_ocr script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/crnn_seq2seq_ocr) |
+| Scripts | [crnn_seq2seq_ocr script](https://gitee.com/mindspore/models/tree/master/official/cv/crnn_seq2seq_ocr) |
### Inference Performance
diff --git a/official/cv/cspdarknet53/README.md b/official/cv/cspdarknet53/README.md
index 88aaeeeb2bba195a2dc0193cce09a0d259ce3367..cbfd2038d38eaa4113767c51b661ab62819d7b86 100644
--- a/official/cv/cspdarknet53/README.md
+++ b/official/cv/cspdarknet53/README.md
@@ -88,7 +88,7 @@ bash run_eval.sh [DEVICE_ID] [DATA_DIR] [PATH_CHECKPOINT]
For distributed training, a hccl configuration file with JSON format needs to be created in advance.
Please follow the instructions in the link below:
-<https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>
+<https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>
```bash
# Train ImageNet 8p on ModelArts
@@ -206,7 +206,7 @@ bash run_distribute_train.sh [RANK_TABLE_FILE] [DATA_DIR] (option)[PATH_CHECKPOI
bash run_standalone_train.sh [DEVICE_ID] [DATA_DIR] (option)[PATH_CHECKPOINT]
```
-> Notes: RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html), and the device_ip can be got as [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools). For large models like InceptionV3, it's better to export an external environment variable `export HCCL_CONNECT_TIMEOUT=600` to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
+> Notes: RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html), and the device_ip can be got as [Link](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools). For large models like InceptionV3, it's better to export an external environment variable `export HCCL_CONNECT_TIMEOUT=600` to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
>
> This is processor cores binding operation regarding the `device_num` and total processor numbers. If you are not expect to do it, remove the operations `taskset` in `scripts/run_distribute_train.sh`
@@ -306,7 +306,7 @@ Total data: 50000, top1 accuracy: 0.78458, top5 accuracy: 0.94254
| Total time (8p) | 8ps: 14h |
| Checkpoint for Fine tuning | 217M (.ckpt file) |
| Speed | 8pc: 3977 imgs/sec |
-| Scripts | [cspdarknet53 script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/cspdarknet53) |
+| Scripts | [cspdarknet53 script](https://gitee.com/mindspore/models/tree/master/official/cv/cspdarknet53) |
### Inference Performance
@@ -328,4 +328,4 @@ We use random seed in "train.py", "./src/utils/var_init.py", "./src/utils/sample
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/ctpn/README.md b/official/cv/ctpn/README.md
index 26b30d481e7ac6fa22c0796bf340c6302b3b271a..07d8d804ff5e72c063ca6688cbf4ed36bee5d333 100644
--- a/official/cv/ctpn/README.md
+++ b/official/cv/ctpn/README.md
@@ -208,7 +208,7 @@ imagenet_cfg = edict({
Then you can train it with ImageNet2012.
> Notes:
-> RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html) , and the device_ip can be got as [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools). For large models like InceptionV4, it's better to export an external environment variable聽`export HCCL_CONNECT_TIMEOUT=600`聽to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
+> RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html) , and the device_ip can be got as [Link](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools). For large models like InceptionV4, it's better to export an external environment variable聽`export HCCL_CONNECT_TIMEOUT=600`聽to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
>
> This is processor cores binding operation regarding the `device_num` and total processor numbers. If you are not expect to do it, remove the operations `taskset` in `scripts/run_distribute_train.sh`
>
@@ -425,7 +425,7 @@ Evaluation result will be stored in the example path, you can find result like t
| Loss Function | SoftmaxCrossEntropyWithLogits for classification, SmoothL2Loss for bbox regression|
| Loss | ~0.04 |
| Total time (8p) | 6h |
-| Scripts | [ctpn script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ctpn) |
+| Scripts | [ctpn script](https://gitee.com/mindspore/models/tree/master/official/cv/ctpn) |
#### Inference Performance
@@ -457,4 +457,4 @@ We set seed to 1 in train.py.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/deeplabv3/README.md b/official/cv/deeplabv3/README.md
index 0d06884224bd42d1fb243b43011133b3915bbb58..407e6d9aa576e19b93fcd47e287706c7e516125a 100644
--- a/official/cv/deeplabv3/README.md
+++ b/official/cv/deeplabv3/README.md
@@ -893,7 +893,7 @@ mean Iou 0.7854572371350974
| Parameters (M) | 58.2 |
| Checkpoint for Fine tuning | 443M (.ckpt file) |
| Model for inference | 223M (.air file) |
-| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/deeplabv3) |
+| Scripts | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/deeplabv3) |
## Inference Performance
@@ -915,4 +915,4 @@ In dataset.py, we set the seed inside "create_dataset" function. We also use ran
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/deeplabv3/README_CN.md b/official/cv/deeplabv3/README_CN.md
index 51ef16a690f050676c2f785c94269e0762f00002..9d6f756432e79402e6c722a532cee40594d17599 100644
--- a/official/cv/deeplabv3/README_CN.md
+++ b/official/cv/deeplabv3/README_CN.md
@@ -889,7 +889,7 @@ mean Iou 0.7854572371350974
| 鎹熷け | 0.0065883575 |
| 閫熷害 | 31 甯ф暟/绉掞紙鍗曞崱锛宻8锛�<br> 234 甯ф暟/绉掞紙8鍗★紝s8锛� |
| 寰皟妫€鏌ョ偣 | 443M 锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/deeplabv3) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/deeplabv3) |
## 鎺ㄧ悊鎬ц兘
@@ -911,4 +911,4 @@ dataset.py涓缃簡鈥渃reate_dataset鈥濆嚱鏁板唴鐨勭瀛愶紝鍚屾椂杩樹娇鐢�
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/deeplabv3plus/README_CN.md b/official/cv/deeplabv3plus/README_CN.md
index 755dc728220179573e5cf4efac602b6d0251495d..9985407b66d88224e7e9f3e387e5f6929ce95cae 100644
--- a/official/cv/deeplabv3plus/README_CN.md
+++ b/official/cv/deeplabv3plus/README_CN.md
@@ -554,7 +554,7 @@ python ${train_code_path}/eval.py --data_root=/PATH/TO/DATA \
| 鎹熷け | 0.0041095633 |
| 鎬ц兘 | 187736.386 ms锛堝崟鍗★紝s16锛�<br> 44474.187 ms锛堝叓鍗★紝s16锛� |
| 寰皟妫€鏌ョ偣 | 453M 锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/deeplabv3plus) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/deeplabv3plus) |
# 闅忔満鎯呭喌璇存槑
@@ -562,4 +562,4 @@ dataset.py涓缃簡鈥渃reate_dataset鈥濆嚱鏁板唴鐨勭瀛愶紝鍚屾椂杩樹娇鐢�
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/deeptext/README.md b/official/cv/deeptext/README.md
index 908469bf2e5841b10d4cc2958298adfe186f6130..365c3031630e23d9796659e72e59f302fa0cecfb 100644
--- a/official/cv/deeptext/README.md
+++ b/official/cv/deeptext/README.md
@@ -131,7 +131,7 @@ sh run_eval_gpu.sh [IMGS_PATH] [ANNOS_PATH] [CHECKPOINT_PATH] [COCO_TEXT_PARSER_
```
> Notes:
-> RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html) , and the device_ip can be got as [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools). For large models like InceptionV4, it's better to export an external environment variable聽`export HCCL_CONNECT_TIMEOUT=600`聽to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
+> RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html) , and the device_ip can be got as [Link](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools). For large models like InceptionV4, it's better to export an external environment variable聽`export HCCL_CONNECT_TIMEOUT=600`聽to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
>
> This is processor cores binding operation regarding the `device_num` and total processor numbers. If you are not expect to do it, remove the operations `taskset` in `scripts/run_distribute_train.sh`
>
@@ -358,7 +358,7 @@ class 1 precision is 84.24%, recall is 87.40%, F1 is 85.79%
| Loss Function | SoftmaxCrossEntropyWithLogits for classification, SmoothL2Loss for bbox regression | SoftmaxCrossEntropyWithLogits for classification, SmoothL2Loss for bbox regression |
| Loss | ~0.008 | ~0.116 |
| Total time (8p) | 4h | 9h |
-| Scripts | [deeptext script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/deeptext) | [deeptext script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/deeptext) |
+| Scripts | [deeptext script](https://gitee.com/mindspore/models/tree/master/official/cv/deeptext) | [deeptext script](https://gitee.com/mindspore/models/tree/master/official/cv/deeptext) |
#### Inference Performance
@@ -398,4 +398,4 @@ We set seed to 1 in train.py.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/densenet/README.md b/official/cv/densenet/README.md
index 4e5b359b4789f4987f3607875bb6b777a028dad6..f4f63949c38ffbd97d50b3eb89ba4a2238d222f0 100644
--- a/official/cv/densenet/README.md
+++ b/official/cv/densenet/README.md
@@ -115,7 +115,7 @@ After installing MindSpore via the official website, you can start training and
Please follow the instructions in the link below:
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>.
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>.
- running on ModelArts
- If you want to train the model on modelarts, you can refer to the [official guidance document] of modelarts (https://support.huaweicloud.com/modelarts/)
@@ -543,4 +543,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/densenet/README_CN.md b/official/cv/densenet/README_CN.md
index 3301ea23f961f04333f3c085586a8eeae08ad771..11febe6c612d13aa90d67e1586787857854a40eb 100644
--- a/official/cv/densenet/README_CN.md
+++ b/official/cv/densenet/README_CN.md
@@ -120,7 +120,7 @@ DenseNet-100浣跨敤鐨勬暟鎹泦锛� Cifar-10
璇烽伒寰互涓嬮摼鎺ヤ腑鐨勮鏄庯細
- [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)
+ [閾炬帴](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)
- 濡傛灉瑕佸湪modelarts涓婅繘琛屾ā鍨嬬殑璁粌锛屽彲浠ュ弬鑰僲odelarts鐨刐瀹樻柟鎸囧鏂囨。](https://support.huaweicloud.com/modelarts/) 寮€濮嬭繘琛屾ā鍨嬬殑璁粌鍜屾帹鐞嗭紝鍏蜂綋鎿嶄綔濡備笅锛�
@@ -501,4 +501,4 @@ dataset.py涓缃簡鈥渃reate_dataset鈥濆嚱鏁板唴鐨勭瀛愶紝鍚屾椂杩樹娇鐢�
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/dpn/README.md b/official/cv/dpn/README.md
index 71c98709ad8c167be2e3b083413f20318259b1a3..655aaf47dfb43af07a6a77a7a131b8e2fc999d71 100644
--- a/official/cv/dpn/README.md
+++ b/official/cv/dpn/README.md
@@ -222,7 +222,7 @@ The model checkpoint will be saved into `[ckpt_path_to_save]`.
Please follow the instructions in the link below:
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>.
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>.
Run `scripts/train_distributed.sh` to train the model distributed. The usage of the script is:
@@ -411,4 +411,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/east/README.md b/official/cv/east/README.md
index 7d7c2afb664f6048551f437b76abcdcafcd849e2..664c3f1500837da4d090687b453a8a785f7b8ead 100644
--- a/official/cv/east/README.md
+++ b/official/cv/east/README.md
@@ -93,7 +93,7 @@ bash run_eval_ascend.sh [DATASET_PATH] [CKPT_PATH] [DEVICE_ID]
```
> Notes:
-> RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html) , and the device_ip can be got as [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools). For large models like InceptionV4, it's better to export an external environment variable聽`export HCCL_CONNECT_TIMEOUT=600`聽to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
+> RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html) , and the device_ip can be got as [Link](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools). For large models like InceptionV4, it's better to export an external environment variable聽`export HCCL_CONNECT_TIMEOUT=600`聽to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
>
> This is processor cores binding operation regarding the `device_num` and total processor numbers. If you are not expect to do it, remove the operations `taskset` in `scripts/run_distribute_train.sh`
>
@@ -266,7 +266,7 @@ Calculated {"precision": 0.8329088130412634, "recall": 0.7871930669234473, "hmea
| Loss Function | Dice for classification, Iou for bbox regression |
| Loss | ~0.27 |
| Total time (8p) | 1h20m |
-| Scripts | [east script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/east) |
+| Scripts | [east script](https://gitee.com/mindspore/models/tree/master/official/cv/east) |
#### Inference Performance
@@ -298,5 +298,5 @@ We set seed to 1 in train.py.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/efficientnet/README.md b/official/cv/efficientnet/README.md
index 82e92c2b17a829ab09be65f8a12ad728932bb2de..be58733a7d6adcdf9a3a80111f7f5e719d3052c6 100644
--- a/official/cv/efficientnet/README.md
+++ b/official/cv/efficientnet/README.md
@@ -279,4 +279,4 @@ acc=76.96%(TOP1)
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/faster_rcnn/README.md b/official/cv/faster_rcnn/README.md
index 663214096775c711334da85a53fe8270dfd308e0..7543e8218d3d6c70a6a48e7117bc91a465caa7f2 100644
--- a/official/cv/faster_rcnn/README.md
+++ b/official/cv/faster_rcnn/README.md
@@ -374,7 +374,7 @@ bash run_distribute_train_gpu.sh [DEVICE_NUM] [PRETRAINED_MODEL] [BACKBONE] [COC
Notes:
-1. Rank_table.json which is specified by RANK_TABLE_FILE is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+1. Rank_table.json which is specified by RANK_TABLE_FILE is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
2. As for PRETRAINED_MODEL锛宨t should be a trained ResNet50 checkpoint. If you need to load Ready-made pretrained FasterRcnn checkpoint, you may make changes to the train.py script as follows.
```python
@@ -518,7 +518,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Speed | 1pc: 190 ms/step; 8pcs: 200 ms/step | 1pc: 320 ms/step; 8pcs: 335 ms/step |
| Total time | 1pc: 37.17 hours; 8pcs: 4.89 hours |1pc: 63.09 hours; 8pcs: 8.25 hours |
| Parameters (M) | 250 |250 |
-| Scripts | [fasterrcnn script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/faster_rcnn) | [fasterrcnn script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/faster_rcnn) |
+| Scripts | [fasterrcnn script](https://gitee.com/mindspore/models/tree/master/official/cv/faster_rcnn) | [fasterrcnn script](https://gitee.com/mindspore/models/tree/master/official/cv/faster_rcnn) |
### Inference Performance
@@ -536,4 +536,4 @@ Inference result is saved in current path, you can find result like this in acc.
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/faster_rcnn/README_CN.md b/official/cv/faster_rcnn/README_CN.md
index 3c23afb866068c4c14fa335d41f40b333ab462db..e54c9dec1212315f94648e837ea682036f72a6cb 100644
--- a/official/cv/faster_rcnn/README_CN.md
+++ b/official/cv/faster_rcnn/README_CN.md
@@ -375,7 +375,7 @@ bash run_distribute_train_gpu.sh [DEVICE_NUM] [PRETRAINED_MODEL] [BACKBONE] [COC
Notes:
-1. 杩愯鍒嗗竷寮忎换鍔℃椂闇€瑕佺敤鍒癛ANK_TABLE_FILE鎸囧畾鐨剅ank_table.json銆傛偍鍙互浣跨敤[hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)鐢熸垚璇ユ枃浠躲€�
+1. 杩愯鍒嗗竷寮忎换鍔℃椂闇€瑕佺敤鍒癛ANK_TABLE_FILE鎸囧畾鐨剅ank_table.json銆傛偍鍙互浣跨敤[hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)鐢熸垚璇ユ枃浠躲€�
2. PRETRAINED_MODEL搴旇鏄缁冨ソ鐨凴esNet-50妫€鏌ョ偣銆傚鏋滈渶瑕佸姞杞借缁冨ソ鐨凢asterRcnn鐨勬鏌ョ偣锛岄渶瑕佸train.py浣滃涓嬩慨鏀�:
```python
@@ -518,7 +518,7 @@ bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANN_FILE] [DEVICE_ID]
| 閫熷害 | 1鍗★細190姣/姝ワ紱8鍗★細200姣/姝� | 1鍗★細320姣/姝ワ紱8鍗★細335姣/姝� |
| 鎬绘椂闂� | 1鍗★細37.17灏忔椂锛�8鍗★細4.89灏忔椂 |1鍗★細63.09灏忔椂锛�8鍗★細8.25灏忔椂 |
| 鍙傛暟(M) | 250 |250 |
-| 鑴氭湰 | [Faster R-CNN鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/faster_rcnn) | [Faster R-CNN鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/faster_rcnn) |
+| 鑴氭湰 | [Faster R-CNN鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/faster_rcnn) | [Faster R-CNN鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/faster_rcnn) |
### 璇勪及鎬ц兘
@@ -536,4 +536,4 @@ bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [ANN_FILE] [DEVICE_ID]
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/fastscnn/README_CN.md b/official/cv/fastscnn/README_CN.md
index 0d224115557b7b155cb49532d8d661b3a8a4d6fc..2dcf9dccc21c58a98aec7aeb39c308ee2d2734f0 100644
--- a/official/cv/fastscnn/README_CN.md
+++ b/official/cv/fastscnn/README_CN.md
@@ -95,7 +95,7 @@ python eval.py \
bash ./scripts/run_eval.sh [train_code_path] [dataset] [resume_path] [resume_name] [output_path]
```
-Ascend璁粌锛氱敓鎴怺RANK_TABLE_FILE](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)
+Ascend璁粌锛氱敓鎴怺RANK_TABLE_FILE](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)
## 鑴氭湰璇存槑
@@ -349,7 +349,7 @@ FastSCNN on 鈥淐ityscapes 鈥�
| Accuracy | 55.48% |
| Total time | 8p锛�8h20m |
| Checkpoint for Fine tuning | 8p: 14.51MB(.ckpt file) |
-| Scripts | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/fastscnn |
+| Scripts | https://gitee.com/mindspore/models/tree/master/official/cv/fastscnn |
## 闅忔満鎯呭喌璇存槑
@@ -357,4 +357,4 @@ train.py涓缃簡闅忔満绉嶅瓙銆�
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/googlenet/README.md b/official/cv/googlenet/README.md
index ca8ce7db208baf43772292f982a540f7e1e29e7c..c0a628f306b579bf9139778c3521e6bf558be843 100644
--- a/official/cv/googlenet/README.md
+++ b/official/cv/googlenet/README.md
@@ -121,7 +121,7 @@ After installing MindSpore via the official website, you can start training and
Please follow the instructions in the link below:
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>.
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>.
- running on GPU
@@ -536,7 +536,7 @@ Current batch_ Size can only be set to 1.
| Parameters (M) | 13.0 | 13.0 |
| Checkpoint for Fine tuning | 43.07M (.ckpt file) | 43.07M (.ckpt file) |
| Model for inference | 21.50M (.onnx file), 21.60M(.air file) | |
-| Scripts | [googlenet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/googlenet) | [googlenet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/googlenet) |
+| Scripts | [googlenet script](https://gitee.com/mindspore/models/tree/master/official/cv/googlenet) | [googlenet script](https://gitee.com/mindspore/models/tree/master/official/cv/googlenet) |
#### GoogleNet on 1200k images
@@ -727,4 +727,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/googlenet/README_CN.md b/official/cv/googlenet/README_CN.md
index 5cd3c07be27d5eb8cde5715e13dbde76f9549c2f..f4aad91b5b13b0e5d8d8b844c70ab0ca3eadbd25 100644
--- a/official/cv/googlenet/README_CN.md
+++ b/official/cv/googlenet/README_CN.md
@@ -123,7 +123,7 @@ GoogleNet鐢卞涓猧nception妯″潡涓茶仈璧锋潵锛屽彲浠ユ洿鍔犳繁鍏ャ€� 闄嶇淮鐨�
璇烽伒寰互涓嬮摼鎺ヤ腑鐨勮鏄庯細
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.>
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools.>
- GPU澶勭悊鍣ㄧ幆澧冭繍琛�
@@ -698,4 +698,4 @@ python export.py --config_path [CONFIG_PATH]
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/inceptionv3/README.md b/official/cv/inceptionv3/README.md
index 7629b561acaca4ca19e08da825441bcc1bad24ee..82a3878bf8c03ab09066600538067853f8f5aea0 100644
--- a/official/cv/inceptionv3/README.md
+++ b/official/cv/inceptionv3/README.md
@@ -298,7 +298,7 @@ bash scripts/run_standalone_train.sh [DEVICE_ID] [DATA_PATH] [CKPT_PATH]
bash scripts/run_standalone_train_cpu.sh DATA_PATH
```
-> Notes: RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html), and the device_ip can be got as [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools). For large models like InceptionV3, it's better to export an external environment variable `export HCCL_CONNECT_TIMEOUT=600` to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
+> Notes: RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html), and the device_ip can be got as [Link](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools). For large models like InceptionV3, it's better to export an external environment variable `export HCCL_CONNECT_TIMEOUT=600` to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
>
> This is processor cores binding operation regarding the `device_num` and total processor numbers. If you are not expect to do it, remove the operations `taskset` in `scripts/run_distribute_train.sh`
@@ -443,7 +443,7 @@ accuracy:78.742
| Checkpoint for Fine tuning | 313M |
| Model for inference | 92M (.onnx file) |
| Speed | 1pc:1200 img/s;8pc:9500 img/s |
-| Scripts | [inceptionv3 script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/inceptionv3) |
+| Scripts | [inceptionv3 script](https://gitee.com/mindspore/models/tree/master/official/cv/inceptionv3) |
### Inference Performance
@@ -465,4 +465,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/inceptionv3/README_CN.md b/official/cv/inceptionv3/README_CN.md
index 3e92fcfa4227e9a585423e700c8bd19ed68e7b3c..52877c04a41e25b0617b29e95fff1cf4be6dcbed 100644
--- a/official/cv/inceptionv3/README_CN.md
+++ b/official/cv/inceptionv3/README_CN.md
@@ -297,7 +297,7 @@ bash scripts/run_standalone_train.sh [DEVICE_ID] [DATA_PATH] [CKPT_PATH]
# example: bash scripts/run_standalone_train.sh 0 /home/DataSet/cifar10/ ./ckpt/
```
-> 娉細RANK_TABLE_FILE鍙弬鑰僛閾炬帴](https://www.mindspore.cn/docs/programming_guide/zh-CN/master/distributed_training_ascend.html)銆俤evice_ip鍙互閫氳繃[閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)鑾峰彇
+> 娉細RANK_TABLE_FILE鍙弬鑰僛閾炬帴](https://www.mindspore.cn/docs/programming_guide/zh-CN/master/distributed_training_ascend.html)銆俤evice_ip鍙互閫氳繃[閾炬帴](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)鑾峰彇
> 杩欐槸鍏充簬device_num鍜屽鐞嗗櫒鎬绘暟鐨勫鐞嗗櫒鏍哥粦瀹氭搷浣溿€傚涓嶉渶瑕侊紝璇峰垹闄cripts/run_distribute_train.sh涓殑taskset鎿嶄綔銆�
### 鍚姩
@@ -441,7 +441,7 @@ accuracy:78.742
| 鍙傛暟(M) | 103M |
| 寰皟妫€鏌ョ偣 | 313M |
| 璁粌閫熷害 | 鍗曞崱锛�1200img/s;8鍗★細9500 img/s |
-| 鑴氭湰 | [inceptionv3鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/inceptionv3) |
+| 鑴氭湰 | [inceptionv3鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/inceptionv3) |
#### 鎺ㄧ悊鎬ц兘
@@ -464,5 +464,5 @@ accuracy:78.742
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/inceptionv4/README.md b/official/cv/inceptionv4/README.md
index 1748aedb99a8d8f37dd8686d7b20285fa57c53c5..5841de54508b61ffec82f10495d47c8b23653738 100644
--- a/official/cv/inceptionv4/README.md
+++ b/official/cv/inceptionv4/README.md
@@ -263,7 +263,7 @@ bash scripts/run_standalone_train_ascend.sh [DEVICE_ID] [DATA_DIR]
```
> Notes:
-> RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html) , and the device_ip can be got as [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools). For large models like InceptionV4, it's better to export an external environment variable聽`export HCCL_CONNECT_TIMEOUT=600`聽to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
+> RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html) , and the device_ip can be got as [Link](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools). For large models like InceptionV4, it's better to export an external environment variable聽`export HCCL_CONNECT_TIMEOUT=600`聽to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
>
> This is processor cores binding operation regarding the `device_num` and total processor numbers. If you are not expect to do it, remove the operations `taskset` in `scripts/run_distribute_train.sh`
@@ -429,7 +429,7 @@ accuracy:80.044
| Total time (8p) | 20h | 95h |
| Params (M) | 153M | 153M |
| Checkpoint for Fine tuning | 2135M | 489M |
-| Scripts | [inceptionv4 script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/inceptionv4) | [inceptionv4 script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/inceptionv4) |
+| Scripts | [inceptionv4 script](https://gitee.com/mindspore/models/tree/master/official/cv/inceptionv4) | [inceptionv4 script](https://gitee.com/mindspore/models/tree/master/official/cv/inceptionv4) |
#### Inference Performance
@@ -466,4 +466,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/lenet/README.md b/official/cv/lenet/README.md
index e44d8b8eb0f0161d38ee7b14e6f45f7d6c48f47a..047f700537a402bb181786ac806dbe5a3a642eeb 100644
--- a/official/cv/lenet/README.md
+++ b/official/cv/lenet/README.md
@@ -321,7 +321,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Speed | 1.071 ms/step |
| Total time | 32.1s | |
| Checkpoint for Fine tuning | 482k (.ckpt file) |
-| Scripts | [LeNet Script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/lenet)s |
+| Scripts | [LeNet Script](https://gitee.com/mindspore/models/tree/master/official/cv/lenet)s |
#### Inference Performance
@@ -343,4 +343,4 @@ In dataset.py, we set the seed inside ```create_dataset``` function.
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/lenet/README_CN.md b/official/cv/lenet/README_CN.md
index d13f391f1a8b2f4662e259bf35290659a8a2b732..dca3b9d923f67cd2b7937317fe360cb938fa8443 100644
--- a/official/cv/lenet/README_CN.md
+++ b/official/cv/lenet/README_CN.md
@@ -319,7 +319,7 @@ bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DVPP] [DEVICE_ID]
| 閫熷害 | 1.0姣/姝� |
| 鎬绘椂闀� | 32.1绉� |
| 寰皟妫€鏌ョ偣 | 482k (.ckpt鏂囦欢) |
-| 鑴氭湰 | [LeNet鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/lenet) |
+| 鑴氭湰 | [LeNet鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/lenet) |
### 鎺ㄧ悊鎬ц兘
@@ -341,4 +341,4 @@ bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DVPP] [DEVICE_ID]
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/lenet_quant/Readme.md b/official/cv/lenet_quant/Readme.md
index 0a8d1c4b5596d454d608d753f4efc566ed522e39..18a57e84eec6532be763edd3dceb3b3635784ad8 100644
--- a/official/cv/lenet_quant/Readme.md
+++ b/official/cv/lenet_quant/Readme.md
@@ -214,7 +214,7 @@ You can view the results through the file "acc.log". The accuracy of the test da
| Speed |3.29 ms/step |
| Total time | 40s |
| Checkpoint for Fine tuning | 482k (.ckpt file) |
-| Scripts | [scripts](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/lenet) |
+| Scripts | [scripts](https://gitee.com/mindspore/models/tree/master/official/cv/lenet) |
## [Description of Random Situation](#contents)
@@ -222,4 +222,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function.
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/lenet_quant/Readme_CN.md b/official/cv/lenet_quant/Readme_CN.md
index 8c8d90c7e074cdc9b3c9e82ad0a4f032cc8510dd..3c4f1a19b2e203c50a7ede67970b3d31b98fda04 100644
--- a/official/cv/lenet_quant/Readme_CN.md
+++ b/official/cv/lenet_quant/Readme_CN.md
@@ -216,7 +216,7 @@ bash run_infer_310.sh [AIR_PATH] [DATA_PATH] [LABEL_PATH] [DEVICE_ID]
| 閫熷害 |3.29姣/姝� |
| 鎬绘椂闀� | 40绉� |
| 寰皟妫€鏌ョ偣 | 482k (.ckpt鏂囦欢) |
-| 鑴氭湰 | [鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/lenet) |
+| 鑴氭湰 | [鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/lenet) |
## 闅忔満鎯呭喌璇存槑
@@ -224,4 +224,4 @@ bash run_infer_310.sh [AIR_PATH] [DATA_PATH] [LABEL_PATH] [DEVICE_ID]
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/maskrcnn/README.md b/official/cv/maskrcnn/README.md
index d5597471c3fc6360f7b373e26f1f13956624d0a9..f27275e927ab87d2e75042f53e2562e841512743 100644
--- a/official/cv/maskrcnn/README.md
+++ b/official/cv/maskrcnn/README.md
@@ -114,7 +114,7 @@ pip install mmcv=0.2.14
Note:
1. To speed up data preprocessing, MindSpore provide a data format named MindRecord, hence the first step is to generate MindRecord files based on COCO2017 dataset before training. The process of converting raw COCO2017 dataset to MindRecord format may take about 4 hours.
- 2. For distributed training, a [hccl configuration file](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools) with JSON format needs to be created in advance.
+ 2. For distributed training, a [hccl configuration file](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools) with JSON format needs to be created in advance.
3. PRETRAINED_CKPT is a resnet50 checkpoint that trained over ImageNet2012.you can train it with [resnet50](https://gitee.com/qujianwei/mindspore/tree/master/model_zoo/official/cv/resnet) scripts in modelzoo, and use src/convert_checkpoint.py to get the pretrain checkpoint file.
4. For large models like MaskRCNN, it's better to export an external environment variable `export HCCL_CONNECT_TIMEOUT=600` to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
@@ -548,7 +548,7 @@ bash run_distribute_train.sh [RANK_TABLE_FILE] [PRETRAINED_MODEL]
```
- Notes
-1. hccl.json which is specified by RANK_TABLE_FILE is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+1. hccl.json which is specified by RANK_TABLE_FILE is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
2. As for PRETRAINED_MODEL锛宨t should be a trained ResNet50 checkpoint. If not set, the model will be trained from the very beginning. If you need to load Ready-made pretrained MaskRcnn checkpoint, you may make changes to the train.py script as follows.
```python
@@ -788,7 +788,7 @@ Accumulating evaluation results...
| Parameters (M) | 84.8 |
| Checkpoint for Fine tuning | 85M(.ckpt file) |
| Model for inference | 571M(.air file) |
-| Scripts | [maskrcnn script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/maskrcnn) |
+| Scripts | [maskrcnn script](https://gitee.com/mindspore/models/tree/master/official/cv/maskrcnn) |
### Inference Performance
@@ -810,4 +810,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/maskrcnn/README_CN.md b/official/cv/maskrcnn/README_CN.md
index 6b1969a7585c11eea6db184385930707659d53fb..38c6c8b0850655c8f85fcb2f13397c4573050985 100644
--- a/official/cv/maskrcnn/README_CN.md
+++ b/official/cv/maskrcnn/README_CN.md
@@ -116,7 +116,7 @@ pip install mmcv=0.2.14
娉細
1. 涓哄姞蹇暟鎹澶勭悊閫熷害锛孧indSpore鎻愪緵浜哅indRecord鏁版嵁鏍煎紡銆傚洜姝わ紝璁粌鍓嶉鍏堥渶瑕佺敓鎴愬熀浜嶤OCO2017鏁版嵁闆嗙殑MindRecord鏂囦欢銆侰OCO2017鍘熷鏁版嵁闆嗚浆鎹负MindRecord鏍煎紡澶ф闇€瑕�4灏忔椂銆�
- 2. 杩涜鍒嗗竷寮忚缁冨墠锛岄渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨刐hccl閰嶇疆鏂囦欢](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)銆�
+ 2. 杩涜鍒嗗竷寮忚缁冨墠锛岄渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨刐hccl閰嶇疆鏂囦欢](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)銆�
3. PRETRAINED_CKPT鏄竴涓猂esNet50妫€鏌ョ偣锛岄€氳繃ImageNet2012璁粌銆備綘鍙互浣跨敤ModelZoo涓� [resnet50](https://gitee.com/qujianwei/mindspore/tree/master/model_zoo/official/cv/resnet) 鑴氭湰鏉ヨ缁�, 鐒跺悗浣跨敤src/convert_checkpoint.py鎶婅缁冨ソ鐨剅esnet50鐨勬潈閲嶆枃浠惰浆鎹负鍙姞杞界殑鏉冮噸鏂囦欢銆�
4. 鎵ц璇勪及鑴氭湰銆�
@@ -544,7 +544,7 @@ bash run_distribute_train.sh [RANK_TABLE_FILE] [PRETRAINED_MODEL]
- Notes
-1. 杩愯鍒嗗竷寮忎换鍔℃椂瑕佺敤鍒扮敱RANK_TABLE_FILE鎸囧畾鐨刪ccl.json鏂囦欢銆傛偍鍙娇鐢╗hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)鐢熸垚璇ユ枃浠躲€�
+1. 杩愯鍒嗗竷寮忎换鍔℃椂瑕佺敤鍒扮敱RANK_TABLE_FILE鎸囧畾鐨刪ccl.json鏂囦欢銆傛偍鍙娇鐢╗hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)鐢熸垚璇ユ枃浠躲€�
2. PRETRAINED_MODEL搴旇鏄缁冨ソ鐨凴esNet50妫€鏌ョ偣銆傚鏋滄鍙傛暟鏈缃紝缃戠粶灏嗕粠澶村紑濮嬭缁冦€傚鏋滄兂瑕佸姞杞借缁冨ソ鐨凪askRcnn妫€鏌ョ偣锛岄渶瑕佸train.py浣滃涓嬩慨鏀癸細
```python
@@ -778,7 +778,7 @@ Accumulating evaluation results...
| 閫熷害 | 鍗曞崱锛�250姣/姝ワ紱8P: 260姣/姝� |
| 鎬绘椂闀� | 鍗曞崱锛�52灏忔椂锛�8鍗★細6.6灏忔椂 |
| 鍙傛暟锛圡锛� | 280 |
-| 鑴氭湰 | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/maskrcnn> |
+| 鑴氭湰 | <https://gitee.com/mindspore/models/tree/master/official/cv/maskrcnn> |
### 璇勪及鎬ц兘
@@ -800,4 +800,4 @@ Accumulating evaluation results...
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/maskrcnn_mobilenetv1/README.md b/official/cv/maskrcnn_mobilenetv1/README.md
index 97b5ecaa8b34af36a7d901cfee69b13e9764fea8..31e722d79534a0c162556ffd30162ea520e3d32e 100644
--- a/official/cv/maskrcnn_mobilenetv1/README.md
+++ b/official/cv/maskrcnn_mobilenetv1/README.md
@@ -121,7 +121,7 @@ pip install mmcv=0.2.14
Note:
1. To speed up data preprocessing, MindSpore provide a data format named MindRecord, hence the first step is to generate MindRecord files based on COCO2017 dataset before training. The process of converting raw COCO2017 dataset to MindRecord format may take about 4 hours.
- 2. For distributed training, a [hccl configuration file](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools) with JSON format needs to be created in advance.
+ 2. For distributed training, a [hccl configuration file](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools) with JSON format needs to be created in advance.
3. For large models like maskrcnn_mobilenetv1, it's better to export an external environment variable `export HCCL_CONNECT_TIMEOUT=600` to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
4. Execute eval script.
@@ -535,7 +535,7 @@ bash run_distribute_train.sh [RANK_TABLE_FILE] [DATA_PATH] [PRETRAINED_MODEL(opt
# example: bash run_distribute_train.sh ~/hccl_8p.json /home/DataSet/cocodataset/
```
-> hccl.json which is specified by RANK_TABLE_FILE is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+> hccl.json which is specified by RANK_TABLE_FILE is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
> As for PRETRAINED_MODEL, if not set, the model will be trained from the very beginning. Ready-made pretrained_models are not available now. Stay tuned.
> This is processor cores binding operation regarding the `device_num` and total processor numbers. If you are not expect to do it, remove the operations `taskset` in `scripts/run_distribute_train.sh`
@@ -685,7 +685,7 @@ Accumulating evaluation results...
| Loss | 0.88387 |
| Speed | 8pcs: 249 ms/step |
| Total time | 8pcs: 6.23 hours |
-| Scripts | [maskrcnn script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/maskrcnn_mobilenetv1) |
+| Scripts | [maskrcnn script](https://gitee.com/mindspore/models/tree/master/official/cv/maskrcnn_mobilenetv1) |
### Inference Performance
@@ -707,4 +707,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/mobilenetv1/README.md b/official/cv/mobilenetv1/README.md
index 068e4e50e00e8251becd0b70ab7e09cb897a362a..ce1a3c4b052d49f593220a8208772cf780ddb78f 100644
--- a/official/cv/mobilenetv1/README.md
+++ b/official/cv/mobilenetv1/README.md
@@ -247,7 +247,7 @@ You can start training using python or shell scripts. The usage of shell scripts
For distributed training with Ascend, a hccl configuration file with JSON format needs to be created in advance.
-Please follow the instructions in the link [hccn_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+Please follow the instructions in the link [hccn_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
### Launch
@@ -393,7 +393,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Total time | 225 min | -- |
| Params (M) | 3.3 M | -- |
| Checkpoint for Fine tuning | 27.3 M | -- |
-| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv1)
+| Scripts | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/mobilenetv1)
## [Description of Random Situation](#contents)
@@ -402,4 +402,4 @@ In train.py, we set the seed which is used by numpy.random, mindspore.common.Ini
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/mobilenetv2/README.md b/official/cv/mobilenetv2/README.md
index acd953a9a37297af2de1c0a4a0ac48cacbe6e8f3..68e28f19f9c615e9c3b45f40b022c0ddb3dd981e 100644
--- a/official/cv/mobilenetv2/README.md
+++ b/official/cv/mobilenetv2/README.md
@@ -427,7 +427,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Total time | 753 min | 845 min |
| Params (M) | 3.3 M | 3.3 M |
| Checkpoint for Fine tuning | 27.3 M | 27.3 M |
-| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv2)|
+| Scripts | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/mobilenetv2)|
### Inference Performance
@@ -450,4 +450,4 @@ In train.py, we set the seed which is used by numpy.random, mindspore.common.Ini
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/mobilenetv2/README_CN.md b/official/cv/mobilenetv2/README_CN.md
index c4d878d4b0a887b45933ad5bdf5454295d7eb7f8..35af3e3d4714d9094943f39c571768f508e8f814 100644
--- a/official/cv/mobilenetv2/README_CN.md
+++ b/official/cv/mobilenetv2/README_CN.md
@@ -427,7 +427,7 @@ bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [LABEL_PATH] [DVPP] [DEVICE_ID]
|鎬绘椂闀� | 753 min | 845 min |
| 鍙傛暟(M) | 3.3M | 3.3M |
| 寰皟妫€鏌ョ偣 | 27.3M | 27.3M |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv2)|
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/mobilenetv2)|
### 鎺ㄧ悊鎬ц兘
@@ -450,4 +450,4 @@ bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [LABEL_PATH] [DVPP] [DEVICE_ID]
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/mobilenetv2_quant/README_CN.md b/official/cv/mobilenetv2_quant/README_CN.md
index cbfa9eac47fcfa93116f2df847a001a83a8f8fc3..10730046fc684e88976457050761fc7e4fe54295 100644
--- a/official/cv/mobilenetv2_quant/README_CN.md
+++ b/official/cv/mobilenetv2_quant/README_CN.md
@@ -320,4 +320,4 @@ bash run_infer_310.sh [AIR_PATH] [DATA_PATH] [LABEL_PATH] [DEVICE_ID]
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/mobilenetv2_quant/Readme.md b/official/cv/mobilenetv2_quant/Readme.md
index 82719ea7fb4752ee24a12adc3a18939d4be0f3ce..fa8ce0c44328796ccc5e13a06b30b0779aad1423 100644
--- a/official/cv/mobilenetv2_quant/Readme.md
+++ b/official/cv/mobilenetv2_quant/Readme.md
@@ -317,4 +317,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/mobilenetv3/README_CN.md b/official/cv/mobilenetv3/README_CN.md
index c98c37195e2aaa6d3b75cd11e02f68938f1ddedf..5fb40ebc8f3190ed5e0493c16038f3cb512da05f 100644
--- a/official/cv/mobilenetv3/README_CN.md
+++ b/official/cv/mobilenetv3/README_CN.md
@@ -173,7 +173,7 @@ python export.py --device_target [PLATFORM] --checkpoint_path [CKPT_PATH]
|鎬绘椂闀� | 1433鍒嗛挓 |
| 鍙傛暟(M) | 5.48M |
| 寰皟妫€鏌ョ偣 | 44M |
-|鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv3)|
+|鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/mobilenetv3)|
# 闅忔満鎯呭喌璇存槑
@@ -181,4 +181,4 @@ python export.py --device_target [PLATFORM] --checkpoint_path [CKPT_PATH]
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/mobilenetv3/Readme.md b/official/cv/mobilenetv3/Readme.md
index 205afb7ec4316968aeb69ad08e9ba692af02c837..478cc35d10ef86f023105e1444015ff49c05e522 100644
--- a/official/cv/mobilenetv3/Readme.md
+++ b/official/cv/mobilenetv3/Readme.md
@@ -169,7 +169,7 @@ python export.py --device_target [PLATFORM] --checkpoint_path [CKPT_PATH]
| Total time | 1433 min |
| Params (M) | 5.48 M |
| Checkpoint for Fine tuning | 44 M |
-| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/mobilenetv3)|
+| Scripts | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/mobilenetv3)|
# [Description of Random Situation](#contents)
@@ -177,4 +177,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/nasnet/README.md b/official/cv/nasnet/README.md
index 0a65e1c859a85eaa3aba37450d45cc489a5d9bd0..626a5edf9a47db01f95783faecc2871f502a7717 100644
--- a/official/cv/nasnet/README.md
+++ b/official/cv/nasnet/README.md
@@ -175,4 +175,4 @@ acc=73.5%(TOP1)
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/nasnet/README_CN.md b/official/cv/nasnet/README_CN.md
index 61e5a64a68aa6541494da1ed80d575e6a8c67075..3f60d0a2f3e0e77449c88307cb1bedc22fcdd36e 100644
--- a/official/cv/nasnet/README_CN.md
+++ b/official/cv/nasnet/README_CN.md
@@ -183,4 +183,4 @@ acc=73.5%(TOP1)
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/openpose/README.md b/official/cv/openpose/README.md
index 5671daea55ab97713b04e0c35abf744db1678000..4caf3cf29c03ad22d1a8acb530e27cd70735a474 100644
--- a/official/cv/openpose/README.md
+++ b/official/cv/openpose/README.md
@@ -103,7 +103,7 @@ After installing MindSpore via the official website, you can start training and
# example: bash scripts/run_eval_ascend.sh /home/model/openpose/ckpt/0-8_663.ckpt /home/DataSet/coco/val2017 /home/DataSet/coco/annotations/person_keypoints_val2017.json
```
-[RANK_TABLE_FILE] is the path of the multi-card information configuration table in the environment. The configuration table can be automatically generated by the tool [hccl_tool](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+[RANK_TABLE_FILE] is the path of the multi-card information configuration table in the environment. The configuration table can be automatically generated by the tool [hccl_tool](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
# [Script Description](#contents)
diff --git a/official/cv/posenet/README_CN.md b/official/cv/posenet/README_CN.md
index aef7e6405504571616b8b160662662b25f79375a..2effe1ce17dc815202ee61c72e6f79efaca08dc3 100644
--- a/official/cv/posenet/README_CN.md
+++ b/official/cv/posenet/README_CN.md
@@ -89,7 +89,7 @@ PoseNet鏄墤妗ュぇ瀛︽彁鍑虹殑涓€绉嶉瞾妫掋€佸疄鏃剁殑6DOF锛堝崟鐩叚鑷敱搴�
璇烽伒寰互涓嬮摼鎺ヤ腑鐨勮鏄庯細
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.>
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools.>
- GPU澶勭悊鍣ㄧ幆澧冭繍琛�
@@ -300,7 +300,7 @@ PoseNet鏄墤妗ュぇ瀛︽彁鍑虹殑涓€绉嶉瞾妫掋€佸疄鏃剁殑6DOF锛堝崟鐩叚鑷敱搴�
| 鍙傛暟(M) | 10.7 | 10.7 |
| 寰皟妫€鏌ョ偣 | 82.91M (.ckpt鏂囦欢) | 82.91M (.ckpt鏂囦欢) |
| 鎺ㄧ悊妯″瀷 | 41.66M (.mindir鏂囦欢) | 41.66M (.mindir鏂囦欢) |
-| 鑴氭湰 | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/posenet> | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/posenet> |
+| 鑴氭湰 | <https://gitee.com/mindspore/models/tree/master/official/cv/posenet> | <https://gitee.com/mindspore/models/tree/master/official/cv/posenet> |
#### StMarysChurch涓婄殑PoseNet
@@ -320,7 +320,7 @@ PoseNet鏄墤妗ュぇ瀛︽彁鍑虹殑涓€绉嶉瞾妫掋€佸疄鏃剁殑6DOF锛堝崟鐩叚鑷敱搴�
| 鍙傛暟(M) | 10.7 | 10.7 |
| 寰皟妫€鏌ョ偣 | 82.91M (.ckpt鏂囦欢) | 82.91M (.ckpt鏂囦欢) |
| 鎺ㄧ悊妯″瀷 | 41.66M (.mindir鏂囦欢) | 41.66M (.mindir鏂囦欢) |
-| 鑴氭湰 | [posenet鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/posenet) | [posenet鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/posenet) |
+| 鑴氭湰 | [posenet鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/posenet) | [posenet鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/posenet) |
### 鎺ㄧ悊鎬ц兘
@@ -360,4 +360,4 @@ PoseNet鏄墤妗ュぇ瀛︽彁鍑虹殑涓€绉嶉瞾妫掋€佸疄鏃剁殑6DOF锛堝崟鐩叚鑷敱搴�
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/psenet/README.md b/official/cv/psenet/README.md
index c8997e86cee5acc4e657f7a91692cb45b1078cf4..794e6572717ee278937ba181642a826f579812fd 100644
--- a/official/cv/psenet/README.md
+++ b/official/cv/psenet/README.md
@@ -235,13 +235,13 @@ Major parameters in default_config.yaml are:
For distributed ascend training, a hccl configuration file with JSON format needs to be created in advance.
- Please follow the instructions in the link below: <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>.
+ Please follow the instructions in the link below: <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>.
```shell
bash scripts/run_distribute_train.sh [RANK_FILE] [PRETRAINED_PATH] [TRAIN_ROOT_DIR]
```
-rank_table_file which is specified by RANK_TABLE_FILE is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+rank_table_file which is specified by RANK_TABLE_FILE is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
The above shell script will run distribute training in the background. You can view the results through the file
`device[X]/test_*.log`. The loss value will be achieved as follows:
@@ -390,7 +390,7 @@ The `res` folder is generated in the upper-level directory. For details about th
| Total time | 1pc: 75.48 h; 8pcs: 7.11 h |
| Parameters (M) | 27.36 |
| Checkpoint for Fine tuning | 109.44M (.ckpt file) |
-| Scripts | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/psenet> |
+| Scripts | <https://gitee.com/mindspore/models/tree/master/official/cv/psenet> |
| Parameters | GPU |
| -------------------------- | ----------------------------------------------------------- |
@@ -408,7 +408,7 @@ The `res` folder is generated in the upper-level directory. For details about th
| Total time | 1pc: 335.6 h; 8pcs: 41.95 h |
| Parameters (M) | 27.36 |
| Checkpoint for Fine tuning | 109.44M (.ckpt file) |
-| Scripts | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/psenet> |
+| Scripts | <https://gitee.com/mindspore/models/tree/master/official/cv/psenet> |
### Inference Performance
diff --git a/official/cv/psenet/README_CN.md b/official/cv/psenet/README_CN.md
index f61702b5e05a498d175c8fc5b69478a70511e290..af02a28b8a617be9fa2dc7ef36ecfbfb7b287773 100644
--- a/official/cv/psenet/README_CN.md
+++ b/official/cv/psenet/README_CN.md
@@ -229,7 +229,7 @@ bash scripts/run_eval_ascend.sh
鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆�
- 璇烽伒寰摼鎺ヤ腑鐨勮鏄庯細[閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)
+ 璇烽伒寰摼鎺ヤ腑鐨勮鏄庯細[閾炬帴](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)
```shell
# 绗竴涓弬鏁颁负rank_table鏂囦欢锛岀浜屼釜鍙傛暟涓虹敓鎴愮殑棰勮缁冩ā鍨嬶紝绗笁涓弬鏁颁负涓嬭浇鐨勮缁冩暟鎹泦
@@ -345,7 +345,7 @@ bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DEVICE_ID]
| 鎬绘椂闂� | 1鍗★細75.48灏忔椂锛�8鍗★細7.11灏忔椂|
| 鍙傛暟(M) | 27.36 |
| 寰皟妫€鏌ョ偣 | 109.44M 锛�.ckpt file锛� |
-| 鑴氭湰 | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/psenet> |
+| 鑴氭湰 | <https://gitee.com/mindspore/models/tree/master/official/cv/psenet> |
### 鎺ㄧ悊鎬ц兘
diff --git a/official/cv/resnet/README.md b/official/cv/resnet/README.md
index 0dc17d7bd4f9b703eb55b7d0c35f40ac2ef71fd2..35fca631087266987c878e5896e5cafb935d8ec5 100644
--- a/official/cv/resnet/README.md
+++ b/official/cv/resnet/README.md
@@ -398,7 +398,7 @@ Usage: bash run_eval.sh [DATASET_PATH] [CHECKPOINT_PATH] [CONFIG_PATH]
For distributed training, a hccl configuration file with JSON format needs to be created in advance.
-Please follow the instructions in the link [hccn_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+Please follow the instructions in the link [hccn_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
Training result will be stored in the example path, whose folder name begins with "train" or "train_parallel". Under this, you can find checkpoint file together with result like the following in log.
@@ -778,7 +778,7 @@ Total data: 50000, top1 accuracy: 0.76844, top5 accuracy: 0.93522.
| Total time | 4 mins | 11 minds |
| Parameters (M) | 11.2 | 11.2 |
| Checkpoint for Fine tuning | 86M (.ckpt file) | 85.4 (.ckpt file) |
-| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) |
+| Scripts | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) |
#### ResNet18 on ImageNet2012
@@ -798,7 +798,7 @@ Total data: 50000, top1 accuracy: 0.76844, top5 accuracy: 0.93522.
| Total time | 110 mins | 130 mins |
| Parameters (M) | 11.7 | 11.7 |
| Checkpoint for Fine tuning | 90M (.ckpt file) | 90M (.ckpt file) |
-| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) |
+| Scripts | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) |
#### ResNet50 on CIFAR-10
@@ -818,7 +818,7 @@ Total data: 50000, top1 accuracy: 0.76844, top5 accuracy: 0.93522.
| Total time | 6 mins | 20.2 mins|
| Parameters (M) | 25.5 | 25.5 |
| Checkpoint for Fine tuning | 179.7M (.ckpt file) |179.7M (.ckpt file)|
-| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) |
+| Scripts | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) |
#### ResNet50 on ImageNet2012
@@ -838,7 +838,7 @@ Total data: 50000, top1 accuracy: 0.76844, top5 accuracy: 0.93522.
| Total time | 114 mins | 260 mins|
| Parameters (M) | 25.5 | 25.5 |
| Checkpoint for Fine tuning | 197M (.ckpt file) |197M (.ckpt file) |
-| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) |
+| Scripts | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) |
#### ResNet34 on ImageNet2012
@@ -858,7 +858,7 @@ Total data: 50000, top1 accuracy: 0.76844, top5 accuracy: 0.93522.
| Total time | 112 mins |
| Parameters (M) | 20.79 |
| Checkpoint for Fine tuning | 166M (.ckpt file) |
-| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) |
+| Scripts | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) |
#### ResNet101 on ImageNet2012
@@ -878,7 +878,7 @@ Total data: 50000, top1 accuracy: 0.76844, top5 accuracy: 0.93522.
| Total time | 301 mins | 1100 mins|
| Parameters (M) | 44.6 | 44.6 |
| Checkpoint for Fine tuning | 343M (.ckpt file) |343M (.ckpt file) |
-| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) |
+| Scripts | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) |
#### ResNet152 on ImageNet2012
@@ -918,7 +918,7 @@ Total data: 50000, top1 accuracy: 0.76844, top5 accuracy: 0.93522.
| Total time | 49.3 mins |
| Parameters (M) | 25.5 |
| Checkpoint for Fine tuning | 215.9M (.ckpt file) |
-| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) |
+| Scripts | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) |
### Inference Performance
@@ -1040,4 +1040,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/resnet/README_CN.md b/official/cv/resnet/README_CN.md
index 449425c4a32f0324b29d01ddb943ee05a229fddf..2f30d6eda6522177462e28fa5c1950196bf68b0b 100644
--- a/official/cv/resnet/README_CN.md
+++ b/official/cv/resnet/README_CN.md
@@ -379,7 +379,7 @@ bash run_eval_gpu.sh [DATASET_PATH] [CHECKPOINT_PATH] [CONFIG_PATH]
鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆�
-鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)涓殑璇存槑銆�
+鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)涓殑璇存槑銆�
璁粌缁撴灉淇濆瓨鍦ㄧず渚嬭矾寰勪腑锛屾枃浠跺す鍚嶇О浠モ€渢rain鈥濇垨鈥渢rain_parallel鈥濆紑澶淬€傛偍鍙湪姝よ矾寰勪笅鐨勬棩蹇椾腑鎵惧埌妫€鏌ョ偣鏂囦欢浠ュ強缁撴灉锛屽涓嬫墍绀恒€�
@@ -738,7 +738,7 @@ Total data: 50000, top1 accuracy: 0.76844, top5 accuracy: 0.93522.
| 鎬绘椂闀� | 4鍒嗛挓 | 11鍒嗛挓 |
| 鍙傛暟(M) | 11.2 | 11.2 |
| 寰皟妫€鏌ョ偣 | 86锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) |
#### ImageNet2012涓婄殑ResNet18
@@ -758,7 +758,7 @@ Total data: 50000, top1 accuracy: 0.76844, top5 accuracy: 0.93522.
| 鎬绘椂闀� | 110鍒嗛挓 | 130鍒嗛挓 |
| 鍙傛暟(M) | 11.7 | 11.7 |
| 寰皟妫€鏌ョ偣| 90M锛�.ckpt鏂囦欢锛� | 90M锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) |
#### CIFAR-10涓婄殑ResNet50
@@ -778,7 +778,7 @@ Total data: 50000, top1 accuracy: 0.76844, top5 accuracy: 0.93522.
| 鎬绘椂闀� | 6鍒嗛挓 | 20.2鍒嗛挓|
| 鍙傛暟(M) | 25.5 | 25.5 |
| 寰皟妫€鏌ョ偣 | 179.7M锛�.ckpt鏂囦欢锛� | 179.7M锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) |
#### ImageNet2012涓婄殑ResNet50
@@ -798,7 +798,7 @@ Total data: 50000, top1 accuracy: 0.76844, top5 accuracy: 0.93522.
| 鎬绘椂闀� | 114鍒嗛挓 | 500鍒嗛挓|
| 鍙傛暟(M) | 25.5 | 25.5 |
| 寰皟妫€鏌ョ偣| 197M锛�.ckpt鏂囦欢锛� | 197M锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) |
#### ImageNet2012涓婄殑ResNet34
@@ -818,7 +818,7 @@ Total data: 50000, top1 accuracy: 0.76844, top5 accuracy: 0.93522.
| 鎬绘椂闀� | 112鍒嗛挓 |
| 鍙傛暟(M) | 20.79 |
| 寰皟妫€鏌ョ偣| 166M锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) |
#### ImageNet2012涓婄殑ResNet101
@@ -838,7 +838,7 @@ Total data: 50000, top1 accuracy: 0.76844, top5 accuracy: 0.93522.
| 鎬绘椂闀� | 301鍒嗛挓 | 1100鍒嗛挓|
| 鍙傛暟(M) | 44.6 | 44.6 |
| 寰皟妫€鏌ョ偣| 343M锛�.ckpt鏂囦欢锛� | 343M锛�.ckpt鏂囦欢锛� |
-|鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) |
+|鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) |
#### ImageNet2012涓婄殑ResNet152
@@ -878,7 +878,7 @@ Total data: 50000, top1 accuracy: 0.76844, top5 accuracy: 0.93522.
| 鎬绘椂闀� | 49.3鍒嗛挓 |
| 鍙傛暟(M) | 25.5 |
| 寰皟妫€鏌ョ偣 | 215.9M 锛�.ckpt鏂囦欢锛� |
-|鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) |
+|鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/resnet) |
# 闅忔満鎯呭喌璇存槑
@@ -886,4 +886,4 @@ Total data: 50000, top1 accuracy: 0.76844, top5 accuracy: 0.93522.
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/resnet50_quant/README.md b/official/cv/resnet50_quant/README.md
index 3b7735d9a5a273c8439633af1355751c60654669..4ed6474e15755b2182d3e8ffe64775c6e4e9ea80 100644
--- a/official/cv/resnet50_quant/README.md
+++ b/official/cv/resnet50_quant/README.md
@@ -234,7 +234,7 @@ You can view the results through the file "acc.log". The accuracy of the test da
| Total time | 8pcs: 17 hours(30 epochs with pretrained) |
| Parameters (M) | 25.5 |
| Checkpoint for Fine tuning | 197M (.ckpt file) |
-| Scripts | [resnet50-quant script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet50_quant) |
+| Scripts | [resnet50-quant script](https://gitee.com/mindspore/models/tree/master/official/cv/resnet50_quant) |
### Inference Performance
@@ -256,4 +256,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/resnet50_quant/README_CN.md b/official/cv/resnet50_quant/README_CN.md
index 8edb5afa59d3c9ac39cbeba9d1ef647d328d0eb1..b7a45a662b68a65019f68cde16c88d77e1d6f93d 100644
--- a/official/cv/resnet50_quant/README_CN.md
+++ b/official/cv/resnet50_quant/README_CN.md
@@ -259,4 +259,4 @@ dataset.py涓缃簡鈥渃reate_dataset鈥濆嚱鏁板唴鐨勭瀛愶紝鍚屾椂杩樹娇鐢�
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/resnet_thor/README.md b/official/cv/resnet_thor/README.md
index 8e59f951131fff12a26a62200dfd30da91a1926f..45f8cf243340541d7e7c33165dca51043fdd0932 100644
--- a/official/cv/resnet_thor/README.md
+++ b/official/cv/resnet_thor/README.md
@@ -79,7 +79,7 @@ bash run_distribute_train.sh [RANK_TABLE_FILE] [DATASET_PATH] [DEVICE_NUM]
bash run_eval.sh [DATASET_PATH] [CHECKPOINT_PATH]
```
-> For distributed training, a hccl configuration file with JSON format needs to be created in advance. About the configuration file, you can refer to the [HCCL_TOOL](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+> For distributed training, a hccl configuration file with JSON format needs to be created in advance. About the configuration file, you can refer to the [HCCL_TOOL](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
- Running on GPU
@@ -276,7 +276,7 @@ Inference result will be stored in the example path, whose folder name is "eval"
| Total time(acc to 75.9%) | 72 mins | 229 mins|
| Parameters (M) | 25.5 | 25.5 |
| Checkpoint for Fine tuning | 491M (.ckpt file) |380M (.ckpt file) |
-| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet_thor) |[Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet_thor) |
+| Scripts | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/resnet_thor) |[Link](https://gitee.com/mindspore/models/tree/master/official/cv/resnet_thor) |
### Inference Performance
@@ -298,4 +298,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
## ModelZoo HomePage
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/resnet_thor/README_CN.md b/official/cv/resnet_thor/README_CN.md
index 784ac4eeb98eb89857e43939ce52aecd42b72a0b..30972e4c8c44da39188576120ebad64985a09f2c 100644
--- a/official/cv/resnet_thor/README_CN.md
+++ b/official/cv/resnet_thor/README_CN.md
@@ -83,7 +83,7 @@ bash run_distribute_train.sh [RANK_TABLE_FILE] [DATASET_PATH] [DEVICE_NUM]
bash run_eval.sh [DATASET_PATH] [CHECKPOINT_PATH]
```
-> 瀵逛簬鍒嗗竷寮忚缁冿紝闇€瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆傚叧浜庨厤缃枃浠讹紝鍙互鍙傝€僛HCCL_TOOL](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)
+> 瀵逛簬鍒嗗竷寮忚缁冿紝闇€瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆傚叧浜庨厤缃枃浠讹紝鍙互鍙傝€僛HCCL_TOOL](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)
銆�
- GPU澶勭悊鍣ㄧ幆澧冭繍琛�
@@ -281,7 +281,7 @@ epoch锛� 36 step: 5004锛宭oss is 1.645802
| 鎬绘椂闂达紙鎸�75.9%璁＄畻锛� | 72鍒嗛挓 | 229鍒嗛挓 |
| 鍙傛暟(M) | 25.5 |25.5 |
| checkpoint | 491M锛�.ckpt file锛� | 380M锛�.ckpt file锛� |
-| 鑴氭湰 |[閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet_thor) |[閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet_thor) |
+| 鑴氭湰 |[閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/resnet_thor) |[閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/resnet_thor) |
### 鎺ㄧ悊鎬ц兘
@@ -303,5 +303,5 @@ epoch锛� 36 step: 5004锛宭oss is 1.645802
## ModelZoo棣栭〉
- 璇锋煡鐪嬪畼鏂筟涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)
+ 璇锋煡鐪嬪畼鏂筟涓婚〉](https://gitee.com/mindspore/models)
銆�
diff --git a/official/cv/resnext/README.md b/official/cv/resnext/README.md
index f788958b38b5b6c62e1bdaa599d923bfe4314ddd..6c5a0985fef059df51309db8a8beb36c776e1fc0 100644
--- a/official/cv/resnext/README.md
+++ b/official/cv/resnext/README.md
@@ -371,4 +371,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/resnext/README_CN.md b/official/cv/resnext/README_CN.md
index 7ff2e42c5118e024c470c20c4edb43b10a26abab..09699a0a9ef299c7211e8392e5a1d681d258f37f 100644
--- a/official/cv/resnext/README_CN.md
+++ b/official/cv/resnext/README_CN.md
@@ -363,4 +363,4 @@ dataset.py涓缃簡鈥渃reate_dataset鈥濆嚱鏁板唴鐨勭瀛愶紝鍚屾椂杩樹娇鐢�
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/retinaface_resnet50/README.md b/official/cv/retinaface_resnet50/README.md
index 64b01c09e04a224e489e1c90d6f81c4d29b9e758..e37ddade4f2194d9254f2192794f67b7f2817833 100644
--- a/official/cv/retinaface_resnet50/README.md
+++ b/official/cv/retinaface_resnet50/README.md
@@ -248,7 +248,7 @@ Parameters for both training and evaluation can be set in config.py
| Total time | 4pcs: 6.4 hours |
| Parameters (M) | 27.29M |
| Checkpoint for Fine tuning | 336.3M (.ckpt file) |
-| Scripts | [retinaface script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/retinaface_resnet50) |
+| Scripts | [retinaface script](https://gitee.com/mindspore/models/tree/master/official/cv/retinaface_resnet50) |
## [How to use](#contents)
@@ -296,4 +296,4 @@ In train.py, we set the seed with setup_seed function.
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/retinaface_resnet50/README_CN.md b/official/cv/retinaface_resnet50/README_CN.md
index 6b528d43bf3f10c5102d2cabe941ca18765bf428..3c587e6bb663128cf42a19524be9808ec329e225 100644
--- a/official/cv/retinaface_resnet50/README_CN.md
+++ b/official/cv/retinaface_resnet50/README_CN.md
@@ -257,7 +257,7 @@ RetinaFace浣跨敤ResNet50楠ㄥ共鎻愬彇鍥惧儚鐗瑰緛杩涜妫€娴嬨€備粠ModelZoo鑾峰彇
| 鎬绘椂闀� | 3鍗★細8.2灏忔椂 |
| 鍙傛暟 (M) | 27.29M |
| 璋冧紭妫€鏌ョ偣 | 336.3M 锛�.ckpt 鏂囦欢锛� |
-| 鑴氭湰 | [RetinaFace鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/retinaface_resnet50) |
+| 鑴氭湰 | [RetinaFace鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/retinaface_resnet50) |
## 鐢ㄦ硶
@@ -305,4 +305,4 @@ RetinaFace浣跨敤ResNet50楠ㄥ共鎻愬彇鍥惧儚鐗瑰緛杩涜妫€娴嬨€備粠ModelZoo鑾峰彇
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/retinanet/README_CN.md b/official/cv/retinanet/README_CN.md
index 72076957c3aa9f2d8f7d61ca3371d12a4c23c240..235181586052f5f2f7f76e4992617c0081cf2c97 100644
--- a/official/cv/retinanet/README_CN.md
+++ b/official/cv/retinanet/README_CN.md
@@ -190,7 +190,7 @@ bash scripts/run_single_train.sh DEVICE_ID MINDRECORD_DIR PRE_TRAINED(optional)
> 娉ㄦ剰:
- RANK_TABLE_FILE鐩稿叧鍙傝€冭祫鏂欒[閾炬帴](https://www.mindspore.cn/docs/programming_guide/zh-CN/master/distributed_training_ascend.html), 鑾峰彇device_ip鏂规硶璇﹁[閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+ RANK_TABLE_FILE鐩稿叧鍙傝€冭祫鏂欒[閾炬帴](https://www.mindspore.cn/docs/programming_guide/zh-CN/master/distributed_training_ascend.html), 鑾峰彇device_ip鏂规硶璇﹁[閾炬帴](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
#### 杩愯
@@ -445,7 +445,7 @@ mAP: 0.3499478734634595
| 鏈€缁堟崯澶� | 0.582 |
| 绮剧‘搴� (8p) | mAP[0.3475] |
| 璁粌鎬绘椂闂� (8p) | 23h16m54s |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/retinanet) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/retinanet) |
#### 鎺ㄧ悊鎬ц兘
@@ -466,4 +466,4 @@ mAP: 0.3499478734634595
## [ModelZoo 涓婚〉](#content)
-璇锋牳瀵瑰畼鏂� [涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+璇锋牳瀵瑰畼鏂� [涓婚〉](https://gitee.com/mindspore/models).
diff --git a/official/cv/shufflenetv1/README_CN.md b/official/cv/shufflenetv1/README_CN.md
index baca46001f7aa50082cba4728bd93a47d37d10e4..318ec7a93fe988570532a3f9125dd43d4afc0c1c 100644
--- a/official/cv/shufflenetv1/README_CN.md
+++ b/official/cv/shufflenetv1/README_CN.md
@@ -155,7 +155,7 @@ ShuffleNetV1鐨勬牳蹇冮儴鍒嗚鍒嗘垚涓変釜闃舵锛屾瘡涓樁娈甸噸澶嶅爢绉簡
璇烽伒寰互涓嬮摼鎺ヤ腑鐨勮鏄庯細
- [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)
+ [閾炬帴](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)
### 缁撴灉
@@ -322,7 +322,7 @@ Densenet121缃戠粶浣跨敤ImageNet鎺ㄧ悊寰楀埌鐨勭粨鏋滃涓�:
| 璁粌鎬绘椂闂� (8p) | 7.0h | 20.0h |
| 璇勪及鎬绘椂闂� | 99s | 58s |
| 鍙傛暟閲� (M) | 44M | 51.3M |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/shufflenetv1) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/shufflenetv1) |
# 闅忔満鎯呭喌鐨勬弿杩�
@@ -330,4 +330,4 @@ Densenet121缃戠粶浣跨敤ImageNet鎺ㄧ悊寰楀埌鐨勭粨鏋滃涓�:
# ModelZoo
-璇锋牳瀵瑰畼鏂� [涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋牳瀵瑰畼鏂� [涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/shufflenetv2/README.md b/official/cv/shufflenetv2/README.md
index 405525cafaaa4d443ac6face70be271db937ba19..0f065d816808ed0efcd34827266e24b4829f6045 100644
--- a/official/cv/shufflenetv2/README.md
+++ b/official/cv/shufflenetv2/README.md
@@ -150,4 +150,4 @@ Inference result will be stored in the example path, you can find result in `eva
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/simclr/README.md b/official/cv/simclr/README.md
index d14c5dda60a073131f0b39662d93ff158bb8367b..becf2bbc0e350fbb279cd356df7bf7f666412c92 100644
--- a/official/cv/simclr/README.md
+++ b/official/cv/simclr/README.md
@@ -246,7 +246,7 @@ Inference result is saved in current path, you can find result in acc.log file.
| Loss Function | NT-Xent Loss |
| linear eval | 84.505% |
| Total time | 25m04s |
-| Scripts | [SimCLR Script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/simclr) | [SimCLR Script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/simclr) |
+| Scripts | [SimCLR Script](https://gitee.com/mindspore/models/tree/master/official/cv/simclr) | [SimCLR Script](https://gitee.com/mindspore/models/tree/master/official/cv/simclr) |
## [Description of Random Situation](#contents)
@@ -254,4 +254,4 @@ We set the seed inside dataset.py. We also use random seed in train.py.
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/simple_pose/README.md b/official/cv/simple_pose/README.md
index 84db42fb46b62fb9e9ecbc87ceaddc74df6619ae..9a78c5ca07ce3312d9c734ab7fca30fff3e2f32d 100644
--- a/official/cv/simple_pose/README.md
+++ b/official/cv/simple_pose/README.md
@@ -90,7 +90,7 @@ You also need the person detection result of COCO val2017 to reproduce the multi
## [Model Checkpoints](#contents)
-Before you start your training process, you need to obtain mindspore imagenet pretrained models. The model weight file can be obtained by running the Resnet training script in [official model zoo](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet). We also provide a pretrained model that can be used to train SimplePoseNet directly in [GoogleDrive](https://drive.google.com/file/d/1r3Hs0QNys0HyNtsQhSvx6IKdyRkC-3Hh/view?usp=sharing). The model file should be placed under `<ROOT>/models/` like this:
+Before you start your training process, you need to obtain mindspore imagenet pretrained models. The model weight file can be obtained by running the Resnet training script in [official model zoo](https://gitee.com/mindspore/models/tree/master/official/cv/resnet). We also provide a pretrained model that can be used to train SimplePoseNet directly in [GoogleDrive](https://drive.google.com/file/d/1r3Hs0QNys0HyNtsQhSvx6IKdyRkC-3Hh/view?usp=sharing). The model file should be placed under `<ROOT>/models/` like this:
```text
鈹斺攢 <ROOT>
@@ -461,4 +461,4 @@ In `src/dataset.py`, we set the seed inside 鈥渃reate_dataset" function. We also
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/squeezenet/README.md b/official/cv/squeezenet/README.md
index 894fc71ba58cff379b1a7bfa4a75e459896985c1..d8136687b522234d23f526025a215a204c54a0f0 100644
--- a/official/cv/squeezenet/README.md
+++ b/official/cv/squeezenet/README.md
@@ -68,7 +68,7 @@ For FP16 operators, if the input data type is FP32, the backend of MindSpore wil
# [Environment Requirements](#contents)
- Hardware锛圓scend/CPU锛�
- - Prepare hardware environment with Ascend processor. Squeezenet training on GPU performs is not good now, and it is still in research. See [squeezenet in research](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/squeezenet) to get up-to-date details.
+ - Prepare hardware environment with Ascend processor. Squeezenet training on GPU performs is not good now, and it is still in research. See [squeezenet in research](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet) to get up-to-date details.
- Framework
- [MindSpore](https://www.mindspore.cn/install/en)
- For more information, please check the resources below锛�
@@ -311,7 +311,7 @@ For more configuration details, please refer the file `*.yaml`.
For distributed training, a hccl configuration file with JSON format needs to be created in advance.
-Please follow the instructions in the link [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+Please follow the instructions in the link [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
Training result will be stored in the example path, whose folder name begins with "train" or "train_parallel". Under this, you can find checkpoint file together with result like the followings in log.
@@ -513,7 +513,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Total time | 1pc: 55.5 mins; 8pcs: 15.0 mins | 1pc: 90mins; 8pcs: 34mins |
| Parameters (M) | 4.8 | 0.74 |
| Checkpoint for Fine tuning | 6.4M (.ckpt file) | 6.4M (.ckpt file)|
-| Scripts | [squeezenet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/squeezenet) | [squeezenet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/squeezenet) |
+| Scripts | [squeezenet script](https://gitee.com/mindspore/models/tree/master/official/cv/squeezenet) | [squeezenet script](https://gitee.com/mindspore/models/tree/master/official/cv/squeezenet) |
#### SqueezeNet on ImageNet
@@ -533,7 +533,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Total time | 8pcs: 5.2 hours | 8pcs: 12.1 hours |
| Parameters (M) | 4.8 | 1.25 |
| Checkpoint for Fine tuning | 13.3M (.ckpt file) | 13.3M (.ckpt file) |
-| Scripts | [squeezenet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/squeezenet) | [squeezenet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/squeezenet) |
+| Scripts | [squeezenet script](https://gitee.com/mindspore/models/tree/master/official/cv/squeezenet) | [squeezenet script](https://gitee.com/mindspore/models/tree/master/official/cv/squeezenet) |
#### SqueezeNet_Residual on CIFAR-10
@@ -553,7 +553,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Total time | 1pc: 68.6 mins; 8pcs: 20.9 mins | 1pc: 115 mins; 8pcs: 43.5 mins |
| Parameters (M) | 4.8 | 0.74 |
| Checkpoint for Fine tuning | 6.5M (.ckpt file) | 6.5M (.ckpt file) |
-| Scripts | [squeezenet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/squeezenet) | [squeezenet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/squeezenet) |
+| Scripts | [squeezenet script](https://gitee.com/mindspore/models/tree/master/official/cv/squeezenet) | [squeezenet script](https://gitee.com/mindspore/models/tree/master/official/cv/squeezenet) |
#### SqueezeNet_Residual on ImageNet
@@ -573,7 +573,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Total time | 8pcs: 8.0 hours | 8pcs: 18.4 hours |
| Parameters (M) | 4.8 | 1.25 |
| Checkpoint for Fine tuning | 15.3M (.ckpt file) | 15.3M (.ckpt file) |
-| Scripts | [squeezenet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/squeezenet) | [squeezenet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/squeezenet) |
+| Scripts | [squeezenet script](https://gitee.com/mindspore/models/tree/master/official/cv/squeezenet) | [squeezenet script](https://gitee.com/mindspore/models/tree/master/official/cv/squeezenet) |
### Inference Performance
@@ -795,4 +795,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/srcnn/README.md b/official/cv/srcnn/README.md
index 144a9ba87139d75b3acd532fbe413be72f22a607..764b2d5f181c02bc20366c9b777cc15308a2210d 100644
--- a/official/cv/srcnn/README.md
+++ b/official/cv/srcnn/README.md
@@ -172,4 +172,4 @@ result {'PSNR': 36.72421418219669}
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/ssd/README.md b/official/cv/ssd/README.md
index 7b486f2d2e11d4f05aed19b83a73d80d10030c73..534b63cc70c5f8ee2b112a2fc0776cbd0d215583 100644
--- a/official/cv/ssd/README.md
+++ b/official/cv/ssd/README.md
@@ -331,7 +331,7 @@ We need five or seven parameters for this scripts.
- `EPOCH_NUM`: epoch num for distributed train.
- `LR`: learning rate init value for distributed train.
- `DATASET`锛歵he dataset mode for distributed train.
-- `RANK_TABLE_FILE :` the path of [rank_table.json](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools), it is better to use absolute path.
+- `RANK_TABLE_FILE :` the path of [rank_table.json](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools), it is better to use absolute path.
- `CONFIG_PATH`: parameter configuration.
- `PRE_TRAINED :` the path of pretrained checkpoint file, it is better to use absolute path.
- `PRE_TRAINED_EPOCH_SIZE :` the epoch num of pretrained.
@@ -607,7 +607,7 @@ mAP: 0.23657619676441116
| Speed | 8pcs: 90ms/step | 8pcs: 121ms/step | 8pcs: 547ms/step |1pcs: 547ms/step |
| Total time | 8pcs: 4.81hours | 8pcs: 12.31hours | 8pcs: 4.22hours |1pcs: 4.22hours |
| Parameters (M) | 34 | 34 | 48M |97M |
-| Scripts | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd> | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd> | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd> |<https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd> |
+| Scripts | <https://gitee.com/mindspore/models/tree/master/official/cv/ssd> | <https://gitee.com/mindspore/models/tree/master/official/cv/ssd> | <https://gitee.com/mindspore/models/tree/master/official/cv/ssd> |<https://gitee.com/mindspore/models/tree/master/official/cv/ssd> |
#### Inference Performance
@@ -629,4 +629,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
## [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/ssd/README_CN.md b/official/cv/ssd/README_CN.md
index 6ff9b47f19d9d5807b1f31bc84d5e13761704693..555587c1d4f9306c746489aa04350fb655ae035a 100644
--- a/official/cv/ssd/README_CN.md
+++ b/official/cv/ssd/README_CN.md
@@ -268,7 +268,7 @@ bash run_eval_gpu.sh [DATASET] [CHECKPOINT_PATH] [DEVICE_ID] [CONFIG_PATH]
- `EPOCH_NUM`锛氬垎甯冨紡璁粌鐨勮疆娆℃暟銆�
- `LR`锛氬垎甯冨紡璁粌鐨勫涔犵巼鍒濆鍊笺€�
- `DATASET`锛氬垎甯冨紡璁粌鐨勬暟鎹泦妯″紡銆�
-- `RANK_TABLE_FILE`锛歔rank_table.json](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)鐨勮矾寰勩€傛渶濂戒娇鐢ㄧ粷瀵硅矾寰勩€�
+- `RANK_TABLE_FILE`锛歔rank_table.json](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)鐨勮矾寰勩€傛渶濂戒娇鐢ㄧ粷瀵硅矾寰勩€�
- `CONFIG_PATH`: 鍙傛暟閰嶇疆銆�
- `PRE_TRAINED`锛氶璁粌妫€鏌ョ偣鏂囦欢鐨勮矾寰勩€傛渶濂戒娇鐢ㄧ粷瀵硅矾寰勩€�
- `PRE_TRAINED_EPOCH_SIZE`锛氶璁粌鐨勮疆娆℃暟銆�
@@ -528,7 +528,7 @@ mAP: 0.23657619676441116
| 閫熷害 | 8鍗★細90姣/姝� | 8鍗★細121姣/姝� |
| 鎬绘椂闀� | 8鍗★細4.81灏忔椂 | 8鍗★細12.31灏忔椂 |
| 鍙傛暟(M) | 34 | 34 |
-|鑴氭湰 | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/ssd |
+|鑴氭湰 | https://gitee.com/mindspore/models/tree/master/official/cv/ssd | https://gitee.com/mindspore/models/tree/master/official/cv/ssd |
### 鎺ㄧ悊鎬ц兘
@@ -550,4 +550,4 @@ dataset.py涓缃簡鈥渃reate_dataset鈥濆嚱鏁板唴鐨勭瀛愶紝鍚屾椂杩樹娇鐢�
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/tinydarknet/README.md b/official/cv/tinydarknet/README.md
index c34f41447c98a35db8af0edf0d4ecbb400f36497..2bdca4270d4a37f3296d26f095eabd55b2fc9a1b 100644
--- a/official/cv/tinydarknet/README.md
+++ b/official/cv/tinydarknet/README.md
@@ -91,7 +91,7 @@ After installing MindSpore via the official website, you can start training and
Please follow the instructions in the link below:
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.>
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools.>
- running on GPU with gpu default parameters
@@ -500,7 +500,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Loss Function | Softmax Cross Entropy | Softmax Cross Entropy |
| Speed | 8pc: 104 ms/step | 8pc: 255 ms/step |
| Parameters(M) | 4.0; | 4.0; |
-| Scripts | [Tiny-Darknet scripts](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/tinydarknet)
+| Scripts | [Tiny-Darknet scripts](https://gitee.com/mindspore/models/tree/master/official/cv/tinydarknet)
### [Evaluation Performance](#contents)
@@ -532,4 +532,4 @@ Inference result is saved in current path, you can find result like this in acc.
# [ModelZoo Homepage](#contents)
- Please check the official[homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official[homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/tinydarknet/README_CN.md b/official/cv/tinydarknet/README_CN.md
index 9514a3a5744410454c7d67327156a46f734038c5..2942d0c59328c412e0626517990f9f121de28649 100644
--- a/official/cv/tinydarknet/README_CN.md
+++ b/official/cv/tinydarknet/README_CN.md
@@ -99,7 +99,7 @@ Tiny-DarkNet鏄疛oseph Chet Redmon绛変汉鎻愬嚭鐨勪竴涓�16灞傜殑閽堝浜庣粡鍏哥殑
璇锋寜鐓т互涓嬮摼鎺ョ殑鎸囧杩涜璁剧疆:
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.>
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools.>
- running on GPU with gpu default parameters
@@ -509,7 +509,7 @@ bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [LABEL_PATH] [DVPP] [DEVICE_ID]
| 閫熷害 | 8鍗�: 104 ms/step | 8鍗�: 255 ms/step |
| 鎬绘椂闂� | 8鍗�: 17.8灏忔椂 | 8鍗�: 46.9灏忔椂 |
| 鍙傛暟(M) | 4.0; | 4.0; |
-| 鑴氭湰 | [Tiny-Darknet鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/tinydarknet)
+| 鑴氭湰 | [Tiny-Darknet鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/tinydarknet)
### [璇勪及鎬ц兘](#鐩綍)
@@ -541,4 +541,4 @@ bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [LABEL_PATH] [DVPP] [DEVICE_ID]
# [ModelZoo涓婚〉](#鐩綍)
- 璇峰弬鑰冨畼鏂筟涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ 璇峰弬鑰冨畼鏂筟涓婚〉](https://gitee.com/mindspore/models).
diff --git a/official/cv/unet/README.md b/official/cv/unet/README.md
index 8fbd7fa0f5cf2ee349c5907133fa1040a9bff38e..f75549cca7dbfc1d0b26b51bac6d6a6a5f9a5b90 100644
--- a/official/cv/unet/README.md
+++ b/official/cv/unet/README.md
@@ -473,7 +473,7 @@ The above python command will run in the background. You can view the results th
| Total time | 1pc: 2.67 mins; | 1pc: 5.64 mins; |
| Parameters (M) | 93M | 93M |
| Checkpoint for Fine tuning | 355.11M (.ckpt file) | 355.11M (.ckpt file) |
-| Scripts | [unet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/unet) | [unet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/unet) |
+| Scripts | [unet script](https://gitee.com/mindspore/models/tree/master/official/cv/unet) | [unet script](https://gitee.com/mindspore/models/tree/master/official/cv/unet) |
| Parameters | Ascend | GPU |
| -----| ----- | ----- |
@@ -492,7 +492,7 @@ The above python command will run in the background. You can view the results th
| Total time | 1pc: 10.8min | 1pc锛�8min |
| Parameters (M) | 27M | 27M |
| Checkpoint for Fine tuning | 103.4M(.ckpt file) | 103.4M(.ckpt file) |
-| Scripts | [unet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/unet) | [unet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/unet) |
+| Scripts | [unet script](https://gitee.com/mindspore/models/tree/master/official/cv/unet) | [unet script](https://gitee.com/mindspore/models/tree/master/official/cv/unet) |
## [How to use](#contents)
@@ -616,4 +616,4 @@ In data_loader.py, we set the seed inside 鈥淿get_val_train_indices" function. W
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
\ No newline at end of file
+Please check the official [homepage](https://gitee.com/mindspore/models).
\ No newline at end of file
diff --git a/official/cv/unet/README_CN.md b/official/cv/unet/README_CN.md
index 2e304254afe4e8f38a4105b66a7153fad32d1756..65012dd3636adb84f94b3076ab8a49291a154ee2 100644
--- a/official/cv/unet/README_CN.md
+++ b/official/cv/unet/README_CN.md
@@ -472,7 +472,7 @@ bash scripts/run_distribute_train_gpu.sh [RANKSIZE] [DATASET] [CONFIG_PATH]
| 鎬绘椂闀� | 1鍗★細2.67鍒嗛挓锛�8鍗★細1.40鍒嗛挓 | 1鍗★細5.64鍒嗛挓锛�8鍗★細3.41鍒嗛挓 |
| 鍙傛暟(M) | 93M | 93M |
| 寰皟妫€鏌ョ偣 | 355.11M (.ckpt鏂囦欢) | 355.11M (.ckpt鏂囦欢) |
-| 鑴氭湰 | [U-Net鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/unet) | [U-Net鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/unet) |
+| 鑴氭湰 | [U-Net鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/unet) | [U-Net鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/unet) |
| 鍙傛暟 | Ascend | GPU |
| ----- | ------ | ----- |
@@ -491,7 +491,7 @@ bash scripts/run_distribute_train_gpu.sh [RANKSIZE] [DATASET] [CONFIG_PATH]
| 鎬绘椂闀� | 1鍗�: 10.8鍒嗛挓 | 1鍗�: 8鍒嗛挓 |
| 鍙傛暟(M) | 27M | 27M |
| 寰皟妫€鏌ョ偣 | 103.4M(.ckpt鏂囦欢) | 103.4M(.ckpt鏂囦欢) |
-| 鑴氭湰 | [U-Net鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/unet) | [U-Net鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/unet) |
+| 鑴氭湰 | [U-Net鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/unet) | [U-Net鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/unet) |
### 鐢ㄦ硶
@@ -609,4 +609,4 @@ dataset.py涓缃簡鈥渟eet_sed鈥濆嚱鏁板唴鐨勭瀛愶紝鍚屾椂杩樹娇鐢ㄤ簡train
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/unet3d/README.md b/official/cv/unet3d/README.md
index 146b50c0b5d26ab834b318aceb656243e6d71423..0cad140435fd79e4910134fe4c6b0019279fe1f9 100644
--- a/official/cv/unet3d/README.md
+++ b/official/cv/unet3d/README.md
@@ -285,7 +285,7 @@ After training, you'll get some checkpoint files under the `train_parallel_fp[32
#### Distributed training on Ascend
> Notes:
-> RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html) , and the device_ip can be got as [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools). For large models like InceptionV4, it's better to export an external environment variable `export HCCL_CONNECT_TIMEOUT=600` to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
+> RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html) , and the device_ip can be got as [Link](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools). For large models like InceptionV4, it's better to export an external environment variable `export HCCL_CONNECT_TIMEOUT=600` to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
>
```shell
@@ -405,7 +405,7 @@ eval average dice is 0.9502010010453671
| Speed | 8pcs: 1795ms/step | 8pcs: 1883ms/step |
| Total time | 8pcs: 0.62hours | 8pcs: 0.66hours |
| Parameters (M) | 34 | 34 |
-| Scripts | [unet3d script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/unet3d) |
+| Scripts | [unet3d script](https://gitee.com/mindspore/models/tree/master/official/cv/unet3d) |
#### Inference Performance
@@ -426,4 +426,4 @@ We set seed to 1 in train.py.
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/vgg16/README.md b/official/cv/vgg16/README.md
index 902fc41e3c90382ce430582d2319637b65728e8f..041bf395adb3bacedf31f51d5e54e5a58a7c5c83 100644
--- a/official/cv/vgg16/README.md
+++ b/official/cv/vgg16/README.md
@@ -126,7 +126,7 @@ python eval.py --config_path=[YAML_CONFIG_PATH] --data_dir=[DATA_PATH] --pre_tr
For distributed training, a hccl configuration file with JSON format needs to be created in advance.
Please follow the instructions in the link below:
-<https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>
+<https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>
- Running on GPU
@@ -586,7 +586,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Speed | 1pc: 79 ms/step; 8pcs: 104 ms/step |1pc: 81 ms/step; 8pcs 94.4ms/step |
| Total time | 1pc: 72 mins; 8pcs: 11.8 mins |8pcs: 19.7 hours |
| Checkpoint for Fine tuning | 1.1G(.ckpt file) |1.1G(.ckpt file) |
-| Scripts |[vgg16](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/vgg16) | |
+| Scripts |[vgg16](https://gitee.com/mindspore/models/tree/master/official/cv/vgg16) | |
#### Evaluation Performance
@@ -607,4 +607,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/vgg16/README_CN.md b/official/cv/vgg16/README_CN.md
index 740a1d3b57a1b73a3afe625e1951e5626ae73b2e..65e79d3169688f11c1219e0623afdcbc27ae102f 100644
--- a/official/cv/vgg16/README_CN.md
+++ b/official/cv/vgg16/README_CN.md
@@ -128,7 +128,7 @@ python eval.py --config_path=[YAML_CONFIG_PATH] --data_dir=[DATA_PATH] --pre_tr
鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆�
鍏蜂綋鎿嶄綔锛屽弬瑙侊細
-<https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>
+<https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>
- GPU澶勭悊鍣ㄧ幆澧冭繍琛�
@@ -588,7 +588,7 @@ bash run_quant_infer.sh [AIR_PATH] [DATA_PATH] [LABEL_PATH]
| 閫熷害 | 1鍗★細79 姣/姝ワ紱8鍗★細104姣/姝� | 1鍗★細81姣/姝ワ紱8鍗★細94.4姣/姝� |
| 鎬绘椂闀� | 1鍗★細72鍒嗛挓锛�8鍗★細11.8鍒嗛挓 | 8鍗★細19.7灏忔椂 |
| 璋冧紭妫€鏌ョ偣 | 1.1 GB锛�.ckpt 鏂囦欢锛� | 1.1 GB锛�.ckpt 鏂囦欢锛� |
-| 鑴氭湰 |[VGG16](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/vgg16) | |
+| 鑴氭湰 |[VGG16](https://gitee.com/mindspore/models/tree/master/official/cv/vgg16) | |
#### 璇勪及鎬ц兘
@@ -609,4 +609,4 @@ dataset.py涓缃簡鈥渃reate_dataset鈥濆嚱鏁板唴鐨勭瀛愶紝鍚屾椂杩樹娇鐢�
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/vit/README.md b/official/cv/vit/README.md
index 17fd82df836ed594570aee202d369224e016ba46..c3325693e20420dbc6740c804bde8060a5fab6c8 100644
--- a/official/cv/vit/README.md
+++ b/official/cv/vit/README.md
@@ -105,7 +105,7 @@ After installing MindSpore via the official website, you can start training and
Please follow the instructions in the link below:
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>.
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>.
- ModelArts (If you want to run in modelarts, please check the official documentation of [modelarts](https://support.huaweicloud.com/modelarts/), and you can start training as follows)
@@ -523,4 +523,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/vit/README_CN.md b/official/cv/vit/README_CN.md
index 54f81702760237c55b3df05b992de9ee825ce191..f8f96aea7a443621c4cb5fca1d19f3db8fc5f79c 100644
--- a/official/cv/vit/README_CN.md
+++ b/official/cv/vit/README_CN.md
@@ -108,7 +108,7 @@ Vit鏄熀浜庡涓猼ransformer encoder妯″潡涓茶仈璧锋潵锛岀敱澶氫釜inception妯�
璇烽伒寰互涓嬮摼鎺ヤ腑鐨勮鏄庯細
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.>
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools.>
- 鍦� ModelArts 杩涜璁粌 (濡傛灉浣犳兂鍦╩odelarts涓婅繍琛岋紝鍙互鍙傝€冧互涓嬫枃妗� [modelarts](https://support.huaweicloud.com/modelarts/))
@@ -529,4 +529,4 @@ python export.py --config_path=[CONFIG_PATH]
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/warpctc/README.md b/official/cv/warpctc/README.md
index a58e355d230a6b2ca33c07556d53c7401cc148a0..079a49fd740a9e72ec4f693259a28e689f177250 100644
--- a/official/cv/warpctc/README.md
+++ b/official/cv/warpctc/README.md
@@ -89,7 +89,7 @@ The dataset is self-generated using a third-party library called [captcha](https
Please follow the instructions in the link below:
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>.
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>.
- Running on GPU
@@ -361,7 +361,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Total time | 30 mins | 5 mins|
| Parameters (M) | 2.75 | 2.75 |
| Checkpoint for Fine tuning | 20.3M (.ckpt file) | 20.3M (.ckpt file) |
-| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/warpctc) | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/warpctc) |
+| Scripts | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/warpctc) | [Link](https://gitee.com/mindspore/models/tree/master/official/cv/warpctc) |
#### [Evaluation Performance](#contents)
@@ -397,4 +397,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/warpctc/README_CN.md b/official/cv/warpctc/README_CN.md
index 359285aeb81f05b98da572cdad1aed4006c63994..a5e13ec146426895fd04bfa054e8761934db732e 100644
--- a/official/cv/warpctc/README_CN.md
+++ b/official/cv/warpctc/README_CN.md
@@ -92,7 +92,7 @@ WarpCTC鏄甫鏈変竴灞侳C绁炵粡缃戠粶鐨勪簩灞傚爢鍙燣STM妯″瀷銆傝缁嗕俊鎭
璇︽儏鍙傝濡備笅閾炬帴锛�
- [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)
+ [閾炬帴](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)
- 鍦℅PU鐜杩愯
@@ -364,7 +364,7 @@ bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DEVICE_ID]
| 鎬绘椂闀� | 30鍒嗛挓 | 5鍒嗛挓|
| 鍙傛暟(M) | 2.75 | 2.75 |
| 寰皟妫€鏌ョ偣 | 20.3M (.ckpt鏂囦欢) | 20.3M (.ckpt鏂囦欢) |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/warpctc) | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/warpctc) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/warpctc) | [閾炬帴](https://gitee.com/mindspore/models/tree/master/official/cv/warpctc) |
#### 璇勪及鎬ц兘
@@ -400,4 +400,4 @@ bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DEVICE_ID]
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/xception/README.md b/official/cv/xception/README.md
index ebcb0750df683ffbd21181a3f9ed00e084b36fd7..c4e8222cba21fb6ba3e6c5ea0669ae288e45d9cb 100644
--- a/official/cv/xception/README.md
+++ b/official/cv/xception/README.md
@@ -193,7 +193,7 @@ bash run_eval_gpu.sh DEVICE_ID DATASET_PATH CHECKPOINT_PATH
bash run_infer_310.sh MINDIR_PATH DATA_PATH LABEL_FILE DEVICE_ID
```
-> Notes: RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html), and the device_ip can be got as [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+> Notes: RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html), and the device_ip can be got as [Link](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
### Launch
@@ -420,7 +420,7 @@ Top_1_Acc: 0.79886%, Top_5_Acc: 0.94882%
| Per step time (8p) | 479 ms/step | 282 ms/step |
| Total time (8p) | 42h | 51h |
| Params (M) | 180M | 180M |
-| Scripts | [Xception script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/xception) | [Xception script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/xception) |
+| Scripts | [Xception script](https://gitee.com/mindspore/models/tree/master/official/cv/xception) | [Xception script](https://gitee.com/mindspore/models/tree/master/official/cv/xception) |
#### Inference Performance
@@ -441,4 +441,4 @@ In `dataset.py`, we set the seed inside `create_dataset` function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/yolov3_darknet53/README.md b/official/cv/yolov3_darknet53/README.md
index 7635f403d977d40bbb5b6470f243375282754f12..5d276089bf5d7d159a4fb145bbc5f9d0250f0784 100644
--- a/official/cv/yolov3_darknet53/README.md
+++ b/official/cv/yolov3_darknet53/README.md
@@ -509,7 +509,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Total time | 8pc: 13 hours | 8pc: 18 hours(shape=416) |
| Parameters (M) | 62.1 | 62.1 |
| Checkpoint for Fine tuning | 474M (.ckpt file) | 474M (.ckpt file) |
-| Scripts | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_darknet53 | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_darknet53 |
+| Scripts | https://gitee.com/mindspore/models/tree/master/official/cv/yolov3_darknet53 | https://gitee.com/mindspore/models/tree/master/official/cv/yolov3_darknet53 |
#### Inference Performance
@@ -531,4 +531,4 @@ There are random seeds in distributed_sampler.py, transforms.py, yolo_dataset.py
## [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/yolov3_darknet53/README_CN.md b/official/cv/yolov3_darknet53/README_CN.md
index eda3c03a0aaf0a8041ac1e8e14cb8fbf16d0be66..a61999d918d88f5d7ccc6c6bd4480cd85621a469 100644
--- a/official/cv/yolov3_darknet53/README_CN.md
+++ b/official/cv/yolov3_darknet53/README_CN.md
@@ -502,7 +502,7 @@ bash run_quant_infer.sh [AIR_PATH] [DATA_PATH] [IMAGE_ID] [IMAGE_SHAPE] [ANN_FIL
| 鎬绘椂闀� | 8鍗★細13灏忔椂 | 8鍗�: 18灏忔椂(shape=416) |
| 鍙傛暟(M) | 62.1 | 62.1 |
| 寰皟妫€鏌ョ偣 | 474M (.ckpt鏂囦欢) | 474M (.ckpt鏂囦欢) |
-| 鑴氭湰 | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_darknet53 | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_darknet53 |
+| 鑴氭湰 | https://gitee.com/mindspore/models/tree/master/official/cv/yolov3_darknet53 | https://gitee.com/mindspore/models/tree/master/official/cv/yolov3_darknet53 |
### 鎺ㄧ悊鎬ц兘
@@ -524,4 +524,4 @@ bash run_quant_infer.sh [AIR_PATH] [DATA_PATH] [IMAGE_ID] [IMAGE_SHAPE] [ANN_FIL
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/yolov3_darknet53_quant/README.md b/official/cv/yolov3_darknet53_quant/README.md
index f10bc02e80010556aca1d86d7762d6f2355e7521..ad2bff29e36375722a9b66e9a40c2d60d99aabf2 100644
--- a/official/cv/yolov3_darknet53_quant/README.md
+++ b/official/cv/yolov3_darknet53_quant/README.md
@@ -325,7 +325,7 @@ Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.555
| Total time | 8pc: 23.5 hours |
| Parameters (M) | 62.1 |
| Checkpoint for Fine tuning | 474M (.ckpt file) |
-| Scripts | [YoloV3-DarkNet53-Quant Script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_darknet53_quant) |
+| Scripts | [YoloV3-DarkNet53-Quant Script](https://gitee.com/mindspore/models/tree/master/official/cv/yolov3_darknet53_quant) |
#### Inference Performance
@@ -347,4 +347,4 @@ There are random seeds in distributed_sampler.py, transforms.py, yolo_dataset.py
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/yolov3_darknet53_quant/README_CN.md b/official/cv/yolov3_darknet53_quant/README_CN.md
index 2ef0b23307d84cd32447482a42e4b46e34bbb5f3..ff0f48692f37405787cd17dd159caab1ed4316e9 100644
--- a/official/cv/yolov3_darknet53_quant/README_CN.md
+++ b/official/cv/yolov3_darknet53_quant/README_CN.md
@@ -336,7 +336,7 @@ Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.555
| 鎬绘椂闀� | 8鍗★細23.5灏忔椂 |
| 鍙傛暟 (M) | 62.1 |
| 寰皟妫€鏌ョ偣 | 474M (.ckpt鏂囦欢) |
-| 鑴氭湰 | [YoloV3-DarkNet53-Quant鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_darknet53_quant) |
+| 鑴氭湰 | [YoloV3-DarkNet53-Quant鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/yolov3_darknet53_quant) |
#### 鎺ㄧ悊鎬ц兘
@@ -358,4 +358,4 @@ Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.555
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/yolov3_resnet18/README.md b/official/cv/yolov3_resnet18/README.md
index c3d57d5a8a8cb36f6dd2ab858fb593a5bc764d65..094be542a8a058a99248661ce9b558df299ec574 100644
--- a/official/cv/yolov3_resnet18/README.md
+++ b/official/cv/yolov3_resnet18/README.md
@@ -283,7 +283,7 @@ To train the model, run `train.py` with the dataset `image_dir`, `anno_path` and
bash run_distribute_train.sh 8 150 /data/Mindrecord_train /data /data/train.txt /data/hccl.json
```
- The input variables are device numbers, epoch size, mindrecord directory path, dataset directory path, train TXT file path and [hccl json configuration file](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools). **It is better to use absolute path.**
+ The input variables are device numbers, epoch size, mindrecord directory path, dataset directory path, train TXT file path and [hccl json configuration file](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools). **It is better to use absolute path.**
You will get the loss value and time of each step as following:
@@ -417,7 +417,7 @@ class 1 precision is 94.61%, recall is 64.07%
| Speed | 1pc: 120 ms/step; 8pcs: 160 ms/step |
| Total time | 1pc: 150 mins; 8pcs: 70 mins |
| Parameters (M) | 189 |
-| Scripts | [yolov3_resnet18 script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_resnet18) | [yolov3_resnet18 script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_resnet18) |
+| Scripts | [yolov3_resnet18 script](https://gitee.com/mindspore/models/tree/master/official/cv/yolov3_resnet18) | [yolov3_resnet18 script](https://gitee.com/mindspore/models/tree/master/official/cv/yolov3_resnet18) |
### Inference Performance
@@ -438,5 +438,5 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/yolov3_resnet18/README_CN.md b/official/cv/yolov3_resnet18/README_CN.md
index 2cbb456bbaf73d4c63d111e46376c195c64dc8ec..04b78349e63d42ee80f6755d9fd68732525fae63 100644
--- a/official/cv/yolov3_resnet18/README_CN.md
+++ b/official/cv/yolov3_resnet18/README_CN.md
@@ -283,7 +283,7 @@ YOLOv3鏁翠綋缃戠粶鏋舵瀯濡備笅锛�
bash run_distribute_train.sh 8 150 /data/Mindrecord_train /data /data/train.txt /data/hccl.json
```
- 杈撳叆鍙橀噺涓鸿澶囩紪鍙枫€佽疆娆″ぇ灏忋€丮indRecord鐩綍璺緞銆佹暟鎹泦鐩綍璺緞銆佽缁僒XT鏂囦欢璺緞鍜孾hccl_tools閰嶇疆鏂囦欢](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)銆�**鏈€濂戒娇鐢ㄧ粷瀵硅矾寰勩€�**
+ 杈撳叆鍙橀噺涓鸿澶囩紪鍙枫€佽疆娆″ぇ灏忋€丮indRecord鐩綍璺緞銆佹暟鎹泦鐩綍璺緞銆佽缁僒XT鏂囦欢璺緞鍜孾hccl_tools閰嶇疆鏂囦欢](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)銆�**鏈€濂戒娇鐢ㄧ粷瀵硅矾寰勩€�**
姣忔鐨勬崯澶卞€煎拰鏃堕棿濡備笅锛�
@@ -414,7 +414,7 @@ class 1 precision is 94.61%, recall is 64.07%
| 閫熷害 | 1pc锛�120姣/姝�; 8鍗★細160姣/姝� |
| 鎬绘椂闀� | 1pc锛�150鍒嗛挓; 8鍗�: 70鍒嗛挓 |
| 鍙傛暟(M) | 189 |
-| 鑴氭湰 | [yolov3_resnet18鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_resnet18) | [yolov3_resnet18鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/yolov3_resnet18) |
+| 鑴氭湰 | [yolov3_resnet18鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/yolov3_resnet18) | [yolov3_resnet18鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/cv/yolov3_resnet18) |
### 鎺ㄧ悊鎬ц兘
@@ -435,4 +435,4 @@ class 1 precision is 94.61%, recall is 64.07%
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/yolov4/README.md b/official/cv/yolov4/README.md
index 338495e05217ef5de625d5f587492b013a5c70b5..db0cac1e0632c741805261a64239abdc5694c154 100644
--- a/official/cv/yolov4/README.md
+++ b/official/cv/yolov4/README.md
@@ -598,7 +598,7 @@ YOLOv4 on 118K images(The annotation and data format must be the same as coco201
| Speed | 1p 53FPS 8p 390FPS(shape=416) 220FPS(dynamic shape) |
| Total time | 48h(dynamic shape) |
| Checkpoint for Fine tuning | about 500M (.ckpt file) |
-| Scripts | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/> |
+| Scripts | <https://gitee.com/mindspore/models/tree/master/official/cv/yolov4> |
### Inference Performance
@@ -622,4 +622,4 @@ In var_init.py, we set seed for weight initialization
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/cv/yolov4/README_CN.md b/official/cv/yolov4/README_CN.md
index 58e90584295a0c9f2203693b13ecb5633d35faf9..3ddb7fd692cc9431fcb1cde251ecc8770a954204 100644
--- a/official/cv/yolov4/README_CN.md
+++ b/official/cv/yolov4/README_CN.md
@@ -604,7 +604,7 @@ YOLOv4搴旂敤浜�118000寮犲浘鍍忎笂锛堟爣娉ㄥ拰鏁版嵁鏍煎紡蹇呴』涓嶤OCO 2017鐩�
|閫熷害| 1鍗★細53FPS锛�8鍗★細390FPS (shape=416) 220FPS (鍔ㄦ€佸舰鐘�)|
|鎬绘椂闀縷48灏忔椂锛堝姩鎬佸舰鐘讹級|
|寰皟妫€鏌ョ偣|绾�500M锛�.ckpt鏂囦欢锛墊
-|鑴氭湰| <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/> |
+|鑴氭湰| <https://gitee.com/mindspore/models/tree/master/official/cv/yolov4> |
### 鎺ㄧ悊鎬ц兘
@@ -628,4 +628,4 @@ YOLOv4搴旂敤浜�20000寮犲浘鍍忎笂锛堟爣娉ㄥ拰鏁版嵁鏍煎紡蹇呴』涓嶤OCO test 2017
# [ModelZoo涓婚〉](#鐩綍)
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/cv/yolov5/README.md b/official/cv/yolov5/README.md
index 21e5517e464f1ec0591e2d4fe6af7258195aab60..83afcfa006248e98548ffe41f994373fe0da83f4 100644
--- a/official/cv/yolov5/README.md
+++ b/official/cv/yolov5/README.md
@@ -292,7 +292,7 @@ YOLOv5 on 118K images(The annotation and data format must be the same as coco201
| Speed | 8p about 450 FPS | 8p about 290 FPS |
| Total time | 8p 21h28min | 8p 35h |
| Checkpoint for Fine tuning | 53.62M (.ckpt file) | 58.87M (.ckpt file) |
-| Scripts | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/ | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/ |
+| Scripts | https://gitee.com/mindspore/models/tree/master/official/cv/yolov5 | https://gitee.com/mindspore/models/tree/master/official/cv/yolov5 |
### Inference Performance
@@ -315,4 +315,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/gnn/bgcf/README.md b/official/gnn/bgcf/README.md
index a3b671fff513a266d3fa27c99c29c62b5584e1f0..a5092151d3d43eefb561833724df2bb50b7a6642 100644
--- a/official/gnn/bgcf/README.md
+++ b/official/gnn/bgcf/README.md
@@ -385,7 +385,7 @@ recall_@10:0.10383, recall_@20:0.15524, ndcg_@10:0.07503, ndcg_@20:0.
| Optimizer | Adam | Adam |
| Loss Function | BPR loss | BPR loss |
| Training Cost | 25min | 60min |
-| Scripts | [bgcf script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/gnn/bgcf) | [bgcf script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/gnn/bgcf) |
+| Scripts | [bgcf script](https://gitee.com/mindspore/models/tree/master/official/gnn/bgcf) | [bgcf script](https://gitee.com/mindspore/models/tree/master/official/gnn/bgcf) |
#### Inference Performance
@@ -407,4 +407,4 @@ BGCF model contains lots of dropout operations, if you want to disable dropout,
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](http://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](http://gitee.com/mindspore/models).
diff --git a/official/gnn/bgcf/README_CN.md b/official/gnn/bgcf/README_CN.md
index f0b4ceadc20c53ec432e5eeb58cf2d5e3f3e8e98..dff906387ee8d6f2b2dbbdd09980505bae26e9de 100644
--- a/official/gnn/bgcf/README_CN.md
+++ b/official/gnn/bgcf/README_CN.md
@@ -407,7 +407,7 @@ recall_@10:0.10383, recall_@20:0.15524, ndcg_@10:0.07503, ndcg_@20:0.
| Recall@20 | 0.1534 | 0.15524 |
| NDCG@20 | 0.0912 | 0.09249 |
| 璁粌鎴愭湰 | 25min | 60min |
-| 鑴氭湰 | [bgcf鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/gnn/bgcf) | [bgcf鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/gnn/bgcf) |
+| 鑴氭湰 | [bgcf鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/gnn/bgcf) | [bgcf鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/gnn/bgcf) |
### 鎺ㄧ悊鎬ц兘
@@ -429,4 +429,4 @@ BGCF妯″瀷涓湁寰堝鐨刣ropout鎿嶄綔锛屽鏋滄兂鍏抽棴dropout锛屽彲浠ュ湪 ./de
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/gnn/gat/README.md b/official/gnn/gat/README.md
index 972e20bbbc3a17bf444e086b1b93c6d83e14c07d..932a9db85b469f9d01a348761678a6a144c56d11 100644
--- a/official/gnn/gat/README.md
+++ b/official/gnn/gat/README.md
@@ -281,7 +281,7 @@ test acc=0.84199995
| Accuracy | 83.0/72.5 |
| Speed | 0.195s/epoch |
| Total time | 39s |
-| Scripts | [GAT Script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/gnn/gat) |
+| Scripts | [GAT Script](https://gitee.com/mindspore/models/tree/master/official/gnn/gat) |
## [Description of random situation](#contents)
@@ -289,4 +289,4 @@ GAT model contains lots of dropout operations, if you want to disable dropout, s
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](http://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](http://gitee.com/mindspore/models).
diff --git a/official/gnn/gat/README_CN.md b/official/gnn/gat/README_CN.md
index d1f436f99c1aea47ed95ada21e47f1af0d909056..767c177b32a1dfc4d092e5e3928e6c97e067221b 100644
--- a/official/gnn/gat/README_CN.md
+++ b/official/gnn/gat/README_CN.md
@@ -278,7 +278,7 @@ test acc=0.84199995
| 鍑嗙‘鐜� | 83.0/72.5 |
| 閫熷害 | 0.195s/epoch |
| 鎬绘椂闀� | 39s |
-| 鑴氭湰 | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/gnn/gat> |
+| 鑴氭湰 | <https://gitee.com/mindspore/models/tree/master/official/gnn/gat> |
## 闅忔満鎯呭喌璇存槑
@@ -286,4 +286,4 @@ GAT妯″瀷涓湁寰堝鐨刣ropout鎿嶄綔锛屽鏋滄兂鍏抽棴dropout锛屽彲浠ュ湪src/co
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/gnn/gcn/README.md b/official/gnn/gcn/README.md
index 532f68a8da7530d13c0152449b385b97c07eed6f..402cb68c5ec20f96fb830f9766c2599b1c5174a6 100644
--- a/official/gnn/gcn/README.md
+++ b/official/gnn/gcn/README.md
@@ -267,7 +267,7 @@ Test set results: accuracy= 0.81300
| Loss Function | Softmax Cross Entropy |
| Accuracy | 81.5/70.3 |
| Parameters (B) | 92160/59344 |
-| Scripts | [GCN Script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/gnn/gcn) |
+| Scripts | [GCN Script](https://gitee.com/mindspore/models/tree/master/official/gnn/gcn) |
## [Description of Random Situation](#contents)
@@ -280,4 +280,4 @@ Some seeds have already been set in train.py to avoid the randomness of weight i
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/gnn/gcn/README_CN.md b/official/gnn/gcn/README_CN.md
index 629978b20ab711cd123e26cecb7cd835d93c7ecb..8f19122464082953da70a90919dfc4a28e384bee 100644
--- a/official/gnn/gcn/README_CN.md
+++ b/official/gnn/gcn/README_CN.md
@@ -269,7 +269,7 @@ Test set results: accuracy= 0.81300
| 鎹熷け鍑芥暟 | Softmax浜ゅ弶鐔� |
| 鍑嗙‘鐜� | 81.5/70.3 |
| 鍙傛暟(B) | 92160/59344 |
-| 鑴氭湰 | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/gnn/gcn> |
+| 鑴氭湰 | <https://gitee.com/mindspore/models/tree/master/official/gnn/gcn> |
## 闅忔満鎯呭喌璇存槑
@@ -282,4 +282,4 @@ train.py宸茬粡璁剧疆浜嗕竴浜涚瀛愶紝閬垮厤鏉冮噸鍒濆鍖栫殑闅忔満鎬с€傝嫢闇€
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/lite/MindSpore_inhand/common/src/main/java/com/mindspore/common/config/MSLinkUtils.java b/official/lite/MindSpore_inhand/common/src/main/java/com/mindspore/common/config/MSLinkUtils.java
index 038cab655a59295012b0d004e52de11308adb194..54df7c73072b3fdb006c5475c45ad4f0a4f5c5bc 100644
--- a/official/lite/MindSpore_inhand/common/src/main/java/com/mindspore/common/config/MSLinkUtils.java
+++ b/official/lite/MindSpore_inhand/common/src/main/java/com/mindspore/common/config/MSLinkUtils.java
@@ -25,6 +25,6 @@ public class MSLinkUtils {
public static final String ME_APK_URL = "https://download.mindspore.cn/model_zoo/official/lite/apk/mindmain.html";
public static final String ME_HELP_URL = "https://gitee.com/mindspore/mindspore/issues/new?issue%5Bassignee_id%5D=0&issue%5Bmilestone_id%5D=0";
- public static final String ME_CODE_URL = "https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/lite";
+ public static final String ME_CODE_URL = "https://gitee.com/mindspore/models/tree/master/official/lite";
public static final String ME_STAR_URL = "https://gitee.com/mindspore/mindspore";
}
diff --git a/official/nlp/bert/README.md b/official/nlp/bert/README.md
index e1e3b569790ee8678f78f6dc0a7988051941654d..250d42af70e8792fc433941a4f58dde9062a5c20 100644
--- a/official/nlp/bert/README.md
+++ b/official/nlp/bert/README.md
@@ -195,7 +195,7 @@ For distributed training on single machine, [here](https://gitee.com/mindspore/m
For distributed training among multiple machines, training command should be executed on each machine in a small time interval. Thus, an hccl.json is needed on each machine. [here](https://gitee.com/mindspore/mindspore/tree/master/config/hccl_multi_machine_multi_rank.json) is an example of hccl.json for multi-machine case.
Please follow the instructions in the link below to create an hccl.json file in need:
-[https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+[https://gitee.com/mindspore/models/tree/master/utils/hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
For dataset, if you want to set the format and parameters, a schema configuration file with JSON format needs to be created, please refer to [tfrecord](https://www.mindspore.cn/docs/programming_guide/en/master/dataset_loading.html#tfrecord) format.
@@ -765,7 +765,7 @@ python run_eval_onnx.py --config_path [../../task_classifier_config.yaml] --eval
| Total time | 63H | 610H |
| Params (M) | 110M | 110M |
| Checkpoint for Fine tuning | 1.2G(.ckpt file) | 1.2G(.ckpt file) |
-| Scripts | [BERT_base](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/bert) | [BERT_base](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/bert) |
+| Scripts | [BERT_base](https://gitee.com/mindspore/models/tree/master/official/nlp/bert) | [BERT_base](https://gitee.com/mindspore/models/tree/master/official/nlp/bert) |
| Parameters | Ascend |
| -------------------------- | ---------------------------------------------------------- |
@@ -785,7 +785,7 @@ python run_eval_onnx.py --config_path [../../task_classifier_config.yaml] --eval
| Total time | 180h |
| Params (M) | 340M |
| Checkpoint for Fine tuning | 3.2G(.ckpt file) |
-| Scripts | [BERT_NEZHA](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/bert) |
+| Scripts | [BERT_NEZHA](https://gitee.com/mindspore/models/tree/master/official/nlp/bert) |
#### Inference Performance
@@ -814,11 +814,11 @@ In run_pretrain.py, we set a random seed to make sure that each node has the sam
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
# FAQ
-Refer to the [ModelZoo FAQ](https://gitee.com/mindspore/mindspore/tree/master/model_zoo#FAQ) for some common question.
+Refer to the [ModelZoo FAQ](https://gitee.com/mindspore/models#FAQ) for some common question.
- **Q: How to resolve the continually overflow?**
diff --git a/official/nlp/bert/README_CN.md b/official/nlp/bert/README_CN.md
index 3fa9530bdb05e0a51d6a21e4a5ca3e083a3d7a62..330306dfe183936d097644f0ca62d27d1e9cada4 100644
--- a/official/nlp/bert/README_CN.md
+++ b/official/nlp/bert/README_CN.md
@@ -773,11 +773,11 @@ run_pretrain.py涓缃簡闅忔満绉嶅瓙锛岀‘淇濆垎甯冨紡璁粌涓瘡涓妭鐐�
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
# FAQ
-浼樺厛鍙傝€僛ModelZoo FAQ](https://gitee.com/mindspore/mindspore/tree/master/model_zoo#FAQ)鏉ユ煡鎵句竴浜涘父瑙佺殑鍏叡闂銆�
+浼樺厛鍙傝€僛ModelZoo FAQ](https://gitee.com/mindspore/models#FAQ)鏉ユ煡鎵句竴浜涘父瑙佺殑鍏叡闂銆�
- **Q: 杩愯杩囩▼涓彂鐢熸寔缁孩鍑烘€庝箞鍔烇紵**
diff --git a/official/nlp/bert/scripts/ascend_distributed_launcher/README.md b/official/nlp/bert/scripts/ascend_distributed_launcher/README.md
index ae76f74d0508f53694233e043ddb45f233bd16a6..5db42226ddaa808723d51e5e11b7bda9e6770832 100644
--- a/official/nlp/bert/scripts/ascend_distributed_launcher/README.md
+++ b/official/nlp/bert/scripts/ascend_distributed_launcher/README.md
@@ -41,7 +41,7 @@ log file dir: ./LOG6/log.txt
## Note
-1. Note that `hccl_2p_56_x.x.x.x.json` can use [hccl_tools.py](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools) to generate.
+1. Note that `hccl_2p_56_x.x.x.x.json` can use [hccl_tools.py](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools) to generate.
2. For hyper parameter, please note that you should customize the scripts `hyper_parameter_config.ini`. Please note that these two hyper parameters are not allowed to be configured here:
- device_id
diff --git a/official/nlp/bert_thor/README.md b/official/nlp/bert_thor/README.md
index 2cb03a011e9cc9073a059b450f5e51a4717e7256..b8fc4188160f65974def4d01bcf4dc91265984cb 100644
--- a/official/nlp/bert_thor/README.md
+++ b/official/nlp/bert_thor/README.md
@@ -74,7 +74,7 @@ bash scripts/run_distribute_pretrain.sh [DEVICE_NUM] [EPOCH_SIZE] [DATA_DIR] [SC
python pretrain_eval.py
```
-> For distributed training, a hccl configuration file with JSON format needs to be created in advance. About the configuration file, you can refer to the [HCCL_TOOL](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+> For distributed training, a hccl configuration file with JSON format needs to be created in advance. About the configuration file, you can refer to the [HCCL_TOOL](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
## Script Description
@@ -220,7 +220,7 @@ step: 3000 Accuracy: [0.71377236]
| Total time | 11 mins |
| Parameters (M) | 330 |
| Checkpoint for Fine tuning | 4.5G(.ckpt file) |
-| Scripts | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/bert_thor |
+| Scripts | https://gitee.com/mindspore/models/tree/master/official/nlp/bert_thor |
## Description of Random Situation
@@ -228,4 +228,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
## ModelZoo Homepage
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/nlp/bert_thor/README_CN.md b/official/nlp/bert_thor/README_CN.md
index 27fa5fdd5a381b942e0881eb38dded3bdeef0040..c65828b4f515287a51819af37a4f889196f789ea 100644
--- a/official/nlp/bert_thor/README_CN.md
+++ b/official/nlp/bert_thor/README_CN.md
@@ -77,7 +77,7 @@ bash scripts/run_distribute_pretrain.sh [DEVICE_NUM] [EPOCH_SIZE] [DATA_DIR] [SC
python pretrain_eval.py
```
-> 鍒嗗竷寮忚缁冿紝璇锋彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆傚叧浜庨厤缃枃浠讹紝鍙互鍙傝€僛HCCL_TOOL](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)銆�
+> 鍒嗗竷寮忚缁冿紝璇锋彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆傚叧浜庨厤缃枃浠讹紝鍙互鍙傝€僛HCCL_TOOL](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)銆�
## 鑴氭湰璇存槑
@@ -224,7 +224,7 @@ step: 3000 Accuracy: [0.71377236]
| 鎬绘椂闀� | 11鍒嗛挓 |
| 鍙傛暟锛圡锛� | 330 |
| 寰皟妫€鏌ョ偣 | 4.5G 锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/bert_thor |
+| 鑴氭湰 | https://gitee.com/mindspore/models/tree/master/official/nlp/bert_thor |
## 闅忔満鎯呭喌璇存槑
@@ -232,4 +232,4 @@ dataset.py璁剧疆浜哻reate_dataset鍑芥暟鍐呯殑绉嶅瓙銆傛垜浠繕鍦╰rain.py涓娇
## ModelZoo棣栭〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/nlp/cpm/README.md b/official/nlp/cpm/README.md
index 437f103ec390f8d4795ea6ea498e58764ed19086..a309cd6a62f9f097f950d5738a1b41276830005a 100644
--- a/official/nlp/cpm/README.md
+++ b/official/nlp/cpm/README.md
@@ -398,7 +398,7 @@ The finetune performance and accuracy of single machine and 8 cards are as follo
| Loss | 0.7 |
| Params (M) | 2597.1 |
| Checkpoint for inference | 76G 锛�.ckpt file锛� |
-| Scripts | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/cpm> |
+| Scripts | <https://gitee.com/mindspore/models/tree/master/official/nlp/cpm> |
The finetune performance and accuracy of 4 machines and 32 cards are as follows:
@@ -416,7 +416,7 @@ The finetune performance and accuracy of 4 machines and 32 cards are as follows:
| Loss | 0.03 |
| Params (M) | 2597.1 |
| Checkpoint for inference | 57G 锛�.ckpt file锛� |
-| Scripts | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/cpm> |
+| Scripts | <https://gitee.com/mindspore/models/tree/master/official/nlp/cpm> |
# Description of Random Situation
@@ -433,4 +433,4 @@ The accuracy and performance of this model have been verified in Ascend environm
# ModelZoo Homepage
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/nlp/cpm/README_CN.md b/official/nlp/cpm/README_CN.md
index 00b7af1cb6a8a5cad0411fcff6133afcf9f4753b..bfa87f8adf50a3869d9c39e07449e7cc241f7492 100644
--- a/official/nlp/cpm/README_CN.md
+++ b/official/nlp/cpm/README_CN.md
@@ -400,7 +400,7 @@ Zero-shot鍗曟満鍙屽崱鎺ㄧ悊鎬ц兘鍜岀簿搴﹀涓嬶細
| 鎹熷け | 0.7 |
| 鍙傛暟 (M) | 2597.1 |
| 鎺ㄧ悊妫€鏌ョ偣 | 76G 锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/cpm> |
+| 鑴氭湰 | <https://gitee.com/mindspore/models/tree/master/official/nlp/cpm> |
鍥涙満32鍗inetune鎬ц兘鍜岀簿搴﹀涓嬶細
@@ -418,7 +418,7 @@ Zero-shot鍗曟満鍙屽崱鎺ㄧ悊鎬ц兘鍜岀簿搴﹀涓嬶細
| 鎹熷け | 0.03 |
| 鍙傛暟 (M) | 2597.1 |
| 鎺ㄧ悊妫€鏌ョ偣 | 57G 锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/cpm> |
+| 鑴氭湰 | <https://gitee.com/mindspore/models/tree/master/official/nlp/cpm> |
# 闅忔満鎯呭喌璇存槑
@@ -435,4 +435,4 @@ train.py宸茬粡璁剧疆浜嗕竴浜涚瀛愶紝閬垮厤鏁版嵁闆嗚疆鎹㈠拰鏉冮噸鍒濆鍖栫殑
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/nlp/dgu/README_CN.md b/official/nlp/dgu/README_CN.md
index 48f6bb37f62ce9f3fde403d0f8d7c5ccb92b527c..25fbcdaded8f95c5f163de8fc52688d06dbcbbff 100644
--- a/official/nlp/dgu/README_CN.md
+++ b/official/nlp/dgu/README_CN.md
@@ -443,4 +443,4 @@ config.py涓紝榛樿灏唄idden_dropout_prob鍜宯ote_pros_dropout_prob璁剧疆涓�0.1
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/nlp/emotect/README_CN.md b/official/nlp/emotect/README_CN.md
index 08cb38a238b8e7f088a218d452f9925c4100ecfa..a8f694870522a7a2b7a168c64d00d5ea93d6cbad 100644
--- a/official/nlp/emotect/README_CN.md
+++ b/official/nlp/emotect/README_CN.md
@@ -224,4 +224,4 @@ bash scripts/run_infer_310.sh [MINDIR_PATH] [DATA_FILE_PATH] [NEED_PREPROCESS] [
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/nlp/ernie/README_CN.md b/official/nlp/ernie/README_CN.md
index 3b2c24336f55565125c1fa93ecdcea3118b1d179..a21a440fb357348feb62aa9b85082f79543e64b2 100644
--- a/official/nlp/ernie/README_CN.md
+++ b/official/nlp/ernie/README_CN.md
@@ -450,10 +450,10 @@ CMRC2018
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
# FAQ
-浼樺厛鍙傝€僛ModelZoo FAQ](https://gitee.com/mindspore/mindspore/tree/master/model_zoo#FAQ)鏉ユ煡鎵句竴浜涘父瑙佺殑鍏叡闂銆�
+浼樺厛鍙傝€僛ModelZoo FAQ](https://gitee.com/mindspore/models#FAQ)鏉ユ煡鎵句竴浜涘父瑙佺殑鍏叡闂銆�
- **Q: 褰撲娇鐢� `PYNATICE_MODE` 杩愯鏃跺嚭鐜板唴瀛樻孩鍑烘€庝箞鍔烇紵** **A**: 鍦� `PYNATIVE_MODE` 涓嬶紝鍐呭瓨鍗犵敤浼氭洿澶氾紝鍙互灏濊瘯鍑忓皬 batch size 鏉ョ紦瑙ｏ紝渚嬪锛屽浜� XNLI銆丏BQA 鏁版嵁闆嗭紝鍙皢 batchsize 鍑忓皬鍒� 16銆�
diff --git a/official/nlp/fasttext/README.md b/official/nlp/fasttext/README.md
index 479f762dc294eb4cf35ed21ce7799a4df4b1eccd..b1a06a9cfd423f3d7f246f0e7e0ce0571d57c00c 100644
--- a/official/nlp/fasttext/README.md
+++ b/official/nlp/fasttext/README.md
@@ -290,7 +290,7 @@ Parameters for both training and evaluation can be set in config.py. All the dat
| Loss | 0.0067 | 0.0085 |
| Params (M) | 22 | 22 |
| Checkpoint for inference | 254M (.ckpt file) | 254M (.ckpt file) |
-| Scripts | [fasttext](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/fasttext) | [fasttext](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/fasttext) |
+| Scripts | [fasttext](https://gitee.com/mindspore/models/tree/master/official/nlp/fasttext) | [fasttext](https://gitee.com/mindspore/models/tree/master/official/nlp/fasttext) |
| Parameters | Ascend | GPU |
| ------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
@@ -307,7 +307,7 @@ Parameters for both training and evaluation can be set in config.py. All the dat
| Loss | 2.6e-4 | 0.0004 |
| Params (M) | 106 | 106 |
| Checkpoint for inference | 1.2G (.ckpt file) | 1.2G (.ckpt file) |
-| Scripts | [fasttext](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/fasttext) | [fasttext](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/fasttext) |
+| Scripts | [fasttext](https://gitee.com/mindspore/models/tree/master/official/nlp/fasttext) | [fasttext](https://gitee.com/mindspore/models/tree/master/official/nlp/fasttext) |
| Parameters | Ascend | GPU |
| ------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
@@ -324,7 +324,7 @@ Parameters for both training and evaluation can be set in config.py. All the dat
| Loss | 0.062 | 0.002 |
| Params (M) | 103 | 103 |
| Checkpoint for inference | 1.2G (.ckpt file) | 1.2G (.ckpt file) |
-| Scripts | [fasttext](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/fasttext) | [fasttext](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/fasttext) |
+| Scripts | [fasttext](https://gitee.com/mindspore/models/tree/master/official/nlp/fasttext) | [fasttext](https://gitee.com/mindspore/models/tree/master/official/nlp/fasttext) |
#### Inference Performance
@@ -378,4 +378,4 @@ This model has been validated in the Ascend environment and is not validated on
## [ModelZoo HomePage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)
+Please check the official [homepage](https://gitee.com/mindspore/models)
diff --git a/official/nlp/gnmt_v2/README.md b/official/nlp/gnmt_v2/README.md
index d273ff3d2374efc9e36e7248f4ea1d1d5e4214cb..67d072c217750fa2269a8fc49bddea0786fc9e2d 100644
--- a/official/nlp/gnmt_v2/README.md
+++ b/official/nlp/gnmt_v2/README.md
@@ -396,7 +396,7 @@ For more configuration details, please refer the script `./default_config.yaml`
| Loss | 63.35 | 55.42 |
| Params (M) | 613 | 613 |
| Checkpoint for inference | 1.8G (.ckpt file) | 1.8G (.ckpt file) |
-| Scripts | [gnmt_v2](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/gnmt_v2) | [gnmt_v2](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/gnmt_v2) |
+| Scripts | [gnmt_v2](https://gitee.com/mindspore/models/tree/master/official/nlp/gnmt_v2) | [gnmt_v2](https://gitee.com/mindspore/models/tree/master/official/nlp/gnmt_v2) |
### Inference Performance
@@ -428,4 +428,4 @@ This model has been validated in the Ascend environment and is not validated on
# [ModelZoo HomePage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)
+ Please check the official [homepage](https://gitee.com/mindspore/models)
diff --git a/official/nlp/gpt/README.md b/official/nlp/gpt/README.md
index 4e6686c94ddfc057aacc860b1eb8bcfcba191d10..53f735cf4cc7761503e208c3cd09b145a5d56359 100644
--- a/official/nlp/gpt/README.md
+++ b/official/nlp/gpt/README.md
@@ -59,7 +59,7 @@ bash scripts/run_evaluation.sh lambada /your/ckpt /your/data acc
For distributed training, an hccl configuration file with JSON format needs to be created in advance.
Please follow the instructions in the link below:
-https:gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.
+https:gitee.com/mindspore/models/tree/master/utils/hccl_tools.
# [Script Description](#contents)
@@ -85,4 +85,4 @@ https:gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/nlp/gru/README.md b/official/nlp/gru/README.md
index 421ace5a5157a02396243596edebb4898efb99d7..616b09bd67a4ce794dd57249d4863c3d7b3eed22 100644
--- a/official/nlp/gru/README.md
+++ b/official/nlp/gru/README.md
@@ -399,7 +399,7 @@ perl multi-bleu.perl target.txt.forbleu < output.txt.forbleu
| Loss | 3.86888 |2.533958 |
| Params (M) | 21 | 21 |
| Checkpoint for inference | 272M (.ckpt file) | 272M (.ckpt file) |
-| Scripts | [gru](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/gru) |[gru](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/gru) |
+| Scripts | [gru](https://gitee.com/mindspore/models/tree/master/official/nlp/gru) |[gru](https://gitee.com/mindspore/models/tree/master/official/nlp/gru) |
### Inference Performance
@@ -428,4 +428,4 @@ This model has been validated in the Ascend environment and is not validated on
# [ModelZoo HomePage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)
+ Please check the official [homepage](https://gitee.com/mindspore/models)
diff --git a/official/nlp/lstm/README.md b/official/nlp/lstm/README.md
index 3454f28b9bcc4f924aa00b7afe85d08d77ce917c..094a2f424a00d4b1c3b15b2b606a73ec5d3e73c6 100644
--- a/official/nlp/lstm/README.md
+++ b/official/nlp/lstm/README.md
@@ -443,7 +443,7 @@ Inference result is saved in current path, you can find result in acc.log file.
| Loss | 0.12 | 0.12 | 0.12 |
| Params (M) | 6.45 | 6.45 | 6.45 |
| Checkpoint for inference | 292.9M (.ckpt file) | 292.9M (.ckpt file) | 292.9M (.ckpt file) |
-| Scripts | [lstm script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/lstm) | [lstm script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/lstm) | [lstm script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/lstm) |
+| Scripts | [lstm script](https://gitee.com/mindspore/models/tree/master/official/nlp/lstm) | [lstm script](https://gitee.com/mindspore/models/tree/master/official/nlp/lstm) | [lstm script](https://gitee.com/mindspore/models/tree/master/official/nlp/lstm) |
### Evaluation Performance
@@ -465,4 +465,4 @@ There are three random situations:
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/nlp/lstm/README_CN.md b/official/nlp/lstm/README_CN.md
index 9da950bbf84c74ee2c3a084b6a731fcad13d7b01..108d0657ca12f3626f81c88c67af900aab5d630e 100644
--- a/official/nlp/lstm/README_CN.md
+++ b/official/nlp/lstm/README_CN.md
@@ -443,7 +443,7 @@ bash run_infer_310.sh [MINDIR_PATH] [DATASET_PATH] [NEED_PREPROCESS] [DEVICE_TAR
| 鎹熷け | 0.12 | 0.12 | 0.12 |
| 鍙傛暟锛圡锛� | 6.45 | 6.45 | 6.45 |
| 鎺ㄧ悊妫€鏌ョ偣 | 292.9M锛�.ckpt鏂囦欢锛� | 292.9M锛�.ckpt鏂囦欢锛� | 292.9M锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | [LSTM鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/lstm) | [LSTM鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/lstm) | [LSTM鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/lstm) |
+| 鑴氭湰 | [LSTM鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/nlp/lstm) | [LSTM鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/nlp/lstm) | [LSTM鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/nlp/lstm) |
### 璇勪及鎬ц兘
@@ -465,4 +465,4 @@ bash run_infer_310.sh [MINDIR_PATH] [DATASET_PATH] [NEED_PREPROCESS] [DEVICE_TAR
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/nlp/mass/README.md b/official/nlp/mass/README.md
index 173a20e7c0ea427c800702d61f4c8c44349d271a..6021233967526be9ec7d708626139ab044bdc562 100644
--- a/official/nlp/mass/README.md
+++ b/official/nlp/mass/README.md
@@ -733,4 +733,4 @@ The model has been validated on Ascend and GPU environments, not validated on CP
# ModelZoo Homepage
- [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)
+ [Link](https://gitee.com/mindspore/models)
diff --git a/official/nlp/mass/README_CN.md b/official/nlp/mass/README_CN.md
index 4641bdbe64d04322900b181cd31ccdb8a175448f..05b0dc577f6e66c8ae821c62babab957b3940993 100644
--- a/official/nlp/mass/README_CN.md
+++ b/official/nlp/mass/README_CN.md
@@ -734,4 +734,4 @@ MASS妯″瀷娑夊強闅忔満澶辨椿锛坉ropout锛夋搷浣滐紝濡傞渶绂佺敤姝ゅ姛鑳斤紝璇峰湪
# ModelZoo涓婚〉
- [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)
+ [閾炬帴](https://gitee.com/mindspore/models)
diff --git a/official/nlp/pangu_alpha/README.md b/official/nlp/pangu_alpha/README.md
index b5018d2700e52c74c3f29250974306c178731c1e..114d207b6d8a8a9406a6a5f6eaac13e4cf79890b 100644
--- a/official/nlp/pangu_alpha/README.md
+++ b/official/nlp/pangu_alpha/README.md
@@ -172,7 +172,7 @@ bash scripts/run_distribute_train.sh /path/dataset /path/hccl.json 16 fp32 2.6B
For distributed training, an hccl configuration file with JSON format needs to be created in advance.
Please follow the instructions in the link below:
-https:gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.
+https:gitee.com/mindspore/models/tree/master/utils/hccl_tools.
### Training on GPU
@@ -334,7 +334,7 @@ ${FILE_PATH}/tokenizer/ ${FILE_PATH}/checkpoint_file filitered 2.6B $DEVICE_TAR
### Serving 13B or 2.6B in Distributed mode [Ascend910 8 cards]
-- Generate [rank table file](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+- Generate [rank table file](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
```shell
# mindspore/model_zoo/utils/hccl_tools/hccl_tools.py
@@ -417,7 +417,7 @@ ${FILE_PATH}/tokenizer/ ${FILE_PATH}/checkpoint_file filitered 2.6B $DEVICE_TAR
### Serving in Distributed mode [Ascend910 8 cards * N machine]
-- Generate [rank table file](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+- Generate [rank table file](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
- In every machine, prepare for checkpoint files and embedding files. We can also use 13B as a test example.
- In every machine, use scripts/run_cluster_export.sh to export MindIR models, and move all device* to
'serving_increment/pangu_distributed/models/'.
@@ -487,7 +487,7 @@ successfully.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
# [Requirements](#contents)
diff --git a/official/nlp/q8bert/README.md b/official/nlp/q8bert/README.md
index d3415c81ee00cf2f2d50ab6d7e340787f350a58e..340820d465d096c1ebbbb23fe6cfcae825936ff8 100644
--- a/official/nlp/q8bert/README.md
+++ b/official/nlp/q8bert/README.md
@@ -217,4 +217,4 @@ In config.py, we set the hidden_dropout_prob, attention_pros_dropout_prob and cl
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/nlp/q8bert/README_CN.md b/official/nlp/q8bert/README_CN.md
index db5ac287a8aaa3e441f9f7ce875814de487bbfd3..3ad02c9c4797a66f27af4a4ab9a6fedd5d0ab508 100644
--- a/official/nlp/q8bert/README_CN.md
+++ b/official/nlp/q8bert/README_CN.md
@@ -214,4 +214,4 @@ config.py鏂囦欢涓缃甴idden_dropout_prob鍜宎ttention_pros_dropout_prob鍙傛暟
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/nlp/textcnn/README.md b/official/nlp/textcnn/README.md
index f825bba649768dc2dd020991f384141040d54c38..cdfa411c91ee85871f9bcfbf8bab619eafc66f6d 100644
--- a/official/nlp/textcnn/README.md
+++ b/official/nlp/textcnn/README.md
@@ -344,4 +344,4 @@ Inference result is saved in current path, you can find result in acc.log file.
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/nlp/tinybert/README.md b/official/nlp/tinybert/README.md
index 9de774dd4c6a4b208260f9ad95657f543691e771..27d4376d69b18f55aa084308ea4f332f8d88bf69 100644
--- a/official/nlp/tinybert/README.md
+++ b/official/nlp/tinybert/README.md
@@ -98,7 +98,7 @@ The backbone structure of TinyBERT is transformer, the transformer contains four
For distributed training on Ascend, a hccl configuration file with JSON format needs to be created in advance.
Please follow the instructions in the link below:
- https:gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.
+ https:gitee.com/mindspore/models/tree/master/utils/hccl_tools.
For dataset, if you want to set the format and parameters, a schema configuration file with JSON format needs to be created, please refer to [tfrecord](https://www.mindspore.cn/docs/programming_guide/en/master/dataset_loading.html#tfrecord) format.
@@ -569,7 +569,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Total time | 17.3h(3poch, 8p) | 48h(3poch, 8p) |
| Params (M) | 15M | 15M |
| Checkpoint for task distill| 74M(.ckpt file) | 74M(.ckpt file) |
-| Scripts | [TinyBERT](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/tinybert) | |
+| Scripts | [TinyBERT](https://gitee.com/mindspore/models/tree/master/official/nlp/tinybert) | |
#### Inference Performance
@@ -596,4 +596,4 @@ In run_general_distill.py, we set the random seed to make sure distribute traini
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/nlp/tinybert/README_CN.md b/official/nlp/tinybert/README_CN.md
index dcc7fd579f9e227eff36d513d48ec94929d618aa..9dc08674e4c9b6242bcfa4564e76d73b898222ae 100644
--- a/official/nlp/tinybert/README_CN.md
+++ b/official/nlp/tinybert/README_CN.md
@@ -103,7 +103,7 @@ TinyBERT妯″瀷鐨勪富骞茬粨鏋勬槸杞崲鍣紝杞崲鍣ㄥ寘鍚洓涓紪鐮佸櫒妯″潡
鑻ュ湪Ascend璁惧涓婅繍琛屽垎甯冨紡璁粌锛岃鎻愬墠鍒涘缓JSON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆�
璇︽儏鍙傝濡備笅閾炬帴锛�
- https:gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.
+ https:gitee.com/mindspore/models/tree/master/utils/hccl_tools.
濡傞渶璁剧疆鏁版嵁闆嗘牸寮忓拰鍙傛暟锛岃鍒涘缓JSON鏍煎紡鐨勮鍥鹃厤缃枃浠讹紝璇﹁[TFRecord](https://www.mindspore.cn/docs/programming_guide/zh-CN/master/dataset_loading.html#tfrecord) 鏍煎紡銆�
@@ -594,4 +594,4 @@ run_general_distill.py鏂囦欢涓缃簡闅忔満绉嶅瓙锛岀‘淇濆垎甯冨紡璁粌鍒�
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/nlp/transformer/README.md b/official/nlp/transformer/README.md
index 5ecc158deff63e686e3ee1067ca114280a757f6c..683583d79e60b66119a53ad0738849ddfcfb809c 100644
--- a/official/nlp/transformer/README.md
+++ b/official/nlp/transformer/README.md
@@ -400,7 +400,7 @@ Inference result is saved in current path, 'output_file' will generate in path s
| Loss | 2.8 |
| Params (M) | 213.7 |
| Checkpoint for inference | 2.4G (.ckpt file) |
-| Scripts | [Transformer scripts](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/transformer) |
+| Scripts | [Transformer scripts](https://gitee.com/mindspore/models/tree/master/official/nlp/transformer) |
#### Evaluation Performance
@@ -426,4 +426,4 @@ Some seeds have already been set in train.py to avoid the randomness of dataset
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/nlp/transformer/README_CN.md b/official/nlp/transformer/README_CN.md
index 0f9c4e0b57aada74f390504753a670c6c03296b5..0596a3d11aa8b4a89097c80580c8c6aaf46cc69f 100644
--- a/official/nlp/transformer/README_CN.md
+++ b/official/nlp/transformer/README_CN.md
@@ -403,7 +403,7 @@ bash run_infer_310.sh [MINDIR_PATH] [NEED_PREPROCESS] [DEVICE_ID]
| 鎹熷け | 2.8 |
| 鍙傛暟 (M) | 213.7 |
| 鎺ㄧ悊妫€鏌ョ偣 | 2.4G 锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/nlp/transformer> |
+| 鑴氭湰 | <https://gitee.com/mindspore/models/tree/master/official/nlp/transformer> |
#### 璇勪及鎬ц兘
@@ -429,4 +429,4 @@ train.py宸茬粡璁剧疆浜嗕竴浜涚瀛愶紝閬垮厤鏁版嵁闆嗚疆鎹㈠拰鏉冮噸鍒濆鍖栫殑
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/recommend/deep_and_cross/README_CN.md b/official/recommend/deep_and_cross/README_CN.md
index 24839bba27841be5fbe060478190fec6392f781f..d4e3742bb025e4159667ba134ed11360e126de06 100644
--- a/official/recommend/deep_and_cross/README_CN.md
+++ b/official/recommend/deep_and_cross/README_CN.md
@@ -217,4 +217,4 @@ sh scripts/run_eval.sh CHECKPOINT_PATH
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/recommend/deepfm/README.md b/official/recommend/deepfm/README.md
index 62baa296b423d2ba98c72c951bfad38c228fd918..0481f4be11c2ab32d37ac453de0e49c5f64e7ab1 100644
--- a/official/recommend/deepfm/README.md
+++ b/official/recommend/deepfm/README.md
@@ -95,7 +95,7 @@ After installing MindSpore via the official website, you can start training and
Please follow the instructions in the link below:
- [hccl tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+ [hccl tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
- running on GPU
@@ -430,7 +430,7 @@ auc : 0.8057789065281104
| Total time | 1pc: 90 mins; | To do |
| Parameters (M) | 16.5 | To do |
| Checkpoint for Fine tuning | 190M (.ckpt file) | To do |
-| Scripts | [deepfm script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/recommend/deepfm) | To do |
+| Scripts | [deepfm script](https://gitee.com/mindspore/models/tree/master/official/recommend/deepfm) | To do |
### Inference Performance
@@ -452,4 +452,4 @@ We set the random seed before training in train.py.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/recommend/deepfm/README_CN.md b/official/recommend/deepfm/README_CN.md
index 11e931002dd610359f85286cd5e42998e56d1916..59b02afad32470f86f49e4b92356b6876e8a2048 100644
--- a/official/recommend/deepfm/README_CN.md
+++ b/official/recommend/deepfm/README_CN.md
@@ -98,7 +98,7 @@ FM鍜屾繁搴﹀涔犻儴鍒嗘嫢鏈夌浉鍚岀殑杈撳叆鍘熸牱鐗瑰緛鍚戦噺锛岃DeepFM鑳戒粠
鍏蜂綋鎿嶄綔锛屽弬瑙侊細
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>.
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>.
- 鍦℅PU涓婅繍琛�
@@ -411,7 +411,7 @@ auc : 0.8057789065281104
| 鎬绘椂闀縷 鍗曞崱锛�90 鍒嗛挓; | 寰呰繍琛� |
| 鍙傛暟(M) | 16.5 | 寰呰繍琛� |
| 寰皟妫€鏌ョ偣 | 190M (.ckpt 鏂囦欢) | 寰呰繍琛� |
-| 鑴氭湰 | [DeepFM鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/recommend/deepfm) | 寰呰繍琛� |
+| 鑴氭湰 | [DeepFM鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/recommend/deepfm) | 寰呰繍琛� |
### 鎺ㄧ悊鎬ц兘
@@ -433,4 +433,4 @@ auc : 0.8057789065281104
## ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/recommend/naml/README.md b/official/recommend/naml/README.md
index 35a3734bb8f9057cf2f60a4690b81b5861754f2f..66ded24d3f9063d189563ec3c4d11eda16f7585b 100644
--- a/official/recommend/naml/README.md
+++ b/official/recommend/naml/README.md
@@ -107,7 +107,7 @@ You can start training using python or shell scripts. The usage of shell scripts
Please follow the instructions in the link below:
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>.
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>.
- ModelArts (If you want to run in modelarts, please check the official documentation of [modelarts](https://support.huaweicloud.com/modelarts/), and you can start training as follows)
@@ -253,4 +253,4 @@ In train.py, we set the seed which is used by numpy.random, mindspore.common.Ini
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/recommend/ncf/README.md b/official/recommend/ncf/README.md
index 52f53c1271caf31154518478e7d29d4ec22a6221..b5133a610c1684990508103c3f35eb72ad1f6cd7 100644
--- a/official/recommend/ncf/README.md
+++ b/official/recommend/ncf/README.md
@@ -397,4 +397,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/recommend/tbnet/README.md b/official/recommend/tbnet/README.md
index f15c8598bc8b5b7621d20c2b9e171a298bce931c..09f6e6a688bd1bdc2de37c06d3b860eb531db152 100644
--- a/official/recommend/tbnet/README.md
+++ b/official/recommend/tbnet/README.md
@@ -214,7 +214,7 @@ python infer.py \
| Speed | 1pc: 90ms/step |
| Total Time | 1pc: 297s |
| Checkpoint for Fine Tuning | 104.66M (.ckpt file) |
-| Scripts | [TB-Net scripts](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/recommend/tbnet) |
+| Scripts | [TB-Net scripts](https://gitee.com/mindspore/models/tree/master/official/recommend/tbnet) |
### Evaluation Performance
@@ -247,4 +247,4 @@ python infer.py \
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
\ No newline at end of file
+Please check the official [homepage](https://gitee.com/mindspore/models).
\ No newline at end of file
diff --git a/official/recommend/tbnet/README_CN.md b/official/recommend/tbnet/README_CN.md
index 534c2a5fc7f52a8b7e34184c3cab84e0a37bacf7..621b80787c633be920a68aa3bbdb22902bee4864 100644
--- a/official/recommend/tbnet/README_CN.md
+++ b/official/recommend/tbnet/README_CN.md
@@ -216,7 +216,7 @@ python infer.py \
| 閫熷害 | 鍗曞崱锛�90姣/姝� |
| 鎬绘椂闀� | 鍗曞崱锛�297绉� |
| 寰皟妫€鏌ョ偣 | 104.66M (.ckpt 鏂囦欢) |
-| 鑴氭湰 | [TB-Net鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/recommend/tbnet) |
+| 鑴氭湰 | [TB-Net鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/recommend/tbnet) |
### [璇勪及鎬ц兘](#鐩綍)
@@ -249,4 +249,4 @@ python infer.py \
# [ModelZoo涓婚〉](#鐩綍)
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
\ No newline at end of file
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
\ No newline at end of file
diff --git a/official/recommend/wide_and_deep/README.md b/official/recommend/wide_and_deep/README.md
index f29fa236be55ab13c26bd038c51f23d16e47bf18..0130bf16ae1ec1610ca978a2d237cb88e44bb79e 100644
--- a/official/recommend/wide_and_deep/README.md
+++ b/official/recommend/wide_and_deep/README.md
@@ -458,7 +458,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Params(M) | 75.84 | 75.84 | 75.84 | 75.84 |
| Checkpoint for inference | 233MB(.ckpt file) | 230MB(.ckpt) | 233MB(.ckpt file) | 233MB(.ckpt file) |
-All executable scripts can be found in [here](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/recommend/wide_and_deep/script)
+All executable scripts can be found in [here](https://gitee.com/mindspore/models/tree/master/official/recommend/wide_and_deep/script)
Note: The result of GPU is tested under the master version. The parameter server mode of the Wide&Deep model is still under development.
@@ -500,4 +500,4 @@ There are three random situations:
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/recommend/wide_and_deep/README_CN.md b/official/recommend/wide_and_deep/README_CN.md
index 6f617ac8e4b30af85adfa444b5a0e0c15964d76b..cbb3e61eae9e95e3b28d49e2d6e968f572575bad 100644
--- a/official/recommend/wide_and_deep/README_CN.md
+++ b/official/recommend/wide_and_deep/README_CN.md
@@ -470,7 +470,7 @@ bash run_infer_310.sh [MINDIR_PATH] [DATASET_PATH] [DATA_TYPE] [NEED_PREPROCESS]
| 鍙傛暟(M) | 75.84 | 75.84 | 75.84 | 75.84 |
| 鎺ㄧ悊妫€鏌ョ偣 | 233MB锛�.ckpt鏂囦欢锛� | 230MB锛�.ckpt鏂囦欢锛� | 233Mb锛�.ckpt鏂囦欢锛� | 233MB锛�.ckpt鏂囦欢锛� |
-鎵€鏈夊彲鎵ц鑴氭湰鍙傝[姝ゅ](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/recommend/wide_and_deep/script)銆�
+鎵€鏈夊彲鎵ц鑴氭湰鍙傝[姝ゅ](https://gitee.com/mindspore/models/tree/master/official/recommend/wide_and_deep/script)銆�
璇存槑锛欸PU鐨勭粨鏋滄槸鍦ㄤ富鐗堟湰涓嬫祴璇曠殑銆俉ide&Deep妯″瀷鐨勫弬鏁版湇鍔℃ā寮忓皻澶勪簬寮€鍙戜腑銆�
@@ -512,4 +512,4 @@ export DATASET_ENABLE_NUMA=True
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/recommend/wide_and_deep_multitable/README.md b/official/recommend/wide_and_deep_multitable/README.md
index 1363fea560b4e868848feeb1c4048acbaa9fc6ab..fc16d9bd235933ad1a6b8c89ccf9016c97328733 100644
--- a/official/recommend/wide_and_deep_multitable/README.md
+++ b/official/recommend/wide_and_deep_multitable/README.md
@@ -182,7 +182,7 @@ python eval.py
| Params(M) | 349 | 349 |
| Checkpoint for inference | 1.1GB(.ckpt file) | 1.1GB(.ckpt file) |
-All executable scripts can be found in [here](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/recommend/wide_and_deep_multitable/script)
+All executable scripts can be found in [here](https://gitee.com/mindspore/models/tree/master/official/recommend/wide_and_deep_multitable/script)
#### Evaluation Performance
@@ -206,4 +206,4 @@ There are three random situations:
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/recommend/wide_and_deep_multitable/README_CN.md b/official/recommend/wide_and_deep_multitable/README_CN.md
index 06eafa03a524194ac05ef09a46515c95137629c1..6644063af36c346f3f055a43f7bcfd73cf8f8277 100644
--- a/official/recommend/wide_and_deep_multitable/README_CN.md
+++ b/official/recommend/wide_and_deep_multitable/README_CN.md
@@ -183,7 +183,7 @@ python eval.py
| 鍙傛暟(M) | 349 | 349 |
| 鎺ㄧ悊妫€鏌ョ偣 | 1.1GB(.ckpt鏂囦欢) | 1.1GB(.ckpt鏂囦欢) |
-鎵€鏈夊彲鎵ц鑴氭湰鍙傝[杩欓噷](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/recommend/wide_and_deep/script)銆�
+鎵€鏈夊彲鎵ц鑴氭湰鍙傝[杩欓噷](https://gitee.com/mindspore/models/tree/master/official/recommend/wide_and_deep/script)銆�
#### 璇勪及鎬ц兘
@@ -207,4 +207,4 @@ python eval.py
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/official/rl/dqn/README.md b/official/rl/dqn/README.md
index bd8b165de3c8c0bf440164c0282fa679193f2446..1f1837fc6f959142cd5007bfb0be36aa4bd59bc6 100644
--- a/official/rl/dqn/README.md
+++ b/official/rl/dqn/README.md
@@ -118,7 +118,7 @@ pip install gym
| Loss Function | MSELoss |MSELoss |
| outputs | Reward | Reward |
| Params (M) | 7.3k | 7.3k |
-| Scripts | <<<https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/rl/dqn>>> | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/rl/dqn |
+| Scripts | <<<https://gitee.com/mindspore/models/tree/master/official/rl/dqn>>> | https://gitee.com/mindspore/models/tree/master/official/rl/dqn |
## [Description of Random Situation](#content)
@@ -126,4 +126,4 @@ We use random seed in train.py.
## [ModeZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/official/rl/dqn/README_CN.md b/official/rl/dqn/README_CN.md
index 8e014d50cd57e63724ba0adc9e3a3ebbdca49ee0..3ef0faf390c482e6bd2e312c90cae08a5684dd4c 100644
--- a/official/rl/dqn/README_CN.md
+++ b/official/rl/dqn/README_CN.md
@@ -115,7 +115,7 @@ pip install gym
| 鎹熷け鍑芥暟 | MSELoss | MSELoss |
| 杈撳嚭 | 娓告垙寰楀垎鍊� | 娓告垙寰楀垎鍊� |
| 鍙傛暟閲�(M) | 7.3k | 7.3k |
-| 鑴氭湰 | <<<<https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/rl/dqn>>>> | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/rl/dqn |
+| 鑴氭湰 | <<<<https://gitee.com/mindspore/models/tree/master/official/rl/dqn>>>> | https://gitee.com/mindspore/models/tree/master/official/rl/dqn |
# 闅忔満鎯呭喌鎻忚堪
diff --git a/research/audio/deepspeech2/README-CN.md b/research/audio/deepspeech2/README-CN.md
index af1443c2cd720fc18614a7aa7a730650ce83f801..17e446557babc349989e9b13c0b3c2e6bbbcc409 100644
--- a/research/audio/deepspeech2/README-CN.md
+++ b/research/audio/deepspeech2/README-CN.md
@@ -272,7 +272,7 @@ python export.py --pre_trained_model_path='ckpt_path'
| 杩愯閫熷害 | 2p 2.139s/step |
| 璁粌鎬绘椂闂� | 2p: around 1 week; |
| Checkpoint鏂囦欢澶у皬 | 991M (.ckpt file) |
-| 浠ｇ爜 | [DeepSpeech script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/audio/deepspeech2) |
+| 浠ｇ爜 | [DeepSpeech script](https://gitee.com/mindspore/models/tree/master/research/audio/deepspeech2) |
### Inference Performance
@@ -290,4 +290,4 @@ python export.py --pre_trained_model_path='ckpt_path'
# [ModelZoo涓婚〉](#contents)
- [ModelZoo涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ [ModelZoo涓婚〉](https://gitee.com/mindspore/models).
diff --git a/research/audio/deepspeech2/README.md b/research/audio/deepspeech2/README.md
index c20fac150dbdfcf96130a9263918cced59a780b7..a9172f4d9d200d6904c43e0c161bc519ea64544d 100644
--- a/research/audio/deepspeech2/README.md
+++ b/research/audio/deepspeech2/README.md
@@ -276,7 +276,7 @@ python export.py --pre_trained_model_path='ckpt_path'
| Speed | 2p 2.139s/step |
| Total time: training | 2p: around 1 week; |
| Checkpoint | 991M (.ckpt file) |
-| Scripts | [DeepSpeech script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/audio/deepspeech2) |
+| Scripts | [DeepSpeech script](https://gitee.com/mindspore/models/tree/master/research/audio/deepspeech2) |
### Inference Performance
@@ -294,4 +294,4 @@ python export.py --pre_trained_model_path='ckpt_path'
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/audio/fcn-4/README.md b/research/audio/fcn-4/README.md
index 68e563b19544fe978f938971e0f1209af155ffd6..d2e94f5001d2d1870e46e8aa201d68b939eea3d3 100644
--- a/research/audio/fcn-4/README.md
+++ b/research/audio/fcn-4/README.md
@@ -332,8 +332,8 @@ AUC: 0.90995
| Speed | 1pc: 160 samples/sec; | 1pc: 160 samples/sec; |
| Total time | 1pc: 20 mins; | 1pc: 20 mins; |
| Checkpoint for Fine tuning | 198.73M(.ckpt file) | 198.73M(.ckpt file) |
-| Scripts | [music_auto_tagging script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/audio/fcn-4) |
+| Scripts | [music_auto_tagging script](https://gitee.com/mindspore/models/tree/master/research/audio/fcn-4) |
## [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/audio/wavenet/README.md b/research/audio/wavenet/README.md
index ec487a731c0cffe51a032c26b9e0e247ec7d87e5..03bf98abd3edf8984a0f7e9f57e1c4b9ed7c508e 100644
--- a/research/audio/wavenet/README.md
+++ b/research/audio/wavenet/README.md
@@ -265,7 +265,7 @@ python export.py --preset=/path_to_egs/egs/gaussian/conf/gaussian_wavenet.json -
| Speed | 1p 1.467s/step |
| Total time: training | 1p(mol/gaussian): around 4 days; 2p(mulaw256):around 1 week |
| Checkpoint | 59.79MM/54.87M/54.83M (.ckpt file) |
-| Scripts | [WaveNet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/audio/wavenet) |
+| Scripts | [WaveNet script](https://gitee.com/mindspore/models/tree/master/research/audio/wavenet) |
### Inference Performance On GPU
@@ -273,4 +273,4 @@ Audio samples will be demonstrated online soon.
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/AttGAN/README_CN.md b/research/cv/AttGAN/README_CN.md
index 52d9df3924a4f3b366f8770fe2445e59836e2d35..f596e0801709ce0b5d8c51cc9f93c8c930286950 100644
--- a/research/cv/AttGAN/README_CN.md
+++ b/research/cv/AttGAN/README_CN.md
@@ -89,7 +89,7 @@ CelebFaces Attributes Dataset (CelebA) 鏄竴涓ぇ瑙勬ā鐨勪汉鑴稿睘鎬ф暟鎹�
璇烽伒寰互涓嬮摼鎺ヤ腑鐨勮鏄庯細
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.>
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools.>
瀵逛簬璇勪及鑴氭湰锛岄渶瑕佹彁鍓嶅垱寤哄瓨鏀捐嚜瀹氫箟鍥剧墖(jpg)鐨勭洰褰曚互鍙婂睘鎬х紪杈戞枃浠讹紝鍏充簬灞炴€х紪杈戞枃浠剁殑璇存槑瑙乕鑴氭湰鍙婃牱渚嬩唬鐮乚(#鑴氭湰鍙婃牱渚嬩唬鐮�)銆傜洰褰曚互鍙婂睘鎬х紪杈戞枃浠跺垎鍒搴斿弬鏁癭custom_data`鍜宍custom_attr`銆俢heckpoint鏂囦欢琚缁冭剼鏈粯璁ゆ斁缃湪
`/output/{experiment_name}/checkpoint`鐩綍涓嬶紝鎵ц鑴氭湰鏃堕渶瑕佸皢妫€鏌ョ偣鏂囦欢锛圙enerator锛夌殑鍚嶇О浣滀负鍙傛暟浼犲叆銆�
@@ -222,7 +222,7 @@ bash run_infer_310.sh [GEN_MINDIR_PATH] [ATTR_FILE_PATH] [DATA_PATH] [NEED_PREPR
| 浼樺寲鍣� | Adam |
| 鐢熸垚鍣ㄨ緭鍑� | image |
| 閫熷害 | 5.56 step/s |
-| 鑴氭湰 | [AttGAN script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/AttGAN) |
+| 鑴氭湰 | [AttGAN script](https://gitee.com/mindspore/models/tree/master/research/cv/AttGAN) |
### 鎺ㄧ悊鎬ц兘
@@ -242,4 +242,4 @@ bash run_infer_310.sh [GEN_MINDIR_PATH] [ATTR_FILE_PATH] [DATA_PATH] [NEED_PREPR
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/CGAN/README.md b/research/cv/CGAN/README.md
index 0ce1ffc563d2c94cc4d6a96bc1c68e83059db3a4..5cb26b4954ba641adc3197792bca4ce6a6a22f58 100644
--- a/research/cv/CGAN/README.md
+++ b/research/cv/CGAN/README.md
@@ -123,7 +123,7 @@ bash run_distributed_train_ascend.sh /path/to/MNIST_Data/train /path/to/hccl_8p_
```
- Notes
-1. hccl.json which is specified by RANK_TABLE_FILE is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+1. hccl.json which is specified by RANK_TABLE_FILE is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
### [Training Result](#content)
@@ -170,7 +170,7 @@ python export.py --ckpt_dir /path/to/train/ckpt/G_50.ckpt
| Loss | g_loss: 4.9693 d_loss: 0.1540 |
| Total time | 7.5 mins(8p) |
| Checkpoint for Fine tuning | 26.2M(.ckpt file) |
-| Scripts | [cgan script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/CGAN) |
+| Scripts | [cgan script](https://gitee.com/mindspore/models/tree/master/research/cv/CGAN) |
# [Description of Random Situation](#contents)
@@ -178,4 +178,4 @@ We use random seed in train.py and cell.py for weight initialization.
# [Model_Zoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/CycleGAN/README.md b/research/cv/CycleGAN/README.md
index 9c3255acab8f95256be2525945f146172e1ad612..dbbb16f0b55a4e90bc2270993736084b8c6bf9ee 100644
--- a/research/cv/CycleGAN/README.md
+++ b/research/cv/CycleGAN/README.md
@@ -179,4 +179,4 @@ We use Depth Resnet Generator on Ascend and Resnet Generator on GPU.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/DDM/README.md b/research/cv/DDM/README.md
index d69f30c8d84594b827ca7f2b265a92a9923d2e91..b699c4376f1735cbbec78ec31da5f36fe6e24faa 100644
--- a/research/cv/DDM/README.md
+++ b/research/cv/DDM/README.md
@@ -137,4 +137,4 @@ The Results on all numbers of labeled target images on GTA5->Cityscapes are list
## ModeZoo Homepage
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/DnCNN/README.md b/research/cv/DnCNN/README.md
index 4cf81f54d29c9f244208d27492731778d1648e3a..eb43456e62e7a9da9352496445563758a413e3cb 100644
--- a/research/cv/DnCNN/README.md
+++ b/research/cv/DnCNN/README.md
@@ -262,4 +262,4 @@ python export.py CKPT_PATH
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/EDSR/README_CN.md b/research/cv/EDSR/README_CN.md
index f6ffa8ec7f286cdcef724b4e663c7c1dda932018..1af53d936dbfcbd26d0b497517a039e3b2d748b8 100644
--- a/research/cv/EDSR/README_CN.md
+++ b/research/cv/EDSR/README_CN.md
@@ -113,7 +113,7 @@ EDSR鏄敱澶氫釜浼樺寲鍚庣殑residual blocks涓茶仈鑰屾垚锛岀浉姣斿師濮嬬増鏈殑r
# 蹇€熷叆闂�
閫氳繃瀹樻柟缃戠珯瀹夎MindSpore鍚庯紝鎮ㄥ彲浠ユ寜鐓у涓嬫楠よ繘琛岃缁冨拰璇勪及銆傚浜庡垎甯冨紡璁粌锛岄渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨刪ccl閰嶇疆鏂囦欢銆傝閬靛惊浠ヤ笅閾炬帴涓殑璇存槑锛�
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>
- Ascend-910澶勭悊鍣ㄧ幆澧冭繍琛屽崟鍗¤缁僁IV2K
@@ -434,4 +434,4 @@ python export.py --config_path DIV2K_config.yaml --output_path [dir to save mode
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/FaceAttribute/README.md b/research/cv/FaceAttribute/README.md
index 67d95da593e58f90015dbbf8fe8b4009b2eef5e0..b72fd079881a7c0d5f6df87d828ba0616a516e2b 100644
--- a/research/cv/FaceAttribute/README.md
+++ b/research/cv/FaceAttribute/README.md
@@ -449,4 +449,4 @@ Inference result is saved in current path, you can find result like this in acc.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/FaceDetection/README.md b/research/cv/FaceDetection/README.md
index d1c596aa11bd7f9a563ae0b2d6143978801c74cd..cd90adae06c2e729fdee77a475c92e4803ace92b 100644
--- a/research/cv/FaceDetection/README.md
+++ b/research/cv/FaceDetection/README.md
@@ -420,4 +420,4 @@ Saving ../../results/0-2441_61000/.._.._results_0-2441_61000_face_AP_0.7575.png
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/FaceQualityAssessment/README.md b/research/cv/FaceQualityAssessment/README.md
index 0acbe86ab7a7b7a948ba685db125ff7a6bbacc4c..7f5fb61e001c464927d29ad370ef3aa0502e3a67 100644
--- a/research/cv/FaceQualityAssessment/README.md
+++ b/research/cv/FaceQualityAssessment/README.md
@@ -474,4 +474,4 @@ sh run_export_cpu.sh [PRETRAINED_BACKBONE] [BATCH_SIZE] [FILE_NAME](optional)
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/FaceRecognition/README.md b/research/cv/FaceRecognition/README.md
index 3877f7bce0c9ca9ebc980d91b22d20e25ac6b6bf..ebd8b33716b1e1f32ef6f2ebbeac2f3241f0bdc8 100644
--- a/research/cv/FaceRecognition/README.md
+++ b/research/cv/FaceRecognition/README.md
@@ -427,4 +427,4 @@ You will get the result as following in "./scripts/acc.log" if 'dis_dataset' ran
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/FaceRecognitionForTracking/README.md b/research/cv/FaceRecognitionForTracking/README.md
index 0d293f23df049ef7e49df44531e6b2a8e008946c..dab71bc7329ddb20a62d1ed084d321e33fc2fd84 100644
--- a/research/cv/FaceRecognitionForTracking/README.md
+++ b/research/cv/FaceRecognitionForTracking/README.md
@@ -476,4 +476,4 @@ Inference result is saved in current path, you can find result like this in reca
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/GENet_Res50/README_CN.md b/research/cv/GENet_Res50/README_CN.md
index ee2ddfd8fa070415a5efcd50b9eb8d201c8906d5..eb7242c0a53748b0b8b8113766824f60e372ab73 100644
--- a/research/cv/GENet_Res50/README_CN.md
+++ b/research/cv/GENet_Res50/README_CN.md
@@ -267,4 +267,4 @@ dataset.py涓缃簡鈥渃reate_dataset鈥濆嚱鏁板唴鐨勭瀛愶紝鍚屾椂杩樹娇鐢�
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
\ No newline at end of file
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
\ No newline at end of file
diff --git a/research/cv/HourNAS/README.md b/research/cv/HourNAS/README.md
index cb2850ba8cb634ef6531d5b95e4aa2af2cf920a3..a5f556743253169902cdcc2ebe5511cce8cfdc10 100644
--- a/research/cv/HourNAS/README.md
+++ b/research/cv/HourNAS/README.md
@@ -101,4 +101,4 @@ We set the seed inside dataset.py.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/ICNet/README.md b/research/cv/ICNet/README.md
index de7842d4787ce6bb0b3ccf083ef6ec8d279cb5cd..00d5db4beefc67c73ba6f12cd7326c88ebf42863 100644
--- a/research/cv/ICNet/README.md
+++ b/research/cv/ICNet/README.md
@@ -148,7 +148,7 @@ keep_checkpoint_max: 10
### Pre-training
-The folder Res50V1_PRE contains the scripts for pre-training and its dataset is [image net](https://image-net.org/). More details in [GENet_Res50](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/GENet_Res50)
+The folder Res50V1_PRE contains the scripts for pre-training and its dataset is [image net](https://image-net.org/). More details in [GENet_Res50](https://gitee.com/mindspore/models/tree/master/research/cv/GENet_Res50)
- Usage:
@@ -158,7 +158,7 @@ The folder Res50V1_PRE contains the scripts for pre-training and its dataset is
- Notes:
-The hccl.json file specified by [RANK_TABLE_FILE] is used when running distributed tasks. You can use [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools) to generate this file.
+The hccl.json file specified by [RANK_TABLE_FILE] is used when running distributed tasks. You can use [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools) to generate this file.
### Distributed Training
@@ -242,4 +242,4 @@ The seed in the `create_icnet_dataset` function is set in `cityscapes_mindrecord
# [ModelZoo Homepage](#Content)
-Please visit the official website [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please visit the official website [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/IPT/README.md b/research/cv/IPT/README.md
index 93849c2e8e2de1c78910f5634bcec30dc7bb4f8e..c6fd60d06f14dc2e6e0fc312fbddd277eea8b886 100644
--- a/research/cv/IPT/README.md
+++ b/research/cv/IPT/README.md
@@ -192,4 +192,4 @@ Derain results:
## ModeZoo Homepage
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/LearningToSeeInTheDark/README_CN.md b/research/cv/LearningToSeeInTheDark/README_CN.md
index 8cd0bb1e04d0e82c9406513ed519e3bf09d8515b..d8fe2299d5e665bf510fea38f4000e7e96a8b954 100644
--- a/research/cv/LearningToSeeInTheDark/README_CN.md
+++ b/research/cv/LearningToSeeInTheDark/README_CN.md
@@ -152,7 +152,7 @@ python preprocess.py --raw_path [RAW_PATH] --save_path [SAVE_PATH]
鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆�
-鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)涓殑璇存槑銆�
+鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)涓殑璇存槑銆�
璁粌缁撴灉淇濆瓨鍦ㄧず渚嬭矾寰勪腑锛屾枃浠跺す鍚嶇О浠モ€渢rain鈥濇垨鈥渢rain_parallel鈥濆紑澶淬€傛偍鍙湪姝よ矾寰勪笅鐨勬棩蹇椾腑鎵惧埌妫€鏌ョ偣鏂囦欢浠ュ強缁撴灉锛屽涓嬫墍绀恒€�
@@ -246,4 +246,4 @@ unet_parts.py train_sony.py涓悇鑷缃簡闅忔満绉嶅瓙銆�
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
\ No newline at end of file
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
\ No newline at end of file
diff --git a/research/cv/LightCNN/README_CN.md b/research/cv/LightCNN/README_CN.md
index b7dc957f4872dc7a0a58dd44b7654d9278a3678d..e366509d4507447f33d2d76a17f3e9cdbd1096ba 100644
--- a/research/cv/LightCNN/README_CN.md
+++ b/research/cv/LightCNN/README_CN.md
@@ -106,7 +106,7 @@ LightCNN閫傜敤浜庢湁澶ч噺鍣０鐨勪汉鑴歌瘑鍒暟鎹泦锛屾彁鍑轰簡maxout 鐨�
- [MindSpore鏁欑▼](https://www.mindspore.cn/tutorials/zh-CN/master/index.html)
- [MindSpore Python API](https://www.mindspore.cn/docs/api/zh-CN/master/index.html)
- 鐢熸垚config json鏂囦欢鐢ㄤ簬8鍗¤缁冦€�
- - [绠€鏄撴暀绋媇(https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)
+ - [绠€鏄撴暀绋媇(https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)
- 璇︾粏閰嶇疆鏂规硶璇峰弬鐓瀹樼綉鏁欑▼](https://www.mindspore.cn/tutorials/zh-CN/master/intermediate/distributed_training/distributed_training_ascend.html#id3)銆�
# 蹇€熷叆闂�
@@ -428,11 +428,11 @@ python3 eval_blfur.py \
| 杈撳嚭 | 姒傜巼 |
| 鎹熷け | 0.10905003 |
| 鎬ц兘 | 369,144,120.56 ms锛堝崟鍗★級<br> 85,369,778.48 ms锛堝叓鍗★級 |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/LightCNN) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/research/cv/LightCNN) |
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
[1]: https://arxiv.org/pdf/1511.02683
[2]: http://pan.baidu.com/s/1gfxB0iB
diff --git a/research/cv/ManiDP/Readme.md b/research/cv/ManiDP/Readme.md
index 2d74e7f67c81fb94615a454e320cdf5b829b28ee..2f4302712e41d70ffaaf7f3eafe0e28070067904 100644
--- a/research/cv/ManiDP/Readme.md
+++ b/research/cv/ManiDP/Readme.md
@@ -120,4 +120,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/MaskedFaceRecognition/README.md b/research/cv/MaskedFaceRecognition/README.md
index 2589583f546e771c19c8e0181f4cf209caceac34..7434923f904a3029426abc8f49559213a74d3d5c 100644
--- a/research/cv/MaskedFaceRecognition/README.md
+++ b/research/cv/MaskedFaceRecognition/README.md
@@ -138,4 +138,4 @@ You will get the result as following in "./scripts/log_inference/outputs/models/
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/Pix2Pix/README.md b/research/cv/Pix2Pix/README.md
index d410a9232f6c68f71bd22041e31859d9db951dbc..00a0ca5cb74357b07152cdadb6800d5a87a3ad95 100644
--- a/research/cv/Pix2Pix/README.md
+++ b/research/cv/Pix2Pix/README.md
@@ -292,4 +292,4 @@ bash run_infer_310.sh [The path of the MINDIR for 310 infer] [The path of the da
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/ProtoNet/README.md b/research/cv/ProtoNet/README.md
index 07558b25353594ec611ff43fce07df5241cfd094..109618ffd5e13cdd2bc9e0bf0808f960c059d74e 100644
--- a/research/cv/ProtoNet/README.md
+++ b/research/cv/ProtoNet/README.md
@@ -165,8 +165,8 @@ Test Acc: 0.9954400658607483 Loss: 0.02102319709956646
| Speed | 215 ms/step |
| Total time | 3 h 23m (8p) |
| Checkpoint for Fine tuning | 440 KB (.ckpt file) |
-| Scripts | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/ProtoNet> |
+| Scripts | <https://gitee.com/mindspore/models/tree/master/research/cv/ProtoNet> |
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/RCAN/README.md b/research/cv/RCAN/README.md
index 384c04bdcdde508d4cafc9c4867b8b2c169ba06e..f9cc69c6bbecfd5f37ec682e171f5e854588eb9f 100644
--- a/research/cv/RCAN/README.md
+++ b/research/cv/RCAN/README.md
@@ -226,7 +226,7 @@ sh scripts/run_ascend_distribute.sh [TRAIN_DATA_DIR]
sh scripts/run_ascend_distribute.sh [RANK_TABLE_FILE] [TRAIN_DATA_DIR]
```
-- 鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆傚叿浣撴搷浣滐紝鍙傝锛�<https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>
+- 鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆傚叿浣撴搷浣滐紝鍙傝锛�<https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>
## 璇勪及杩囩▼
@@ -273,7 +273,7 @@ sh scripts/eval.sh [TEST_DATA_DIR] [CHECKPOINT_PATH] [DATASET_TYPE]
| 閫熷害 | 8鍗★細205姣/姝� |
| 鎬绘椂闀� | 8鍗★細14.74灏忔椂 |
| 璋冧紭妫€鏌ョ偣 | 0.2 GB锛�.ckpt 鏂囦欢锛� |
-| 鑴氭湰 |[RCAN](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/RCAN) | |
+| 鑴氭湰 |[RCAN](https://gitee.com/mindspore/models/tree/master/research/cv/RCAN) | |
### 璇勪及鎬ц兘
@@ -290,4 +290,4 @@ sh scripts/eval.sh [TEST_DATA_DIR] [CHECKPOINT_PATH] [DATASET_TYPE]
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/SE-Net/README.md b/research/cv/SE-Net/README.md
index d37647258faa6930dfe570f45dcd0c6118ecbcc4..b072d3eeda908555d518aaa33893a02ef324c465 100644
--- a/research/cv/SE-Net/README.md
+++ b/research/cv/SE-Net/README.md
@@ -206,7 +206,7 @@ sh run_standalone_train_gpu.sh se-resnet50 imagenet2012 [DATASET_PATH]
For distributed training, a hccl configuration file with JSON format needs to be created in advance.
-Please follow the instructions in the link [hccn_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+Please follow the instructions in the link [hccn_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
Training result will be stored in the example path, whose folder name begins with "train" or "train_parallel". Under this, you can find checkpoint file together with result like the following in log.
@@ -310,7 +310,7 @@ result: {'top_5_accuracy': 93.86%, 'top_1_accuracy': 77.80%}
| Total time | # mins | 8pcs: 15.9 hours |
| Parameters (M) | 285M | 285M |
| Checkpoint for Fine tuning | # M (.ckpt file) | # M (.ckpt file) |
-| Scripts | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/SE-Net> |<https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/SE-Net> |
+| Scripts | <https://gitee.com/mindspore/models/tree/master/research/cv/SE-Net> |<https://gitee.com/mindspore/models/tree/master/research/cv/SE-Net> |
### Inference Performance
@@ -349,4 +349,4 @@ In dataset.py, we set the seed inside "create_dataset" function. We also use ran
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/SE_ResNeXt50/README_CN.md b/research/cv/SE_ResNeXt50/README_CN.md
index ee234e4fac097379cd321d96746a8583eb525e1f..112c78a445176d9accb2cb1fe5abf68d54ff876a 100644
--- a/research/cv/SE_ResNeXt50/README_CN.md
+++ b/research/cv/SE_ResNeXt50/README_CN.md
@@ -94,7 +94,7 @@ SE-ResNeXt鐨勬€讳綋缃戠粶鏋舵瀯濡備笅锛� [閾炬帴](https://arxiv.org/abs/1709.015
璇烽伒寰互涓嬮摼鎺ヤ腑鐨勮鏄庯細
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.>
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools.>
# 鑴氭湰璇存槑
@@ -280,4 +280,4 @@ SE-ResNeXt鐨勬€讳綋缃戠粶鏋舵瀯濡備笅锛� [閾炬帴](https://arxiv.org/abs/1709.015
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
\ No newline at end of file
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
\ No newline at end of file
diff --git a/research/cv/SRGAN/README.md b/research/cv/SRGAN/README.md
index c551ebd5526f447b5ea3b0f86fc4433555cca13d..d1bce2c0c4562041a5885513d67d5286339ed680 100644
--- a/research/cv/SRGAN/README.md
+++ b/research/cv/SRGAN/README.md
@@ -41,7 +41,7 @@ Validation and eval evaluationdataset used: [Set5](http://people.rennes.inria.fr
The process of training SRGAN needs a pretrained VGG19 based on Imagenet.
-[Training scripts](<https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/vgg16>)|
+[Training scripts](<https://gitee.com/mindspore/models/tree/master/official/cv/vgg16>)|
[VGG19 pretrained model](<https://download.mindspore.cn/model_zoo/>)
# [Environment Requirements](#contents)
@@ -143,7 +143,7 @@ Evaluation result will be stored in the scripts/result. Under this, you can find
| Speed | 1pc(Ascend): 540 ms/step; 8pcs: 1500 ms/step |
| Total time | 8pcs: 8h |
| Checkpoint for Fine tuning | 184M (.ckpt file) |
-| Scripts | [srgan script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/SRGAN) |
+| Scripts | [srgan script](https://gitee.com/mindspore/models/tree/master/research/cv/SRGAN) |
### Evaluation Performance
@@ -158,4 +158,4 @@ Evaluation result will be stored in the scripts/result. Under this, you can find
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/STGAN/README.md b/research/cv/STGAN/README.md
index 492a2831d74382ed177e9ba3acecc13a41d23040..dd7d34cdbe22bdb370adfd526710c12959e074c1 100644
--- a/research/cv/STGAN/README.md
+++ b/research/cv/STGAN/README.md
@@ -190,7 +190,7 @@ python export.py --ckpt_path [CHECKPOINT_PATH] --platform [PLATFORM] --file_form
| Speed | 1pc: 400 ms/step; 8pcs: 143 ms/step |
| Total time | 1pc: 41:36:07 |
| Checkpoint for Fine tuning | 170.55M(.ckpt file) |
-| Scripts | [STGAN script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/STGAN) |
+| Scripts | [STGAN script](https://gitee.com/mindspore/models/tree/master/research/cv/STGAN) |
## [Model Description](#contents)
@@ -200,11 +200,11 @@ In dataset.py, we set the seed inside ```create_dataset``` function.
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
## FAQ
-Please refer to [ModelZoo FAQ](https://gitee.com/mindspore/mindspore/tree/master/model_zoo#FAQ) to get some common FAQ.
+Please refer to [ModelZoo FAQ](https://gitee.com/mindspore/models#FAQ) to get some common FAQ.
- **Q**: Get "out of memory" error in PYNATIVE_MODE.
**A**: You can set smaller batch size, e.g. 32, 16.
diff --git a/research/cv/SiamFC/README.md b/research/cv/SiamFC/README.md
index 1624fff7d106a6991ae95fe6f9a58ab2ca463115..4a51504dce357a86575402d116c0c87b8bfac77e 100644
--- a/research/cv/SiamFC/README.md
+++ b/research/cv/SiamFC/README.md
@@ -191,5 +191,5 @@ Check the checkpoint path used for evaluation before running the following comma
|loss function |BCEWithLogits |
|training speed | epoch time锛�285693.557 ms per step time :42.961 ms |
|total time |about 5 hours |
-|Script URL |<https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/SiamFC> |
+|Script URL |<https://gitee.com/mindspore/models/tree/master/research/cv/SiamFC> |
|Random number seed |set_seed = 1234 |
diff --git a/research/cv/Spnas/README.md b/research/cv/Spnas/README.md
index f699fdaa2d3f4d10712963e3ab317630744e42f7..b6d3dd0a67f2c8f81e7bb2868784dabfe20ffdc1 100644
--- a/research/cv/Spnas/README.md
+++ b/research/cv/Spnas/README.md
@@ -9,28 +9,28 @@ SP-NAS is an efficient architecture search algorithm for object detection and se
This method has two phases:
1. In serial phase, the block sequence with optimal scaling ratio and output channel is found by using the "swap-expand-reignite" search policy. This search policy can guranteen a new searched architecture to completely inherit of weight from arichtectures before morphism.
-2. In parallel phase, parallized network structures are designed, sub-networks integrated by different feature layers are searched to better fuse the high-level and low-level semantic features. The following figure shows the search policy.
+2. In parallel phase, parallelized network structures are designed, sub-networks integrated by different feature layers are searched to better fuse the high-level and low-level semantic features. The following figure shows the search policy.
## Search Space and Search Policy
-**Serial-level**
+### Serial-level
- Swap-expand-reignite policy: Growing starts from a small network to avoid repeated ImageNet pre-training.
- - The new candidate network is obtained by "switching" or "expanding" the grown network for many times.
- - Quickly train and evaluate candidate networks based on inherited parameters.
- - When the growth reaches the bottleneck, the network is re-trained using ImageNet. The number of ignition times is no more than 2.
+- The new candidate network is obtained by "switching" or "expanding" the grown network for many times.
+- Quickly train and evaluate candidate networks based on inherited parameters.
+- When the growth reaches the bottleneck, the network is re-trained using ImageNet. The number of ignition times is no more than 2.
- Constrained optimal network: A serial network with limited network resources (latency, video memory usage, or complexity) is selected to obtain the maximum performance.
- Search space configuration:
- - Block type: Basic Block, BottleNeck Block, and ResNext;
- - Network depth: 8 to 60 blocks;
- - Number of stages: 5 to 7;
- - Width: Position where the channel size is doubled in the entire sequence.
+- Block type: Basic Block, BottleNeck Block, and ResNext;
+- Network depth: 8 to 60 blocks;
+- Number of stages: 5 to 7;
+- Width: Position where the channel size is doubled in the entire sequence.
-**Parallel-level**
+### Parallel-level
- Based on the result SerialNet from the serial search phase (or the existing handcraft serial network such as ResNet series), search for the parallel structure stacked on SerialNet to better utilize and fuse feature information with different resolutions from different feature layers.
- Search policy: Random sampling to meet the resource constraints: The probability of adding additional subnets is inversely proportional to the FLOPS of the subnets to be added.
@@ -43,7 +43,6 @@ The benchmark datasets can be downloaded as follows:
COCO,
[COCO2017](https://cocodataset.org/#download),
-
## Requirements
### Hardware (Ascend)
@@ -103,6 +102,7 @@ sh scripts/run_distributed.sh
> Inference example:
Modify src/eval.yml:
+
```bash
models_folder: [CHECKPOINT_PATH]
```
@@ -133,7 +133,6 @@ COCO results:
| AmoebaNet | 43.4 | - | - | - | - |
| NAS-FPN | 48.0 | - | - | - | - |
-
## ModeZoo Homepage
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/StackedHourglass/README_CN.md b/research/cv/StackedHourglass/README_CN.md
index e8f19b2618bee07d73f0f50bff5d450c60bf88b8..876757bca113d84483caa48d93fe0204d0fb0c6b 100644
--- a/research/cv/StackedHourglass/README_CN.md
+++ b/research/cv/StackedHourglass/README_CN.md
@@ -190,4 +190,4 @@ python export.py --ckpt_file [ckpt 鏂囦欢璺緞]
# ModelZoo
-璇锋牳瀵瑰畼鏂� [涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
\ No newline at end of file
+璇锋牳瀵瑰畼鏂� [涓婚〉](https://gitee.com/mindspore/models)銆�
\ No newline at end of file
diff --git a/research/cv/StarGAN/README.md b/research/cv/StarGAN/README.md
index 7482fe632a461e9d62a9abff6c592cbe88994862..13f2e332e17f582d67124930e8c5225fdfd62cdd 100644
--- a/research/cv/StarGAN/README.md
+++ b/research/cv/StarGAN/README.md
@@ -117,7 +117,7 @@ python export.py
| Total time | 1pc: 10h; |
| Parameters (M) | 8.423 M |
| Checkpoint for Fine tuning | 32.15M (.ckpt file) |
-| Scripts | [StarGAN script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/StarGAN) |
+| Scripts | [StarGAN script](https://gitee.com/mindspore/models/tree/master/research/cv/StarGAN) |
### Inference Performance
@@ -133,4 +133,4 @@ python export.py
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/TNT/readme.md b/research/cv/TNT/readme.md
index cf68003ad70ca449245c666a93cc5cb678287524..05fdb427496f8cc7735697348c7aa83d2632c9fa 100644
--- a/research/cv/TNT/readme.md
+++ b/research/cv/TNT/readme.md
@@ -125,4 +125,4 @@ In dataset.py, we set the seed inside "create_dataset" function. We also use ran
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
\ No newline at end of file
+Please check the official [homepage](https://gitee.com/mindspore/models).
\ No newline at end of file
diff --git a/research/cv/adelaide_ea/README.md b/research/cv/adelaide_ea/README.md
index ae106bc9b4136de57dfdf07432a598749ebe8b43..40e7ef09959da93e8486a3e0aeaebd8162795066 100644
--- a/research/cv/adelaide_ea/README.md
+++ b/research/cv/adelaide_ea/README.md
@@ -224,7 +224,7 @@ sh scripts/run_distributed.sh [RANK_TABLE_FILE]
Please follow the instructions in the link below:
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>.
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>.
`$RANK_TABLE_FILE` is needed when you are running a distribute task on ascend.
> Or one can run following script for all tasks.
@@ -275,8 +275,8 @@ The Results on super resolution tasks are listed as below.
| Loss Function | CrossEntropyLoss |
| Output | mAP |
| mIOU | 0.7602 |
-| Scripts | [adelaide_ea script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/adelaide_ea) |
+| Scripts | [adelaide_ea script](https://gitee.com/mindspore/models/tree/master/research/cv/adelaide_ea) |
## ModeZoo Homepage
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/advanced_east/README.md b/research/cv/advanced_east/README.md
index 7152516260c277083697db40cb96f57c71d9aa97..ac4e477c2d0caf7e9a40e46fd6e8b6e5c23c3cc3 100644
--- a/research/cv/advanced_east/README.md
+++ b/research/cv/advanced_east/README.md
@@ -268,4 +268,4 @@ On the default
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/arcface/README_CN.md b/research/cv/arcface/README_CN.md
index f08a44a5d210cafd6b2b49695d879c570fc9338d..88b37499b2babbc9d9b38843e569e11a753ca0a1 100644
--- a/research/cv/arcface/README_CN.md
+++ b/research/cv/arcface/README_CN.md
@@ -195,7 +195,7 @@ epoch time: 1104929.793 ms, per step time: 97.162 ms
| 鎬绘椂闂� | 1鍗★細65灏忔椂锛�8鍗★細8.5灏忔椂 |
| 鍙傛暟(M) | 85.2 |
| 寰皟妫€鏌ョ偣 | 1249M 锛�.ckpt file锛� |
-| 鑴氭湰 | [鑴氭湰璺緞](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/arcface) |
+| 鑴氭湰 | [鑴氭湰璺緞](https://gitee.com/mindspore/models/tree/master/research/cv/arcface) |
### 鎺ㄧ悊鎬ц兘
@@ -225,4 +225,4 @@ epoch time: 1104929.793 ms, per step time: 97.162 ms
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
\ No newline at end of file
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
\ No newline at end of file
diff --git a/research/cv/autoaugment/README_CN.md b/research/cv/autoaugment/README_CN.md
index 7be6c9cf91c94aa4f3e7afe465fb02849599ddda..5fe07278d2341bdccf2b1d1cc9e8396c4cbac627 100644
--- a/research/cv/autoaugment/README_CN.md
+++ b/research/cv/autoaugment/README_CN.md
@@ -100,7 +100,7 @@ cifar-10-batches-bin
鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆�
-鍏蜂綋鎿嶄綔锛岃鍙傝[hccn_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)涓殑璇存槑銆�
+鍏蜂綋鎿嶄綔锛岃鍙傝[hccn_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)涓殑璇存槑銆�
## 鑴氭湰璇存槑
@@ -386,4 +386,4 @@ bash run_infer_310.sh [MINDIR_PATH] [DATASET_PATH] [NEED_PREPROCESS] [DEVICE_ID]
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/centernet/README.md b/research/cv/centernet/README.md
index 2b08e9dc28d9e4f36386b03034b9e0b17981da32..e9d54d857aa93b782364a181f11ac975e536429b 100644
--- a/research/cv/centernet/README.md
+++ b/research/cv/centernet/README.md
@@ -579,7 +579,7 @@ CenterNet on 11.8K images(The annotation and data format must be the same as coc
| Total time: training | 1p: 4.38 days; 8p: 13-14 h |
| Total time: evaluation | keep res: test 1.7h, val 0.7h; fix res: test 50 min, val 12 min|
| Checkpoint | 242M (.ckpt file) |
-| Scripts | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/centernet> |
+| Scripts | <https://gitee.com/mindspore/models/tree/master/research/cv/centernet> |
### Inference Performance On Ascend
@@ -604,4 +604,4 @@ In train.py, we set a random seed to make sure that each node has the same initi
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/centernet/scripts/ascend_distributed_launcher/README.md b/research/cv/centernet/scripts/ascend_distributed_launcher/README.md
index 907754ff93d5b058e11b34aa5b3b73d8aa73a8ec..2f0d29a115aef2379f9d7b4cdd62351b21a47ddb 100644
--- a/research/cv/centernet/scripts/ascend_distributed_launcher/README.md
+++ b/research/cv/centernet/scripts/ascend_distributed_launcher/README.md
@@ -41,7 +41,7 @@ log file dir: ./LOG6/training_log.txt
## Note
-1. Note that `hccl_2p_56_x.x.x.x.json` can use [hccl_tools.py](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools) to generate.
+1. Note that `hccl_2p_56_x.x.x.x.json` can use [hccl_tools.py](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools) to generate.
2. For hyper parameter, please note that you should customize the scripts `hyper_parameter_config.ini`. Please note that these two hyper parameters are not allowed to be configured here:
- device_id
diff --git a/research/cv/centernet_det/README.md b/research/cv/centernet_det/README.md
index 6a7f2974eab2b7ce18b11fe5dce4851a415cb2bb..c043e5d24163896337af04c44f8b571ef03be8e2 100644
--- a/research/cv/centernet_det/README.md
+++ b/research/cv/centernet_det/README.md
@@ -573,7 +573,7 @@ CenterNet on 11.8K images(The annotation and data format must be the same as coc
| Total time: training | 8p: 44 h |
| Total time: evaluation | keep res: test 1h, val 0.25h; fix res: test 40 min, val 8 min|
| Checkpoint | 2.3G (.ckpt file) |
-| Scripts | [centernet_det script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/centernet_det) |
+| Scripts | [centernet_det script](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_det) |
### Inference Performance On Ascend 910
@@ -610,8 +610,8 @@ In train.py, we set a random seed to make sure that each node has the same initi
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
# FAQ
-First refer to [ModelZoo FAQ](https://gitee.com/mindspore/mindspore/tree/master/model_zoo#FAQ) to find some common public questions.
+First refer to [ModelZoo FAQ](https://gitee.com/mindspore/models#FAQ) to find some common public questions.
diff --git a/research/cv/centernet_det/scripts/ascend_distributed_launcher/README.md b/research/cv/centernet_det/scripts/ascend_distributed_launcher/README.md
index 42a446891b63650404de9353d608a57f4f36772a..2aad6df596d7cbdb179b36385a607f41bb3f0940 100644
--- a/research/cv/centernet_det/scripts/ascend_distributed_launcher/README.md
+++ b/research/cv/centernet_det/scripts/ascend_distributed_launcher/README.md
@@ -41,7 +41,7 @@ log file dir: ./LOG6/training_log.txt
## Note
-1. Note that `hccl_2p_56_x.x.x.x.json` can use [hccl_tools.py](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools) to generate.
+1. Note that `hccl_2p_56_x.x.x.x.json` can use [hccl_tools.py](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools) to generate.
2. For hyper parameter, please note that you should customize the scripts `hyper_parameter_config.ini`. Please note that these two hyper parameters are not allowed to be configured here:
- device_id
diff --git a/research/cv/centernet_resnet101/README.md b/research/cv/centernet_resnet101/README.md
index 1df4465ea39c7697e5f9425e39188dd6a898cf02..d9be8cbc7dfbc0ea7f3a17637b5e0fc434344d55 100644
--- a/research/cv/centernet_resnet101/README.md
+++ b/research/cv/centernet_resnet101/README.md
@@ -564,7 +564,7 @@ CenterNet on 11.8K images(The annotation and data format must be the same as coc
| Total time: training | 8p: 23 h |
| Total time: evaluation | keep res: test 1h, val 0.7h; fix res: test 40min, val 8min|
| Checkpoint | 591.70MB (.ckpt file) |
-| Scripts | [centernet_resnet101 script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/centernet_resnet101) |
+| Scripts | [centernet_resnet101 script](https://gitee.com/mindspore/models/tree/master/research/cv/centernet_resnet101) |
### Inference Performance On Ascend 910
@@ -601,10 +601,10 @@ In train.py, we set a random seed to make sure that each node has the same initi
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
# FAQ
-First refer to [ModelZoo FAQ](https://gitee.com/mindspore/mindspore/tree/master/model_zoo#FAQ) to find some common public questions.
+First refer to [ModelZoo FAQ](https://gitee.com/mindspore/models#FAQ) to find some common public questions.
- **Q: What to do if memory overflow occurs when using PYNATIVE_MODE锛�** **A**:Memory overflow is usually because PYNATIVE_MODE requires more memory. Setting the batch size to 31 reduces memory consumption and can be used for network training.
diff --git a/research/cv/centernet_resnet101/scripts/ascend_distributed_launcher/README.md b/research/cv/centernet_resnet101/scripts/ascend_distributed_launcher/README.md
index 42a446891b63650404de9353d608a57f4f36772a..2aad6df596d7cbdb179b36385a607f41bb3f0940 100644
--- a/research/cv/centernet_resnet101/scripts/ascend_distributed_launcher/README.md
+++ b/research/cv/centernet_resnet101/scripts/ascend_distributed_launcher/README.md
@@ -41,7 +41,7 @@ log file dir: ./LOG6/training_log.txt
## Note
-1. Note that `hccl_2p_56_x.x.x.x.json` can use [hccl_tools.py](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools) to generate.
+1. Note that `hccl_2p_56_x.x.x.x.json` can use [hccl_tools.py](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools) to generate.
2. For hyper parameter, please note that you should customize the scripts `hyper_parameter_config.ini`. Please note that these two hyper parameters are not allowed to be configured here:
- device_id
diff --git a/research/cv/centernet_resnet50_v1/readme.md b/research/cv/centernet_resnet50_v1/readme.md
index fb06595d5769680d7e9180a758e7ebaa14b1e589..4c2eb1e167af6f256df9958017b864ceedc9fb63 100644
--- a/research/cv/centernet_resnet50_v1/readme.md
+++ b/research/cv/centernet_resnet50_v1/readme.md
@@ -419,7 +419,7 @@ CenterNet on 11.8K images(The annotation and data format must be the same as coc
| Total time: training | 8p: 25 h |
| Total time: evaluation | keep res: test 1h, val 0.25h; fix res: test 40 min, val 8 min |
| Checkpoint | 375MB (.ckpt file) |
-| Scripts | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/centernet> |
+| Scripts | <https://gitee.com/mindspore/models/tree/master/research/cv/centernet> |
### Inference Performance On Ascend
@@ -442,4 +442,4 @@ In train.py, we set a random seed to make sure that each node has the same initi
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/centernet_resnet50_v1/scripts/ascend_distributed_launcher/README.md b/research/cv/centernet_resnet50_v1/scripts/ascend_distributed_launcher/README.md
index 42a446891b63650404de9353d608a57f4f36772a..2aad6df596d7cbdb179b36385a607f41bb3f0940 100644
--- a/research/cv/centernet_resnet50_v1/scripts/ascend_distributed_launcher/README.md
+++ b/research/cv/centernet_resnet50_v1/scripts/ascend_distributed_launcher/README.md
@@ -41,7 +41,7 @@ log file dir: ./LOG6/training_log.txt
## Note
-1. Note that `hccl_2p_56_x.x.x.x.json` can use [hccl_tools.py](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools) to generate.
+1. Note that `hccl_2p_56_x.x.x.x.json` can use [hccl_tools.py](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools) to generate.
2. For hyper parameter, please note that you should customize the scripts `hyper_parameter_config.ini`. Please note that these two hyper parameters are not allowed to be configured here:
- device_id
diff --git a/research/cv/dcgan/README.md b/research/cv/dcgan/README.md
index 5c3e2b22b34c124bf34b84614cefc724655647b9..6cb7f37fa7d87f3545ede50a71ce8ee93bc6bdb7 100644
--- a/research/cv/dcgan/README.md
+++ b/research/cv/dcgan/README.md
@@ -130,7 +130,7 @@ run_distribute.sh [RANK_TABLE_FILE] [DATASET_PATH] [SAVE_PATH]
```
- Notes
-1. hccl.json which is specified by RANK_TABLE_FILE is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+1. hccl.json which is specified by RANK_TABLE_FILE is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
### [Training Result](#content)
@@ -190,7 +190,7 @@ python export.py --ckpt_file [CKPT_PATH] --device_target [DEVICE_TARGET] --file_
| Speed | 1pc: 420 ms/step; 8pcs: 143 ms/step |
| Total time | 1pc: 24.32 hours |
| Checkpoint for Fine tuning | 79.05M(.ckpt file) |
-| Scripts | [dcgan script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/dcgan) |
+| Scripts | [dcgan script](https://gitee.com/mindspore/models/tree/master/research/cv/dcgan) |
# [Description of Random Situation](#contents)
@@ -198,4 +198,4 @@ We use random seed in train.py and cell.py for weight initialization.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/deeplabv3plus/README_CN.md b/research/cv/deeplabv3plus/README_CN.md
index fbf74db8d4878e4f673f51b1441182ff74c5607c..60e21eeeeb56fc90c59be4e99d756fc4c1440701 100644
--- a/research/cv/deeplabv3plus/README_CN.md
+++ b/research/cv/deeplabv3plus/README_CN.md
@@ -599,7 +599,7 @@ python ${train_code_path}/eval.py --data_root=/PATH/TO/DATA \
| 鎹熷け | 0.0041095633 |0.003395824|
| 鎬ц兘 | 187736.386 ms锛堝崟鍗★紝s16锛�<br> 44474.187 ms锛堝叓鍗★紝s16锛� | 1080 ms/step锛堝崟鍗★紝s16锛墊
| 寰皟妫€鏌ョ偣 | 453M 锛�.ckpt鏂囦欢锛� | 454M 锛�.ckpt鏂囦欢锛墊
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/deeplabv3plus) |[閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/deeplabv3plus) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/research/cv/deeplabv3plus) |[閾炬帴](https://gitee.com/mindspore/models/tree/master/research/cv/deeplabv3plus) |
# 闅忔満鎯呭喌璇存槑
@@ -607,4 +607,4 @@ dataset.py涓缃簡鈥渃reate_dataset鈥濆嚱鏁板唴鐨勭瀛愶紝鍚屾椂杩樹娇鐢�
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/dem/README.md b/research/cv/dem/README.md
index 79311970519ed42089a02b714e29831821ee5220..046a04944900dda0b5060806584eea059ee3d04c 100644
--- a/research/cv/dem/README.md
+++ b/research/cv/dem/README.md
@@ -219,4 +219,4 @@ In train.py, we use "dataset.Generator(shuffle=True)" to shuffle dataset.
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/dem/README_CN.md b/research/cv/dem/README_CN.md
index c855bc5db0e1a6d8076b7c734e97838f96661d03..737b90bb09c033b9bf3aec4b8edc1ca5f4a1179a 100644
--- a/research/cv/dem/README_CN.md
+++ b/research/cv/dem/README_CN.md
@@ -226,4 +226,4 @@ accuracy _ CUB _ att = 0.58984
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](<https://gitee.com/mindspore/mindspore/tree/master/model_zoo>)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](<https://gitee.com/mindspore/models>)銆�
diff --git a/research/cv/efficientnet-b0/README_CN.md b/research/cv/efficientnet-b0/README_CN.md
index 1fbc8e801447a9b8665ebf6a5c95951f403f0d69..5ce62a9d1d1c39c8b3574693bfb733c9ce98e4b9 100644
--- a/research/cv/efficientnet-b0/README_CN.md
+++ b/research/cv/efficientnet-b0/README_CN.md
@@ -178,7 +178,7 @@ result: {'Loss': 1.8745046273255959, 'Top_1_Acc': 0.7668870192307692, 'Top_5_Acc
| 璁粌鎬绘椂闂� (8p) | 29.5h |
| 璇勪及鎬绘椂闂� | 1min |
| 鍙傛暟閲� (M) | 61M |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/efficientnet-b0) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/research/cv/efficientnet-b0) |
# 闅忔満鎯呭喌鐨勬弿杩�
@@ -186,4 +186,4 @@ result: {'Loss': 1.8745046273255959, 'Top_1_Acc': 0.7668870192307692, 'Top_5_Acc
# ModelZoo
-璇锋牳瀵瑰畼鏂� [涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
\ No newline at end of file
+璇锋牳瀵瑰畼鏂� [涓婚〉](https://gitee.com/mindspore/models)銆�
\ No newline at end of file
diff --git a/research/cv/eppmvsnet/README.md b/research/cv/eppmvsnet/README.md
index e51f8f578f6d7183143f8ac07b6b13a20c72c079..03fac65a307d1d87813cd16f79c6b643c8777a4a 100644
--- a/research/cv/eppmvsnet/README.md
+++ b/research/cv/eppmvsnet/README.md
@@ -145,4 +145,4 @@ No random situation for evaluation.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](http://gitee.com/mindspore/mindspore/tree/master/model_zoo).
\ No newline at end of file
+Please check the official [homepage](http://gitee.com/mindspore/models).
\ No newline at end of file
diff --git a/research/cv/esr_ea/README.md b/research/cv/esr_ea/README.md
index e4c86c5fa1b8890dad88746ad3cae3977c979004..0944253c1d9ecdfb9dd2d24c869985018af30e1d 100644
--- a/research/cv/esr_ea/README.md
+++ b/research/cv/esr_ea/README.md
@@ -195,7 +195,7 @@ sh scripts/run_distributed.sh [RANK_TABLE_FILE]
Please follow the instructions in the link below:
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>.
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>.
`$RANK_TABLE_FILE` is needed when you are running a distribute task on ascend.
> Or one can run following script for all tasks.
@@ -246,8 +246,8 @@ The Results on super resolution tasks are listed as below.
| Loss Function | L1Loss |
| Output | super resolution image |
| PSNR | 41.08 |
-| Scripts | [esr_ea script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/esr_ea) |
+| Scripts | [esr_ea script](https://gitee.com/mindspore/models/tree/master/research/cv/esr_ea) |
## ModeZoo Homepage
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/faceboxes/README.md b/research/cv/faceboxes/README.md
index 0479746f3d32d98ace1564f59b7c6303ffe35b9f..b6bcb4a7415f765e37651690316286dc930c7639 100644
--- a/research/cv/faceboxes/README.md
+++ b/research/cv/faceboxes/README.md
@@ -273,7 +273,7 @@ Parameters for both training and evaluation can be set in config.py
| Total time | 4pcs: 7.6 hours |
| Parameters (M) | 3.84M |
| Checkpoint for Fine tuning | 13M (.ckpt file) |
-| Scripts | [faceboxes script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/faceboxes) |
+| Scripts | [faceboxes script](https://gitee.com/mindspore/models/tree/master/research/cv/faceboxes) |
# [Description of Random Situation](#contents)
@@ -281,4 +281,4 @@ In train.py, we set the seed with setup_seed function.
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/fairmot/README.md b/research/cv/fairmot/README.md
index 070ab6c1b6b615caf6c58b6f40f61d68eae335fc..68812d577634016b813dd35faecacc94eccbcd0d 100644
--- a/research/cv/fairmot/README.md
+++ b/research/cv/fairmot/README.md
@@ -244,4 +244,4 @@ We also use random seed in `src/utils/backbone_dla_conv.py` to initial network w
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/fishnet99/README_CN.md b/research/cv/fishnet99/README_CN.md
index 81dfccea2fd406854d075adff1cf800ae37bd4dd..58c76e50acc728672d16fec06ad2ee0c2099471c 100644
--- a/research/cv/fishnet99/README_CN.md
+++ b/research/cv/fishnet99/README_CN.md
@@ -99,7 +99,7 @@
璇烽伒寰互涓嬮摼鎺ヤ腑鐨勮鏄庯細
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.>
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools.>
- GPU澶勭悊鍣ㄧ幆澧冭繍琛�
@@ -310,4 +310,4 @@
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
\ No newline at end of file
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
\ No newline at end of file
diff --git a/research/cv/ghostnet/README_CN.md b/research/cv/ghostnet/README_CN.md
index dc37f9a456a00e8bce6fa39a9d75747093b9829c..2a8f666477db76098d852b85769e23b088530884 100644
--- a/research/cv/ghostnet/README_CN.md
+++ b/research/cv/ghostnet/README_CN.md
@@ -172,7 +172,7 @@ GhostNet鐨勬€讳綋缃戠粶鏋舵瀯濡備笅锛歔閾炬帴](https://arxiv.org/pdf/1911.11907.
鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆�
-鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)涓殑璇存槑銆�
+鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)涓殑璇存槑銆�
璁粌缁撴灉淇濆瓨鍦ㄧず渚嬭矾寰勪腑锛屾枃浠跺す鍚嶇О浠モ€渢rain鈥濇垨鈥渢rain_parallel鈥濆紑澶淬€傛偍鍙湪姝よ矾寰勪笅鐨勬棩蹇椾腑鎵惧埌妫€鏌ョ偣鏂囦欢浠ュ強缁撴灉锛屽涓嬫墍绀恒€�
diff --git a/research/cv/ghostnet_quant/Readme.md b/research/cv/ghostnet_quant/Readme.md
index da7d2a7d74e26729cbb28bbca45350df202a3aea..f4033baa3b17de57145e5be01166a66afd85604f 100644
--- a/research/cv/ghostnet_quant/Readme.md
+++ b/research/cv/ghostnet_quant/Readme.md
@@ -134,4 +134,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/glore_res200/README_CN.md b/research/cv/glore_res200/README_CN.md
index d8a55b640cf2af0d73468faa5f9e4d78be02935f..6c81a1be65a1805631d5179aa1f547795d8bbdc3 100644
--- a/research/cv/glore_res200/README_CN.md
+++ b/research/cv/glore_res200/README_CN.md
@@ -119,7 +119,7 @@
璇烽伒寰互涓嬮摼鎺ヤ腑鐨勮鏄庯細
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.>
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools.>
# 鑴氭湰璇存槑
@@ -214,7 +214,7 @@
鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆�
-鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)涓殑璇存槑銆�
+鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)涓殑璇存槑銆�
璁粌缁撴灉淇濆瓨鍦ㄧず渚嬭矾寰勪腑锛屾枃浠跺す鍚嶇О浠モ€渢rain鈥濇垨鈥渢rain_parallel鈥濆紑澶淬€傛偍鍙湪姝よ矾寰勪笅鐨勬棩蹇椾腑鎵惧埌妫€鏌ョ偣鏂囦欢浠ュ強缁撴灉锛屽涓嬫墍绀恒€�
@@ -303,7 +303,7 @@ result:{'top_1 acc':0.802303685897436}
| 鎬绘椂闀� | 33鏃�35鍒嗛挓 |94鏃�08鍒� |
| 鍙傛暟(M) | 70.6 |70.6
| 寰皟妫€鏌ョ偣| 807.57M锛�.ckpt鏂囦欢锛� |808.28(.ckpt)
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/glore_res200) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res200) |
### 鎺ㄧ悊鎬ц兘
@@ -326,4 +326,4 @@ transform_utils.py涓娇鐢ㄦ暟鎹寮烘椂閲囩敤浜嗛殢鏈洪€夋嫨绛栫暐锛宼rain.py
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)
diff --git a/research/cv/glore_res50/README.md b/research/cv/glore_res50/README.md
index b4af32993253ba78a8e0d3cbd82352e9d9dba8e4..aa41b14c248e365fdad6a5505edbdaaca7594278 100644
--- a/research/cv/glore_res50/README.md
+++ b/research/cv/glore_res50/README.md
@@ -162,7 +162,7 @@ glore_res鐨勬€讳綋缃戠粶鏋舵瀯濡備笅锛�
鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆�
-鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)涓殑璇存槑銆�
+鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)涓殑璇存槑銆�
### 缁撴灉
@@ -228,7 +228,7 @@ sh run_eval.sh ~/dataset/imagenet 0 ~/ckpt/glore_res50_120-1251.ckpt
| 鎬绘椂闀� | 10.98灏忔椂 |
| 鍙傛暟(M) | 30.5 |
| 寰皟妫€鏌ョ偣| 233.46M锛�.ckpt鏂囦欢锛墊
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/glore_res50) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res50) |
# 闅忔満鎯呭喌璇存槑
@@ -236,4 +236,4 @@ sh run_eval.sh ~/dataset/imagenet 0 ~/ckpt/glore_res50_120-1251.ckpt
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/hardnet/README_CN.md b/research/cv/hardnet/README_CN.md
index fe2409488c2ffeddfe42a9a85fe83e6b1d5bec30..d1b901770c83e5c25d31a229c4888d0dd7ef1c58 100644
--- a/research/cv/hardnet/README_CN.md
+++ b/research/cv/hardnet/README_CN.md
@@ -101,7 +101,7 @@ HarDNet鎸囩殑鏄疕armonic DenseNet: A low memory traffic network锛屽叾绐佸嚭鐨�
璇烽伒寰互涓嬮摼鎺ヤ腑鐨勮鏄庯細
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.>
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools.>
- GPU鐜杩愯
@@ -398,7 +398,7 @@ bash run_infer_310.sh [MINDIR_PATH] [DATASET_PATH] [DEVICE_ID]
| 鎬绘椂闀� | 鍗曞崱锛�72灏忔椂50鍒嗛挓; 8鍗★細10灏忔椂14鍒嗛挓 | 8鍗★細71灏忔椂14鍒嗛挓 |
| 鍙傛暟(M) | 13.0 | 13.0 |
| 寰皟妫€鏌ョ偣 | 280M (.ckpt鏂囦欢) | 281M (.ckpt鏂囦欢) |
-| 鑴氭湰 | [hardnet鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/hardnet) | [hardnet鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/hardnet) |
+| 鑴氭湰 | [hardnet鑴氭湰](https://gitee.com/mindspore/models/tree/master/research/cv/hardnet) | [hardnet鑴氭湰](https://gitee.com/mindspore/models/tree/master/research/cv/hardnet) |
### 鎺ㄧ悊鎬ц兘
@@ -498,4 +498,4 @@ bash run_infer_310.sh [MINDIR_PATH] [DATASET_PATH] [DEVICE_ID]
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/ibnnet/README_CN.md b/research/cv/ibnnet/README_CN.md
index 9527ca60ed36b8bb95e9b35d88324a9fedcb4bc7..307fd6725e8896e203057f1f97adcd786f87add4 100644
--- a/research/cv/ibnnet/README_CN.md
+++ b/research/cv/ibnnet/README_CN.md
@@ -213,7 +213,7 @@ sh scripts/run_eval_gpu.sh path/evalset path/ckpt
| 鎬绘椂闂� | 1鍗★細65灏忔椂锛�8鍗★細9.5灏忔椂 |
| 鍙傛暟(M) | 46.15 |
| 寰皟妫€鏌ョ偣 | 293M 锛�.ckpt file锛� |
-| 鑴氭湰 | [鑴氭湰璺緞](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/ibnnet) |
+| 鑴氭湰 | [鑴氭湰璺緞](https://gitee.com/mindspore/models/tree/master/research/cv/ibnnet) |
### 鎺ㄧ悊鎬ц兘
@@ -282,4 +282,4 @@ print("accuracy: ", acc)
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/inception_resnet_v2/README.md b/research/cv/inception_resnet_v2/README.md
index a336f2273fa1627223d8c2d8a23eccf8247d7fcf..71e0ddca1dfb796ae5704283d7be741168296b98 100644
--- a/research/cv/inception_resnet_v2/README.md
+++ b/research/cv/inception_resnet_v2/README.md
@@ -121,7 +121,7 @@ bash scripts/run_standalone_train_ascend.sh DEVICE_ID DATA_DIR
```
> Notes:
-> RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html) , and the device_ip can be got as [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools). For large models like InceptionV4, it's better to export an external environment variable聽`export HCCL_CONNECT_TIMEOUT=600`聽to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
+> RANK_TABLE_FILE can refer to [Link](https://www.mindspore.cn/docs/programming_guide/en/master/distributed_training_ascend.html) , and the device_ip can be got as [Link](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools). For large models like InceptionV4, it's better to export an external environment variable聽`export HCCL_CONNECT_TIMEOUT=600`聽to extend hccl connection checking time from the default 120 seconds to 600 seconds. Otherwise, the connection could be timeout since compiling time increases with the growth of model size.
>
> This is processor cores binding operation regarding the `device_num` and total processor numbers. If you are not expect to do it, remove the operations `taskset` in `scripts/run_distribute_train.sh`
@@ -212,4 +212,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
\ No newline at end of file
+Please check the official [homepage](https://gitee.com/mindspore/models).
\ No newline at end of file
diff --git a/research/cv/inception_resnet_v2/README_CN.md b/research/cv/inception_resnet_v2/README_CN.md
index 596ed0a8e51c6a8dce103d674c4e6f9e78e28016..186bdf42b65e6c86a8d15b7ee8732f0ee648436c 100644
--- a/research/cv/inception_resnet_v2/README_CN.md
+++ b/research/cv/inception_resnet_v2/README_CN.md
@@ -131,7 +131,7 @@ Major parameters in train.py and config.py are:
bash scripts/run_standalone_train_ascend.sh DEVICE_ID DATA_DIR
```
-> 娉細RANK_TABLE_FILE鍙弬鑰僛閾炬帴]( https://www.mindspore.cn/docs/programming_guide/zh-CN/master/distributed_training_ascend.html)銆俤evice_ip鍙互閫氳繃[閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)鑾峰彇
+> 娉細RANK_TABLE_FILE鍙弬鑰僛閾炬帴]( https://www.mindspore.cn/docs/programming_guide/zh-CN/master/distributed_training_ascend.html)銆俤evice_ip鍙互閫氳繃[閾炬帴](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)鑾峰彇
### 缁撴灉
@@ -215,5 +215,5 @@ python export.py --ckpt_file [CKPT_PATH] --device_target [DEVICE_TARGET] --file_
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/metric_learn/README_CN.md b/research/cv/metric_learn/README_CN.md
index 37c7e152bc8401aca4c8d3360add6db7547d552b..d26aa16968ee183b4e001ec1656a8bc210be07e4 100644
--- a/research/cv/metric_learn/README_CN.md
+++ b/research/cv/metric_learn/README_CN.md
@@ -221,7 +221,7 @@ cd Stanford_Online_Products && head -n 1048 test.txt > test_tiny.txt
鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆�
-鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)涓殑璇存槑銆�
+鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)涓殑璇存槑銆�
璁粌缁撴灉淇濆瓨鍦ㄧず渚嬭矾寰勪腑锛屾枃浠跺す鍚嶇О浠モ€渢rain鈥濇垨鈥渢rain_parallel鈥濆紑澶淬€傛偍鍙湪姝よ矾寰勪笅鐨勬棩蹇椾腑鎵惧埌妫€鏌ョ偣鏂囦欢浠ュ強缁撴灉锛屽涓嬫墍绀恒€�
@@ -374,4 +374,4 @@ bash run_infer_310.sh [MINDIR_PATH] [DATASET_PATH] [DEVICE_ID]
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/midas/README.md b/research/cv/midas/README.md
index 970629d0792cc9a8f835ba6cac04bcf5dff50578..f25d23ece0073c1004b6edb77333aaf1ddda3340 100644
--- a/research/cv/midas/README.md
+++ b/research/cv/midas/README.md
@@ -267,4 +267,4 @@ sh run_eval.sh [DEVICE_ID] [DATA_NAME]
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/mnasnet/README_CN.md b/research/cv/mnasnet/README_CN.md
index c511498ad268838a89570702d4a56884b20e801c..2269fae5302090a3ad6e80d60b9d5d5b9f3ba98b 100644
--- a/research/cv/mnasnet/README_CN.md
+++ b/research/cv/mnasnet/README_CN.md
@@ -186,7 +186,7 @@ result: {'Loss': 2.0364865480325163, 'Top_1_Acc': 0.7412459935897436, 'Top_5_Acc
| 璁粌鎬绘椂闂� (8p) | 20.8h |
| 璇勪及鎬绘椂闂� | 1min |
| 鍙傛暟閲� (M) | 61M |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/mnasnet) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/research/cv/mnasnet) |
# 闅忔満鎯呭喌鐨勬弿杩�
@@ -194,4 +194,4 @@ result: {'Loss': 2.0364865480325163, 'Top_1_Acc': 0.7412459935897436, 'Top_5_Acc
# ModelZoo
-璇锋牳瀵瑰畼鏂� [涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
\ No newline at end of file
+璇锋牳瀵瑰畼鏂� [涓婚〉](https://gitee.com/mindspore/models)銆�
\ No newline at end of file
diff --git a/research/cv/mobilenetV3_small_x1_0/README_CN.md b/research/cv/mobilenetV3_small_x1_0/README_CN.md
index 60e793881fd529e066e5fd95dd08a84bfa8a00fd..c0411f57ddca35d76f19b5a54ff6872a7a245a9c 100644
--- a/research/cv/mobilenetV3_small_x1_0/README_CN.md
+++ b/research/cv/mobilenetV3_small_x1_0/README_CN.md
@@ -174,7 +174,7 @@ result: {'Loss': 2.3101649037352554, 'Top_1_Acc': 0.6746546546546547, 'Top_5_Acc
| 璁粌鎬绘椂闂� (8p) | 16.4h |
| 璇勪及鎬绘椂闂� | 1min |
| 鍙傛暟閲� (M) | 36M |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/mobilenetV3_small_x1_0) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/research/cv/mobilenetV3_small_x1_0) |
# 闅忔満鎯呭喌鐨勬弿杩�
@@ -182,4 +182,4 @@ result: {'Loss': 2.3101649037352554, 'Top_1_Acc': 0.6746546546546547, 'Top_5_Acc
# ModelZoo
-璇锋牳瀵瑰畼鏂� [涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
\ No newline at end of file
+璇锋牳瀵瑰畼鏂� [涓婚〉](https://gitee.com/mindspore/models)銆�
\ No newline at end of file
diff --git a/research/cv/ntsnet/README.md b/research/cv/ntsnet/README.md
index f8d0c014d47ee3ccc8e74ca33eb2737b8e3d462b..c81c1c0570dafccb1b6ec576fee2c1afba95b21d 100644
--- a/research/cv/ntsnet/README.md
+++ b/research/cv/ntsnet/README.md
@@ -146,7 +146,7 @@ bash run_train.sh [RANK_TABLE_FILE] [DATA_URL] [TRAIN_URL]
```
- Notes
-1. hccl.json which is specified by RANK_TABLE_FILE is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+1. hccl.json which is specified by RANK_TABLE_FILE is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
2. As for PRETRAINED_MODEL锛宨t should be a trained ResNet50 checkpoint.
### [Training Result](#content)
@@ -213,7 +213,7 @@ python export.py --ckpt_file [CKPT_PATH] --device_target [DEVICE_TARGET] --file_
| Total time | 8pcs: 5.93 hours |
| Parameters | 87.6 |
| Checkpoint for Fine tuning | 333.07M(.ckpt file) |
-| Scripts | [ntsnet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/ntsnet) |
+| Scripts | [ntsnet script](https://gitee.com/mindspore/models/tree/master/research/cv/ntsnet) |
# [Description of Random Situation](#contents)
@@ -221,10 +221,10 @@ We use random seed in train.py and eval.py for weight initialization.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
# FAQ
-First refer to [ModelZoo FAQ](https://gitee.com/mindspore/mindspore/tree/master/model_zoo#FAQ) to find some common public questions.
+First refer to [ModelZoo FAQ](https://gitee.com/mindspore/models#FAQ) to find some common public questions.
- **Q: What to do if memory overflow occurs when using PYNATIVE_MODE锛�** **A**:Memory overflow is usually because PYNATIVE_MODE requires more memory. Setting the batch size to 2 reduces memory consumption and can be used for network training.
diff --git a/research/cv/pointnet2/README.md b/research/cv/pointnet2/README.md
index 4174fba4eefa86f8e982f8130e1088ceb5a0fff0..935c5125e7a8e0ac618aeeb65c06e9d65c5abb43 100644
--- a/research/cv/pointnet2/README.md
+++ b/research/cv/pointnet2/README.md
@@ -142,7 +142,7 @@ bash scripts/run_standalone_train.sh hccl_8p_01234567_127.0.0.1.json modelnet40_
Distributed training requires the creation of an HCCL configuration file in JSON format in advance. For specific
operations, see the instructions
-in [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+in [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
After training, the loss value will be achieved as follows:
@@ -227,4 +227,4 @@ We use random seed in dataset.py, provider.py and pointnet2_utils.py.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/relationnet/README.md b/research/cv/relationnet/README.md
index 7c8c2aaa46846848150cfcd196213e22fce61cfe..3c6d2f682ed75611983c3af05fe27d0304c6598e 100644
--- a/research/cv/relationnet/README.md
+++ b/research/cv/relationnet/README.md
@@ -192,7 +192,7 @@ The ckpt_file parameter is required,
| Speed | 70 ms/episode |
| Total time | 4.5h (8p) |
| Checkpoint for Fine tuning | 875k (.ckpt file) |
-| Scripts | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/relationnet |
+| Scripts | https://gitee.com/mindspore/models/tree/master/research/cv/relationnet |
# [Description of Random Situation](#contents)
@@ -201,4 +201,4 @@ In net_train.py, we set the random.choice inside ```train``` function.
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/renas/Readme.md b/research/cv/renas/Readme.md
index f451afebe35c00f098d3a3ca5b96ed6b0b7d9854..3a862f9876e30d68b41f79aaa9d583df20136ff6 100644
--- a/research/cv/renas/Readme.md
+++ b/research/cv/renas/Readme.md
@@ -119,4 +119,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/resnet50_adv_pruning/Readme.md b/research/cv/resnet50_adv_pruning/Readme.md
index 5ef41b1bfc0fe4a9d455c3a297dc39f6e3b0089d..07e6eac7b310815ef56ddfd0446e81906541a23c 100644
--- a/research/cv/resnet50_adv_pruning/Readme.md
+++ b/research/cv/resnet50_adv_pruning/Readme.md
@@ -129,4 +129,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/resnet50_bam/README_CN.md b/research/cv/resnet50_bam/README_CN.md
index c90c266db09f160e401e43b6b19d97f753743a07..82938674d6d191ba3be7ce2e063048cd33acdbc2 100644
--- a/research/cv/resnet50_bam/README_CN.md
+++ b/research/cv/resnet50_bam/README_CN.md
@@ -92,7 +92,7 @@ resnet50_bam鐨勪綔鑰呮彁鍑轰簡涓€涓畝鍗曚絾鏄湁鏁堢殑Attention妯″瀷鈥斺€擝A
璇烽伒寰互涓嬮摼鎺ヤ腑鐨勮鏄庯細
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.>
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools.>
# 鑴氭湰璇存槑
@@ -246,4 +246,4 @@ resnet50_bam鐨勪綔鑰呮彁鍑轰簡涓€涓畝鍗曚絾鏄湁鏁堢殑Attention妯″瀷鈥斺€擝A
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
\ No newline at end of file
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
\ No newline at end of file
diff --git a/research/cv/resnetv2/README_CN.md b/research/cv/resnetv2/README_CN.md
index 0204991cbf6654e4596f7791bcbb844ce4f6baa3..a71be274aa9b61416ffc25f90ab582051e26b51a 100644
--- a/research/cv/resnetv2/README_CN.md
+++ b/research/cv/resnetv2/README_CN.md
@@ -184,7 +184,7 @@ bash scripts/run_standalone_train.sh [resnetv2_50|resnetv2_101|resnetv2_152] [ci
鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆�
-鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)涓殑璇存槑銆�
+鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)涓殑璇存槑銆�
### GPU澶勭悊鍣ㄧ幆澧冭繍琛�
@@ -313,7 +313,7 @@ bash scripts/run_infer_310.sh [MINDIR_PATH] [DATASET] [DATA_PATH] [DEVICE_ID]
|閫熷害|24.3姣/姝ワ紙8鍗★級 |
|鎬绘椂闀� | 10鍒嗛挓 |
| 寰皟妫€鏌ョ偣 | 188.36M锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/resnetv2) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |
#### ImageNet2012涓婄殑Resnetv2_50
@@ -332,7 +332,7 @@ bash scripts/run_infer_310.sh [MINDIR_PATH] [DATASET] [DATA_PATH] [DEVICE_ID]
| 閫熷害 | 325姣/姝ワ紙8鍗★級 |
| 鎬绘椂闀� | 20.3灏忔椂 |
| 寰皟妫€鏌ョ偣 | 195.9M锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/resnetv2) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/research/cv/resnetv2) |
# 闅忔満鎯呭喌璇存槑
@@ -340,4 +340,4 @@ dataset.py涓缃簡鈥渃reate_dataset鈥濆嚱鏁板唴鐨勭瀛愶紝鍚屾椂杩樹娇鐢�
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/resnext152_64x4d/README.md b/research/cv/resnext152_64x4d/README.md
index f06051c8ba43f4ad3a08d75f9b2d7db907979bd8..bec90b1609f014807ce9c7a953787c44ae7c2ee6 100644
--- a/research/cv/resnext152_64x4d/README.md
+++ b/research/cv/resnext152_64x4d/README.md
@@ -245,4 +245,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/resnext152_64x4d/README_CN.md b/research/cv/resnext152_64x4d/README_CN.md
index 084c409e57493d7ae2e8edf52870e66a56dfb4ba..daa836c1aef8cb660033ac9d6a6f8467d983b88a 100644
--- a/research/cv/resnext152_64x4d/README_CN.md
+++ b/research/cv/resnext152_64x4d/README_CN.md
@@ -249,4 +249,4 @@ dataset.py涓缃簡鈥渃reate_dataset鈥濆嚱鏁板唴鐨勭瀛愶紝鍚屾椂杩樹娇鐢�
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/retinaface/README_CN.md b/research/cv/retinaface/README_CN.md
index be0aecf596bffe5d0d632126488b2d9d6e1fffc6..fd38d58f0f15dca8870a3424eb72026fbedb9b74 100644
--- a/research/cv/retinaface/README_CN.md
+++ b/research/cv/retinaface/README_CN.md
@@ -448,4 +448,4 @@ RetinaFace鍙互浣跨敤ResNet50鎴朚obileNet0.25楠ㄥ共鎻愬彇鍥惧儚鐗瑰緛杩涜妫€
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/retinanet_resnet101/README_CN.md b/research/cv/retinanet_resnet101/README_CN.md
index 852e30a1707867adf4d455db072c36b95f266313..5792cef447477813f3ecc892a85322ebe43c0f94 100644
--- a/research/cv/retinanet_resnet101/README_CN.md
+++ b/research/cv/retinanet_resnet101/README_CN.md
@@ -186,7 +186,7 @@ bash run_distribute_train.sh DEVICE_ID EPOCH_SIZE LR DATASET PRE_TRAINED(optiona
> 娉ㄦ剰:
- RANK_TABLE_FILE鐩稿叧鍙傝€冭祫鏂欒[閾炬帴](https://www.mindspore.cn/docs/programming_guide/zh-CN/master/distributed_training_ascend.html), 鑾峰彇device_ip鏂规硶璇﹁[閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+ RANK_TABLE_FILE鐩稿叧鍙傝€冭祫鏂欒[閾炬帴](https://www.mindspore.cn/docs/programming_guide/zh-CN/master/distributed_training_ascend.html), 鑾峰彇device_ip鏂规硶璇﹁[閾炬帴](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
#### 杩愯
@@ -376,7 +376,7 @@ mAP: 0.36858371862143824
| 鏈€缁堟崯澶� | 0.43 |
| 绮剧‘搴� (8p) | mAP[0.3710] |
| 璁粌鎬绘椂闂� (8p) | 34h50m20s |
-| 鑴氭湰 | [Retianet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/retinanet_resnet101) |
+| 鑴氭湰 | [Retianet script](https://gitee.com/mindspore/models/tree/master/research/cv/retinanet_resnet101) |
#### 鎺ㄧ悊鎬ц兘
@@ -397,10 +397,10 @@ mAP: 0.36858371862143824
# [ModelZoo 涓婚〉](#鍐呭)
-璇锋牳瀵瑰畼鏂� [涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+璇锋牳瀵瑰畼鏂� [涓婚〉](https://gitee.com/mindspore/models).
# FAQ
-浼樺厛鍙傝€僛ModelZoo FAQ](https://gitee.com/mindspore/mindspore/tree/master/model_zoo#FAQ)鏉ユ煡鎵句竴浜涘父瑙佺殑鍏叡闂銆�
+浼樺厛鍙傝€僛ModelZoo FAQ](https://gitee.com/mindspore/models#FAQ)鏉ユ煡鎵句竴浜涘父瑙佺殑鍏叡闂銆�
- **Q: 浣跨敤PYNATIVE_MODE鍙戠敓鍐呭瓨婧㈠嚭鎬庝箞鍔烇紵** **A**锛氬唴瀛樻孩鍑洪€氬父鏄洜涓篜YNATIVE_MODE闇€瑕佹洿澶氱殑鍐呭瓨锛� 灏哹atch size璁剧疆涓�16闄嶄綆鍐呭瓨娑堣€楋紝鍙繘琛岀綉缁滆缁冦€�
diff --git a/research/cv/retinanet_resnet152/README_CN.md b/research/cv/retinanet_resnet152/README_CN.md
index e8cc18cdafc20f1a3855782f220e1ce0f7c6c9d9..6bdf1578da66fbab5bf68f58fcad696b0820a266 100644
--- a/research/cv/retinanet_resnet152/README_CN.md
+++ b/research/cv/retinanet_resnet152/README_CN.md
@@ -185,7 +185,7 @@ bash run_distribute_train.sh DEVICE_ID EPOCH_SIZE LR DATASET PRE_TRAINED(optiona
> 娉ㄦ剰:
- RANK_TABLE_FILE鐩稿叧鍙傝€冭祫鏂欒[閾炬帴](https://www.mindspore.cn/docs/programming_guide/zh-CN/master/distributed_training_ascend.html), 鑾峰彇device_ip鏂规硶璇﹁[閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+ RANK_TABLE_FILE鐩稿叧鍙傝€冭祫鏂欒[閾炬帴](https://www.mindspore.cn/docs/programming_guide/zh-CN/master/distributed_training_ascend.html), 鑾峰彇device_ip鏂规硶璇﹁[閾炬帴](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
#### 杩愯
@@ -374,7 +374,7 @@ mAP: 0.35625723922139957
| 鏈€缁堟崯澶� | 0.69 |
| 绮剧‘搴� (8p) | mAP[0.3571] |
| 璁粌鎬绘椂闂� (8p) | 41h32m20s |
-| 鑴氭湰 | [Retianet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/retinanet_resnet152) |
+| 鑴氭湰 | [Retianet script](https://gitee.com/mindspore/models/tree/master/research/cv/retinanet_resnet152) |
#### 鎺ㄧ悊鎬ц兘
@@ -395,4 +395,4 @@ mAP: 0.35625723922139957
# [ModelZoo 涓婚〉](#鍐呭)
-璇锋牳瀵瑰畼鏂� [涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+璇锋牳瀵瑰畼鏂� [涓婚〉](https://gitee.com/mindspore/models).
diff --git a/research/cv/siamRPN/README_CN.md b/research/cv/siamRPN/README_CN.md
index aa1f8b320c8054b80c9e37776494a70787b03b47..a51a5a4b8416f1eac8bbae31f372add757ee48a4 100644
--- a/research/cv/siamRPN/README_CN.md
+++ b/research/cv/siamRPN/README_CN.md
@@ -161,7 +161,7 @@ Siam-RPN鎻愬嚭浜嗕竴绉嶅熀浜嶳PN鐨勫鐢熺綉缁滅粨鏋勩€傜敱瀛敓瀛愮綉缁滃拰RPN
璇烽伒寰互涓嬮摼鎺ヤ腑鐨勮鏄庯細
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.>
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools.>
- 鍦� ModelArts 杩涜璁粌 (濡傛灉浣犳兂鍦╩odelarts涓婅繍琛岋紝鍙互鍙傝€冧互涓嬫枃妗� [modelarts](https://support.huaweicloud.com/modelarts/))
@@ -239,4 +239,4 @@ Siam-RPN鎻愬嚭浜嗕竴绉嶅熀浜嶳PN鐨勫鐢熺綉缁滅粨鏋勩€傜敱瀛敓瀛愮綉缁滃拰RPN
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/simple_baselines/README_CN.md b/research/cv/simple_baselines/README_CN.md
index 0a829964656f4bed6418152e59943cb02426753c..da74354c69aa9755a0465c49fc54772d1d0cbb4e 100644
--- a/research/cv/simple_baselines/README_CN.md
+++ b/research/cv/simple_baselines/README_CN.md
@@ -72,7 +72,7 @@ simple_baselines鐨勬€讳綋缃戠粶鏋舵瀯濡備笅锛�
- 棰勮缁冩ā鍨�
- 褰撳紑濮嬭缁冧箣鍓嶉渶瑕佽幏鍙杕indspore鍥惧儚缃戠粶棰勮缁冩ā鍨嬶紝鍙€氳繃鍦╗official model zoo](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet)涓繍琛孯esnet璁粌鑴氭湰鏉ヨ幏鍙栨ā鍨嬫潈閲嶆枃浠讹紝棰勮缁冩枃浠跺悕绉颁负resnet50.ckpt銆�
+ 褰撳紑濮嬭缁冧箣鍓嶉渶瑕佽幏鍙杕indspore鍥惧儚缃戠粶棰勮缁冩ā鍨嬶紝鍙€氳繃鍦╗official model zoo](https://gitee.com/mindspore/models/tree/master/official/cv/resnet)涓繍琛孯esnet璁粌鑴氭湰鏉ヨ幏鍙栨ā鍨嬫潈閲嶆枃浠讹紝棰勮缁冩枃浠跺悕绉颁负resnet50.ckpt銆�
- 鏁版嵁闆嗗噯澶�
@@ -260,4 +260,4 @@ dataset.py涓缃簡鈥渃reate_dataset鈥濆嚱鏁板唴鐨勭瀛愶紝鍚屾椂鍦╩odel.py
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/single_path_nas/README_CN.md b/research/cv/single_path_nas/README_CN.md
index 178b763718b6e4f6ebf31fd93d41d3cb62d0228a..53920d81c1901ed262a27caffdeda9432aef4f1f 100644
--- a/research/cv/single_path_nas/README_CN.md
+++ b/research/cv/single_path_nas/README_CN.md
@@ -93,7 +93,7 @@ single-path-nas鐨勪綔鑰呯敤涓€涓�7x7鐨勫ぇ鍗风Н锛屾潵浠ｈ〃3x3銆�5x5鍜�7x7鐨�
璇烽伒寰互涓嬮摼鎺ヤ腑鐨勮鏄庯細
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.>
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools.>
# 鑴氭湰璇存槑
@@ -241,4 +241,4 @@ single-path-nas鐨勪綔鑰呯敤涓€涓�7x7鐨勫ぇ鍗风Н锛屾潵浠ｈ〃3x3銆�5x5鍜�7x7鐨�
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
\ No newline at end of file
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
\ No newline at end of file
diff --git a/research/cv/sknet/README.md b/research/cv/sknet/README.md
index 5110c9db5bbaaa5bcf4de42671c5c1bbb13fc443..65549807e56a101ecabb440651f67597e8c752ed 100644
--- a/research/cv/sknet/README.md
+++ b/research/cv/sknet/README.md
@@ -154,7 +154,7 @@ bash run_standalone_train.sh [DATASET_PATH]
For distributed training, a hccl configuration file with JSON format needs to be created in advance.
-Please follow the instructions in the link [hccn_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+Please follow the instructions in the link [hccn_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
Training result will be stored in the example path, whose folder name begins with "train" or "train_parallel". Under this, you can find checkpoint file together with result like the following in log.
@@ -211,7 +211,7 @@ result: {'top_5_accuracy': 0.9982972756410257, 'top_1_accuracy': 0.9449118589743
| Total time | 179 mins |
| Parameters (M) | 13.2M |
| Checkpoint for Fine tuning | 224M (.ckpt file) |
-| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/sknet) |
+| Scripts | [Link](https://gitee.com/mindspore/models/tree/master/research/cv/sknet) |
### Inference Performance
@@ -233,4 +233,4 @@ In dataset.py, we set the seed inside "create_dataset" function. We also use ran
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/squeezenet/README.md b/research/cv/squeezenet/README.md
index f02f7beaf17344c65efa230e0781023af53bbae5..ced93f7d8a88ca8cdc766939b80a25446d87c9aa 100644
--- a/research/cv/squeezenet/README.md
+++ b/research/cv/squeezenet/README.md
@@ -236,7 +236,7 @@ For more configuration details, please refer the script `config.py`.
For distributed training, a hccl configuration file with JSON format needs to be created in advance.
-Please follow the instructions in the link [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+Please follow the instructions in the link [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
Training result will be stored in the example path, whose folder name begins with "train" or "train_parallel". Under this, you can find checkpoint file together with result like the followings in log.
@@ -688,4 +688,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/squeezenet1_1/README.md b/research/cv/squeezenet1_1/README.md
index beba897264d043224bcdc8c35c575bfb9e544fa6..6f41feb3d21d76638e2ba71507d054b604f34ba9 100644
--- a/research/cv/squeezenet1_1/README.md
+++ b/research/cv/squeezenet1_1/README.md
@@ -54,7 +54,7 @@ Dataset used: [ImageNet2012](http://www.image-net.org/)
# [Environment Requirements](#contents)
- Hardware锛圓scend锛�
- - Prepare hardware environment with Ascend processor. Squeezenet1_1 training on GPU performs is not good now, and it is still in research. See [squeezenet in research](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/squeezenet1_1) to get up-to-date details.
+ - Prepare hardware environment with Ascend processor. Squeezenet1_1 training on GPU performs is not good now, and it is still in research. See [squeezenet in research](https://gitee.com/mindspore/models/tree/master/research/cv/squeezenet1_1) to get up-to-date details.
- Framework
- [MindSpore](https://www.mindspore.cn/install/en)
- For more information, please check the resources below锛�
@@ -158,7 +158,7 @@ checkpoint can be produced in training process and be saved in the folder ./trai
For distributed training, a hccl configuration file with JSON format needs to be created in advance.
-Please follow the instructions in the link [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+Please follow the instructions in the link [hccl_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
Training result will be stored in the example path, whose folder name begins with "train" or "train_parallel". Under this, you can find checkpoint file together with result like the followings in log.
@@ -259,7 +259,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Speed | 8pcs: 17.5 ms/step |
| Total time | 8pcs: 5.2 hours | |
| Checkpoint for Fine tuning | 13.24M (.ckpt file) |
-| Scripts | [squeezenet script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/squeezenet) |
+| Scripts | [squeezenet script](https://gitee.com/mindspore/models/tree/master/official/cv/squeezenet) |
### Inference Performance
@@ -335,4 +335,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/sr_ea/README.md b/research/cv/sr_ea/README.md
index 69f7a8360c41f358460a5b93c1cf2fbfb30f9dfa..95fe60075b08a086201910504cf17b96ed0e209d 100644
--- a/research/cv/sr_ea/README.md
+++ b/research/cv/sr_ea/README.md
@@ -194,7 +194,7 @@ sh scripts/run_distributed.sh [RANK_TABLE_FILE]
Please follow the instructions in the link below:
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>.
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>.
`$RANK_TABLE_FILE` is needed when you are running a distribute task on ascend.
> Or one can run following script for all tasks.
@@ -245,8 +245,8 @@ The Results on super resolution tasks are listed as below.
| Loss Function | L1Loss |
| Output | super resolution image |
| PSNR | 43.35 |
-| Scripts | [sr_ea script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/sr_ea) |
+| Scripts | [sr_ea script](https://gitee.com/mindspore/models/tree/master/research/cv/sr_ea) |
## ModeZoo Homepage
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/ssd_ghostnet/README.md b/research/cv/ssd_ghostnet/README.md
index 1ad22a05487b4fc81551c31edfbda238155d8392..8c36444e53c84c790ac9999acca5f2071bccfeed 100644
--- a/research/cv/ssd_ghostnet/README.md
+++ b/research/cv/ssd_ghostnet/README.md
@@ -222,7 +222,7 @@ We need five or seven parameters for this scripts.
- `DATASET`锛歵he dataset mode for distributed train.
-- `RANK_TABLE_FILE :` the path of [rank_table.json](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools), it is better to use absolute path.
+- `RANK_TABLE_FILE :` the path of [rank_table.json](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools), it is better to use absolute path.
- `PRE_TRAINED :` the path of pretrained checkpoint file, it is better to use absolute path.
diff --git a/research/cv/ssd_mobilenetV2/README.md b/research/cv/ssd_mobilenetV2/README.md
index ccabf9ec8327a53c1bf9f1f55605623c3a20074f..e636fb7f5a5eac3f9b2076a3595839d70ad6b289 100644
--- a/research/cv/ssd_mobilenetV2/README.md
+++ b/research/cv/ssd_mobilenetV2/README.md
@@ -202,7 +202,7 @@ We need five or seven parameters for this scripts.
- `EPOCH_NUM`: epoch num for distributed train.
- `LR`: learning rate init value for distributed train.
- `DATASET`锛歵he dataset mode for distributed train.
-- `RANK_TABLE_FILE :` the path of [rank_table.json](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools), it is better to use absolute path.
+- `RANK_TABLE_FILE :` the path of [rank_table.json](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools), it is better to use absolute path.
- `PRE_TRAINED :` the path of pretrained checkpoint file, it is better to use absolute path.
- `PRE_TRAINED_EPOCH_SIZE :` the epoch num of pretrained.
@@ -349,7 +349,7 @@ mAP: 0.2561487588412723
| Loss Function | Sigmoid Cross Entropy,SmoothL1Loss |
| Speed | 8pcs: 80ms/step |
| Total time | 8pcs: 4.67hours |
-| Scripts | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/ssd_mobilenetV2> |
+| Scripts | <https://gitee.com/mindspore/models/tree/master/research/cv/ssd_mobilenetV2> |
#### Inference Performance
@@ -370,4 +370,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
## [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/ssd_mobilenetV2_FPNlite/README.md b/research/cv/ssd_mobilenetV2_FPNlite/README.md
index 1000599cd5882fefabe2ae4c2042cadbb5f08b4f..65989ac612cd8fb017271b54f79f1e974b8a186e 100644
--- a/research/cv/ssd_mobilenetV2_FPNlite/README.md
+++ b/research/cv/ssd_mobilenetV2_FPNlite/README.md
@@ -206,7 +206,7 @@ We need five or seven parameters for this scripts.
- `EPOCH_NUM`: epoch num for distributed train.
- `LR`: learning rate init value for distributed train.
- `DATASET`锛歵he dataset mode for distributed train.
-- `RANK_TABLE_FILE :` the path of [rank_table.json](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools), it is better to use absolute path.
+- `RANK_TABLE_FILE :` the path of [rank_table.json](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools), it is better to use absolute path.
- `PRE_TRAINED :` the path of pretrained checkpoint file, it is better to use absolute path.
- `PRE_TRAINED_EPOCH_SIZE :` the epoch num of pretrained.
@@ -353,7 +353,7 @@ mAP: 0.2645785822173796
| Loss Function | Sigmoid Cross Entropy,SmoothL1Loss |
| Speed | 8pcs: 130ms/step |
| Total time | 8pcs: 8.2hours |
-| Scripts | <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/ssd_mobilenetV2_FPNlite> |
+| Scripts | <https://gitee.com/mindspore/models/tree/master/research/cv/ssd_mobilenetV2_FPNlite> |
#### Inference Performance
@@ -374,4 +374,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
## [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/ssd_resnet50/README.md b/research/cv/ssd_resnet50/README.md
index 6a9c4bbd6c2b8b1f05b67437b210df30947f1c85..116c1abb008c6260d9d3308dfaf4e364b87dabb2 100644
--- a/research/cv/ssd_resnet50/README.md
+++ b/research/cv/ssd_resnet50/README.md
@@ -220,7 +220,7 @@ We need five or seven parameters for this scripts.
- `EPOCH_NUM`: epoch num for distributed train.
- `LR`: learning rate init value for distributed train.
- `DATASET`锛歵he dataset mode for distributed train.
-- `RANK_TABLE_FILE :` the path of [rank_table.json](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools), it is better to use absolute path.
+- `RANK_TABLE_FILE :` the path of [rank_table.json](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools), it is better to use absolute path.
- `PRE_TRAINED :` the path of pretrained checkpoint file, it is better to use absolute path.
- `PRE_TRAINED_EPOCH_SIZE :` the epoch num of pretrained.
@@ -349,4 +349,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
## [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/ssd_resnet50/README_CN.md b/research/cv/ssd_resnet50/README_CN.md
index ba92664d1e0f142b670df405caeec8fecaaf1419..0f2d4067ef3b6b34559ea91c9b26c6284e2548ea 100644
--- a/research/cv/ssd_resnet50/README_CN.md
+++ b/research/cv/ssd_resnet50/README_CN.md
@@ -179,7 +179,7 @@ bash run_eval.sh [DATASET] [CHECKPOINT_PATH] [DEVICE_ID]
- `EPOCH_NUM`锛氬垎甯冨紡璁粌鐨勮疆娆℃暟銆�
- `LR`锛氬垎甯冨紡璁粌鐨勫涔犵巼鍒濆鍊笺€�
- `DATASET`锛氬垎甯冨紡璁粌鐨勬暟鎹泦妯″紡銆�
-- `RANK_TABLE_FILE`锛歔rank_table.json](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)鐨勮矾寰勩€傛渶濂戒娇鐢ㄧ粷瀵硅矾寰勩€�
+- `RANK_TABLE_FILE`锛歔rank_table.json](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)鐨勮矾寰勩€傛渶濂戒娇鐢ㄧ粷瀵硅矾寰勩€�
- `PRE_TRAINED`锛氶璁粌妫€鏌ョ偣鏂囦欢鐨勮矾寰勩€傛渶濂戒娇鐢ㄧ粷瀵硅矾寰勩€�
- `PRE_TRAINED_EPOCH_SIZE`锛氶璁粌鐨勮疆娆℃暟銆�
@@ -301,4 +301,4 @@ dataset.py涓缃簡鈥渃reate_dataset鈥濆嚱鏁板唴鐨勭瀛愶紝鍚屾椂杩樹娇鐢�
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/stgcn/README_CN.md b/research/cv/stgcn/README_CN.md
index b16519b4f16b9ab9961ffc5354aa847cb073a752..773ce239c9df73a9c8c49fe5ea654651eb73172c 100644
--- a/research/cv/stgcn/README_CN.md
+++ b/research/cv/stgcn/README_CN.md
@@ -134,7 +134,7 @@ BJER4
bash scripts/run_distribute_train.sh train_code_path data_path n_pred graph_conv_type
```
- 8P璁粌鏃堕渶瑕佸皢RANK_TABLE_FILE鏀惧湪scripts鏂囦欢澶逛腑锛孯ANK_TABLE_FILE[鐢熸垚鏂规硶](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)
+ 8P璁粌鏃堕渶瑕佸皢RANK_TABLE_FILE鏀惧湪scripts鏂囦欢澶逛腑锛孯ANK_TABLE_FILE[鐢熸垚鏂规硶](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)
璁粌鏃讹紝璁粌杩囩▼涓殑epch鍜宻tep浠ュ強姝ゆ椂鐨刲oss鍜岀簿纭害浼氬憟鐜板湪缁堢涓婏細
@@ -252,4 +252,4 @@ bash run_infer_310.sh [MINDIR_PATH] [DATASET_PATH] [NEED_PREPROCESS] [DEVICE_TAR
# [ModelZoo 涓婚〉](#contents)
- 璇锋煡鐪嬪畼鏂圭綉绔� [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
\ No newline at end of file
+ 璇锋煡鐪嬪畼鏂圭綉绔� [homepage](https://gitee.com/mindspore/models).
\ No newline at end of file
diff --git a/research/cv/tinynet/README.md b/research/cv/tinynet/README.md
index a05487d19bc3547154b50c96b96e2a64394e882c..f960a7bc41d4e549b9379039ef75a0e38881ccb6 100644
--- a/research/cv/tinynet/README.md
+++ b/research/cv/tinynet/README.md
@@ -155,4 +155,4 @@ We set the seed inside dataset.py. We also use random seed in train.py.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/vgg19/README.md b/research/cv/vgg19/README.md
index ae69d888c421e59c30e5ea7307b75066e63f21aa..167d949b31765071ed277f1a365f792e76138d50 100644
--- a/research/cv/vgg19/README.md
+++ b/research/cv/vgg19/README.md
@@ -105,7 +105,7 @@ python eval.py --config_path=[YAML_CONFIG_PATH] --data_dir=[DATA_PATH] --pre_tr
For distributed training, a hccl configuration file with JSON format needs to be created in advance.
Please follow the instructions in the link below:
-<https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>
+<https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>
- Running on GPU
@@ -554,4 +554,4 @@ In dataset.py, we set the seed inside 鈥渃reate_dataset" function. We also use r
## [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/models/tree/master/).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/vgg19/README_CN.md b/research/cv/vgg19/README_CN.md
index 14196d308961e84753d85e2e983a03456ba387c3..43f665b70a27c9d77be90bd8be812b36f427424c 100644
--- a/research/cv/vgg19/README_CN.md
+++ b/research/cv/vgg19/README_CN.md
@@ -120,7 +120,7 @@ python eval.py --config_path=[YAML_CONFIG_PATH] --data_dir=[DATA_PATH] --pre_tr
鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆�
鍏蜂綋鎿嶄綔锛屽弬瑙侊細
-<https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>
+<https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>
- GPU澶勭悊鍣ㄧ幆澧冭繍琛�
@@ -551,7 +551,7 @@ python export.py --config_path [YMAL_CONFIG_PATH] --ckpt_file [CKPT_PATH] --file
| 閫熷害 | 8鍗★細97.4姣/姝� |
| 鎬绘椂闀� | 8鍗★細6.1灏忔椂 |
| 璋冧紭妫€鏌ョ偣 | 1.1 GB锛�.ckpt 鏂囦欢锛� |
-| 鑴氭湰 |[VGG19](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/vgg19) | |
+| 鑴氭湰 |[VGG19](https://gitee.com/mindspore/models/tree/master/research/cv/vgg19) | |
### 璇勪及鎬ц兘
@@ -572,4 +572,4 @@ dataset.py涓缃簡鈥渃reate_dataset鈥濆嚱鏁板唴鐨勭瀛愶紝鍚屾椂杩樹娇鐢�
## ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models/tree/master/)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/wdsr/README_CN.md b/research/cv/wdsr/README_CN.md
index 40f4538d3dd4bb4aac190e34c09d7434a19c6082..8c9cb7faa51e8fb3d0059b2133eded4031ca74b0 100644
--- a/research/cv/wdsr/README_CN.md
+++ b/research/cv/wdsr/README_CN.md
@@ -274,7 +274,7 @@ FILE_FORMAT 鍙€� ['MINDIR', 'AIR', 'ONNX'], 榛樿['MINDIR']銆�
| 閫熷害 | 8鍗★細绾�130姣/姝� |
| 鎬绘椂闀� | 8鍗★細0.5灏忔椂 |
| 寰皟妫€鏌ョ偣 | 35 MB(.ckpt鏂囦欢) |
-| 鑴氭湰 | [WDSR](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/wdsr) |
+| 鑴氭湰 | [WDSR](https://gitee.com/mindspore/models/tree/master/research/cv/wdsr) |
### 璇勪及鎬ц兘
@@ -294,4 +294,4 @@ FILE_FORMAT 鍙€� ['MINDIR', 'AIR', 'ONNX'], 榛樿['MINDIR']銆�
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/wgan/README_CN.md b/research/cv/wgan/README_CN.md
index bdd9bfa41ba74b3d1b218290cd093711227bc336..487febf6d2df217b145957336f688034fed46b20 100644
--- a/research/cv/wgan/README_CN.md
+++ b/research/cv/wgan/README_CN.md
@@ -298,4 +298,4 @@ bash run_infer_310.sh [MINDIR_PATH] [CONFIG_PATH] [NEED_PREPROCESS] [NIMAGES] [D
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/cv/wideresnet/README_CN.md b/research/cv/wideresnet/README_CN.md
index c8d8b1f2232a3a90ec25848e43c8e9f4d416ebfc..2738e1881e3b124e546fb9fbc74ee5149ce29c82 100644
--- a/research/cv/wideresnet/README_CN.md
+++ b/research/cv/wideresnet/README_CN.md
@@ -190,7 +190,7 @@ WideResNet鐨勬€讳綋缃戠粶鏋舵瀯濡備笅锛歔閾炬帴](https://arxiv.org/abs/1605.0714
鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆�
-鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)涓殑璇存槑銆�
+鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)涓殑璇存槑銆�
璁粌缁撴灉淇濆瓨鍦ㄧず渚嬭矾寰勪腑锛屾枃浠跺す鍚嶇О浠モ€渢rain鈥濇垨鈥渢rain_parallel鈥濆紑澶淬€傛偍鍙湪姝よ矾寰勪笅鐨勬棩蹇椾腑鎵惧埌妫€鏌ョ偣鏂囦欢浠ュ強缁撴灉锛屽涓嬫墍绀恒€�
@@ -313,7 +313,7 @@ bash run_infer_310.sh [MINDIR_PATH] [DATASET_PATH] [DEVICE_ID]
|鎬绘椂闀� | 70鍒嗛挓 |
|鍙傛暟(M) | 52.1 |
| 寰皟妫€鏌ョ偣 | 426.49M锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/wideresnet) |
+| 鑴氭湰 | [閾炬帴](https://gitee.com/mindspore/models/tree/master/research/cv/wideresnet) |
# 闅忔満鎯呭喌璇存槑
@@ -321,10 +321,10 @@ dataset.py涓缃簡鈥渃reate_dataset鈥濆嚱鏁板唴鐨勭瀛愶紝鍚屾椂杩樹娇鐢�
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
# FAQ
-浼樺厛鍙傝€僛ModelZoo FAQ](https://gitee.com/mindspore/mindspore/tree/master/model_zoo#FAQ)鏉ユ煡鎵句竴浜涘父瑙佺殑鍏叡闂銆�
+浼樺厛鍙傝€僛ModelZoo FAQ](https://gitee.com/mindspore/models#FAQ)鏉ユ煡鎵句竴浜涘父瑙佺殑鍏叡闂銆�
- **Q: 浣跨敤PYNATIVE_MODE鍙戠敓鍐呭瓨婧㈠嚭鎬庝箞鍔烇紵** **A**锛氬唴瀛樻孩鍑洪€氬父鏄洜涓篜YNATIVE_MODE闇€瑕佹洿澶氱殑鍐呭瓨锛� 灏哹atch size璁剧疆涓�16闄嶄綆鍐呭瓨娑堣€楋紝鍙繘琛岀綉缁滆缁冦€�
diff --git a/research/cv/yolov3_tiny/README.md b/research/cv/yolov3_tiny/README.md
index 819ee2e85fc12cc0e3db6bb30d8caf4a3b8569a2..6b1b6dabbc5f5e099baf2748cf48371a840c4caf 100644
--- a/research/cv/yolov3_tiny/README.md
+++ b/research/cv/yolov3_tiny/README.md
@@ -409,7 +409,7 @@ YOLOv3-tiny on 118K images(The annotation and data format must be the same as co
| Speed | 1p 130 img/s 8p 980 img/s(shape=640) |
| Total time | 10h (8p) |
| Checkpoint for Fine tuning | 69M (.ckpt file) |
-| Scripts | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/|
+| Scripts | https://gitee.com/mindspore/models/|
### Inference Performance
@@ -433,4 +433,4 @@ In var_init.py, we set seed for weight initialization
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/cv/yolov3_tiny/README_CN.md b/research/cv/yolov3_tiny/README_CN.md
index 07e66838e1ddb4f1ca78526d2c471bb43368f67a..71fa963102581c11acbbeea5cfdec57424be7a3d 100644
--- a/research/cv/yolov3_tiny/README_CN.md
+++ b/research/cv/yolov3_tiny/README_CN.md
@@ -404,7 +404,7 @@ YOLOv3-tiny搴旂敤浜�118000寮犲浘鍍忎笂锛堟爣娉ㄥ拰鏁版嵁鏍煎紡蹇呴』涓嶤OCO 2017
| 閫熷害 | 鍗曞崱锛�130imgs/s; 8鍗★細980imgs/s |
| 鎬绘椂闀� | 8鍗�: 10灏忔椂 |
| 鍙傛暟(M) | 69 |
-| 鑴氭湰 | [YOLOv3_Tiny鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/yolov3_tiny) |
+| 鑴氭湰 | [YOLOv3_Tiny鑴氭湰](https://gitee.com/mindspore/models/tree/master/research/cv/yolov3_tiny) |
### 鎺ㄧ悊鎬ц兘
@@ -426,4 +426,4 @@ YOLOv3-tiny搴旂敤浜�5000寮犲浘鍍忎笂锛堟爣娉ㄥ拰鏁版嵁鏍煎紡蹇呴』涓嶤OCO val 20
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/hpc/deepbsde/README.md b/research/hpc/deepbsde/README.md
index efe5d5af9b7290b22f85c778c86a7b268d4c4760..4d472d1057d55ba34df577cc5ccfb44e4d6551ec 100644
--- a/research/hpc/deepbsde/README.md
+++ b/research/hpc/deepbsde/README.md
@@ -179,4 +179,4 @@ We use random in equation.py锛寃hich can be set seed to fixed randomness.
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https:#gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https:#gitee.com/mindspore/models).
diff --git a/research/hpc/molecular_dynamics/README.md b/research/hpc/molecular_dynamics/README.md
index 7b3c362a4ff5f3b9e69fa1dc1e0570ce0a71eb72..903cc1d59f1fc5e9d1214b72ac9c0a936b28744d 100644
--- a/research/hpc/molecular_dynamics/README.md
+++ b/research/hpc/molecular_dynamics/README.md
@@ -143,5 +143,5 @@ atom_energy: -94.38766 -94.294426 -94.39194 -94.70758 -94.51311 -94.457
## ModelZoo Homepage
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/hpc/ocean_model/README.md b/research/hpc/ocean_model/README.md
index 3d96d8c6465a80438cb1581e79d4b1b846075042..ad349740d95452ced8771f63313c50bc1187897d 100644
--- a/research/hpc/ocean_model/README.md
+++ b/research/hpc/ocean_model/README.md
@@ -93,10 +93,10 @@ Training result will be stored in the current path, whose folder name begins wit
| Outputs | numpy file
| Speed | 17 ms/step
| Total time | 3 mins
-| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/hpc/ocean_model)
+| Scripts | [Link](https://gitee.com/mindspore/models/tree/master/research/hpc/ocean_model)
## Description of Random Situation
## ModelZoo HomePage
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/hpc/pinns/README.md b/research/hpc/pinns/README.md
index c49dbed00b2fa9aab2440cd31fbd7945ec7f251a..9ad24330a6473df29338c137c915125b6f5609a0 100644
--- a/research/hpc/pinns/README.md
+++ b/research/hpc/pinns/README.md
@@ -375,4 +375,4 @@ We use random seed in train.py锛寃hich can be reset in src/config.py.
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/hpc/pinns/README_CN.md b/research/hpc/pinns/README_CN.md
index e6850496115b5c0517c3a328d89e0a7027c28113..d080e0adfd5fb9e8c50116c387f0f92e60152f9c 100644
--- a/research/hpc/pinns/README_CN.md
+++ b/research/hpc/pinns/README_CN.md
@@ -372,4 +372,4 @@ Navier-Stokes鏂圭▼鍦烘櫙
# [ModelZoo涓婚〉](#鐩綍)
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/nlp/DYR/README_CN.md b/research/nlp/DYR/README_CN.md
index 00c84bd1e130f4f785e5c081e908b6ce41ee4bc3..70ae98b7460ddaf89ee4ae7b8ae295017c329014 100644
--- a/research/nlp/DYR/README_CN.md
+++ b/research/nlp/DYR/README_CN.md
@@ -202,4 +202,4 @@ Parameters for optimizer:
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/nlp/atae_lstm/README.md b/research/nlp/atae_lstm/README.md
index 27901d433e5544ff8e301317b6c705385db29fa0..7414fb5a5aa33409de51c56b0138ba316842c715 100644
--- a/research/nlp/atae_lstm/README.md
+++ b/research/nlp/atae_lstm/README.md
@@ -229,4 +229,4 @@ python export.py --existed_ckpt="./train/atae_lstm_max.ckpt"
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/nlp/dscnn/README.md b/research/nlp/dscnn/README.md
index 1bcd333a173c3b47ca0550dba09cf929928f201e..373e90d8a4cccc9a2619c153945d3794c151a881 100644
--- a/research/nlp/dscnn/README.md
+++ b/research/nlp/dscnn/README.md
@@ -457,4 +457,4 @@ In download_process_data.py, we set the seed for split train, val, test set.
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/nlp/gpt2/README_CN.md b/research/nlp/gpt2/README_CN.md
index eaabc9743748d31e853f911183e10bd2e9f72d9e..dc6955a32d9f22f142591026b101534ecdc0d9a4 100644
--- a/research/nlp/gpt2/README_CN.md
+++ b/research/nlp/gpt2/README_CN.md
@@ -1055,4 +1055,4 @@ tensorflow
# ModelZoo涓婚〉
- [閾炬帴](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)
+ [閾炬帴](https://gitee.com/mindspore/models)
diff --git a/research/nlp/ktnet/README_CN.md b/research/nlp/ktnet/README_CN.md
index 0808b141e1585ee97102bfa8e12799eab5ec5495..dd648f3a9771abfc058c461982ffe0657997cb89 100644
--- a/research/nlp/ktnet/README_CN.md
+++ b/research/nlp/ktnet/README_CN.md
@@ -468,4 +468,4 @@ NEED_PREPROCESS涓哄繀閫夐」, 鍦╗y|n]涓彇鍊硷紝琛ㄧず鏁版嵁鏄惁棰勫鐞嗕负b
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/nlp/senta/README_CN.md b/research/nlp/senta/README_CN.md
index 4b70a858d64cbee3bd1557b939de305e532252d2..7be8f4f59803da3b7b1c0d9fbab2d93d24624ea9 100644
--- a/research/nlp/senta/README_CN.md
+++ b/research/nlp/senta/README_CN.md
@@ -309,10 +309,10 @@ bash run_infer_310.sh [MINDIR_PATH] [DATA_FILE_PATH] [NEED_PREPROCESS] [DEVICE_I
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
# FAQ
-浼樺厛鍙傝€僛ModelZoo FAQ](https://gitee.com/mindspore/mindspore/tree/master/model_zoo#FAQ)鏉ユ煡鎵句竴浜涘父瑙佺殑鍏叡闂銆�
+浼樺厛鍙傝€僛ModelZoo FAQ](https://gitee.com/mindspore/models#FAQ)鏉ユ煡鎵句竴浜涘父瑙佺殑鍏叡闂銆�
- **Q: 浣跨敤PYNATIVE_MODE鍙戠敓鍐呭瓨婧㈠嚭鎬庝箞鍔烇紵** **A**锛氬唴瀛樻孩鍑洪€氬父鏄洜涓篜YNATIVE_MODE闇€瑕佹洿澶氱殑鍐呭瓨锛� 浼犲叆璁粌鍙傛暟 --batch_size 18 灏� batch size璁剧疆涓� 18 闄嶄綆鍐呭瓨娑堣€楋紝鍙繘琛岀綉缁滆缁冦€�
diff --git a/research/nlp/seq2seq/README_CN.md b/research/nlp/seq2seq/README_CN.md
index 7f2a8cd7f51a075e54c2ce4f792d7a58ac5de25e..01e3fae3f5061331604fbc264f4ad31654d8b29f 100644
--- a/research/nlp/seq2seq/README_CN.md
+++ b/research/nlp/seq2seq/README_CN.md
@@ -75,7 +75,7 @@ bash wmt14_en_fr.sh
璇烽伒寰互涓嬮摼鎺ヤ腑鐨勮鏄庯細
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools.>
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools.>
# 鑴氭湰璇存槑
@@ -251,4 +251,4 @@ bash wmt14_en_fr.sh
# ModelZoo涓婚〉
- 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+ 璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/nlp/skipgram/README_CN.md b/research/nlp/skipgram/README_CN.md
index 08bea691a7543a009e7a876fa787a271f505de77..5f1a3d30d66e93f7b0b3d0694f7eac01c2a8e807 100644
--- a/research/nlp/skipgram/README_CN.md
+++ b/research/nlp/skipgram/README_CN.md
@@ -104,7 +104,7 @@ bash scripts/create_mindrecord.sh [TRAIN_DATA_DIR]
鍒嗗竷寮忚缁冮渶瑕佹彁鍓嶅垱寤篔SON鏍煎紡鐨凥CCL閰嶇疆鏂囦欢銆�
-鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools)涓殑璇存槑銆�
+鍏蜂綋鎿嶄綔锛屽弬瑙乕hccn_tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools)涓殑璇存槑銆�
# 鑴氭湰璇存槑
@@ -255,7 +255,7 @@ epoch: 1 step: 3000, loss is 2.7949429
| 鎬绘椂闀� | 249 min (1鍗�); 101 min (8鍗�) | 675 min
| 鍙傛暟(M) | 146.2 | 146.2 |
| 寰皟妫€鏌ョ偣 | 497M锛�.ckpt鏂囦欢锛� | 497M锛�.ckpt鏂囦欢锛� |
-| 鑴氭湰 | [Skip-gram鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/nlp/skipgram) | [Skip-gram鑴氭湰](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/nlp/skipgram) |
+| 鑴氭湰 | [Skip-gram鑴氭湰](https://gitee.com/mindspore/models/tree/master/research/nlp/skipgram) | [Skip-gram鑴氭湰](https://gitee.com/mindspore/models/tree/master/research/nlp/skipgram) |
# 闅忔満鎯呭喌璇存槑
@@ -263,4 +263,4 @@ train.py涓缃簡闅忔満绉嶅瓙锛屼互閬垮厤璁粌杩囩▼涓殑闅忔満鎬с€�
# ModelZoo涓婚〉
-璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)銆�
+璇锋祻瑙堝畼缃慬涓婚〉](https://gitee.com/mindspore/models)銆�
diff --git a/research/nlp/ternarybert/README.md b/research/nlp/ternarybert/README.md
index 05d9c88d881db9bd17ea23170cd57b8540660175..8698e0723e7e5f8d8cbe567ded06427a3dedebd4 100644
--- a/research/nlp/ternarybert/README.md
+++ b/research/nlp/ternarybert/README.md
@@ -309,4 +309,4 @@ In config.py, we set the hidden_dropout_prob, attention_pros_dropout_prob and cl
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/nlp/textrcnn/readme.md b/research/nlp/textrcnn/readme.md
index cc7d52db0c39b018752165f484135345fa0f5989..283c00ed5217288e5f645daaf5ea6cdfd9386f38 100644
--- a/research/nlp/textrcnn/readme.md
+++ b/research/nlp/textrcnn/readme.md
@@ -265,4 +265,4 @@ Inference result is saved in current path, you can find result like this in acc.
## [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/nlp/tprr/README.md b/research/nlp/tprr/README.md
index f724056e714886a34d83faed76f06aa502d4db99..3f0310c23933d80a4ea1820ef5cb71c0a07b6b62 100644
--- a/research/nlp/tprr/README.md
+++ b/research/nlp/tprr/README.md
@@ -222,4 +222,4 @@ No random situation for evaluation.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](http://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](http://gitee.com/mindspore/models).
diff --git a/research/recommend/Fat-DeepFFM/README.md b/research/recommend/Fat-DeepFFM/README.md
index 95f456819091d172bff9cc42733c7e22e2ee4aaf..b87a870356bc651c871508989924ce32885744a4 100644
--- a/research/recommend/Fat-DeepFFM/README.md
+++ b/research/recommend/Fat-DeepFFM/README.md
@@ -95,7 +95,7 @@ Fat - DeepFFM consists of three parts. The FFM component is a factorization mach
Please follow the instructions in the link below:
- [hccl tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+ [hccl tools](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools).
# [Script Description](#contents)
@@ -277,7 +277,7 @@ Inference result is saved in current path, you can find result like this in acc.
| Total time | 1pc: 4 hours; |
| Parameters (M) | 560.34 |
| Checkpoint for Fine tuning | 87.65M (.ckpt file) |
-| Scripts | [deepfm script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/recommend/Fat-DeepFFM) |
+| Scripts | [deepfm script](https://gitee.com/mindspore/models/tree/master/research/recommend/Fat-DeepFFM) |
### Inference Performance
@@ -299,4 +299,4 @@ We set the random seed before training in train.py.
# [ModelZoo Homepage](#contents)
-Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/recommend/autodis/README.md b/research/recommend/autodis/README.md
index c246fbc8d14ba07d382a53affc22c1fa31d694f5..9eb0abf25b046fe0bed711807d513ac12536d25f 100644
--- a/research/recommend/autodis/README.md
+++ b/research/recommend/autodis/README.md
@@ -78,7 +78,7 @@ After installing MindSpore via the official website, you can start training and
Please follow the instructions in the link below:
- <https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools>.
+ <https://gitee.com/mindspore/models/tree/master/utils/hccl_tools>.
- running on ModelArts
@@ -304,7 +304,7 @@ Inference result is saved in current path, you can find result in acc.log file.
| Total time | 1pc: 90 mins; |
| Parameters (M) | 16.5 |
| Checkpoint for Fine tuning | 191M (.ckpt file) |
-| Scripts | [AutoDis script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/recommend/autodis) |
+| Scripts | [AutoDis script](https://gitee.com/mindspore/models/tree/master/research/recommend/autodis) |
### Inference Performance
@@ -326,4 +326,4 @@ We set the random seed before training in train.py.
# [ModelZoo Homepage](#contents)
- Please check the official [homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+ Please check the official [homepage](https://gitee.com/mindspore/models).
diff --git a/research/rl/ldp_linucb/README.md b/research/rl/ldp_linucb/README.md
index d0eea8a70f4300b0a45a8b57ce436d388118504e..74dd011e1b293cebc620b5d601c38e99ea27a9d8 100644
--- a/research/rl/ldp_linucb/README.md
+++ b/research/rl/ldp_linucb/README.md
@@ -129,4 +129,4 @@ In `train_eval.py`, we randomly sample a user at each round. We also add Gaussia
# [ModelZoo Homepage](#contents)
Please check the official
-[homepage](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
+[homepage](https://gitee.com/mindspore/models).
diff --git a/utils/ascend_distributed_launcher/README.md b/utils/ascend_distributed_launcher/README.md
index 45ae72a271c6116426b4d88d0e2b9ebdd0c9226d..fa2a8d130f29d3242aca25125bc01600917414cc 100644
--- a/utils/ascend_distributed_launcher/README.md
+++ b/utils/ascend_distributed_launcher/README.md
@@ -41,7 +41,7 @@ log file dir: ./LOG6/log.txt
## Note
-1. Note that `hccl_2p_56_x.x.x.x.json` can use [hccl_tools.py](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools) to generate.
+1. Note that `hccl_2p_56_x.x.x.x.json` can use [hccl_tools.py](https://gitee.com/mindspore/models/tree/master/utils/hccl_tools) to generate.
2. For hyper parameter, please note that you should customize the scripts `hyper_parameter_config.ini`. Please note that these two hyper parameters are not allowed to be configured here:
- device_id