diff --git a/README.md b/README.md index 9f4e4e9884a479c5ce61a45933f50abb7b9807c6..e2d10efaed0fefc7cfaca91f862378c91c032621 100644 --- a/README.md +++ b/README.md @@ -75,7 +75,7 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, | Computer Vision (CV) | Text Detection | [PSENet](https://gitee.com/mindspore/models/tree/master/official/cv/psenet) | ✅ | | | | Computer Vision (CV) | Text Recognition | [CNN+CTC](https://gitee.com/mindspore/models/tree/master/official/cv/cnnctc) | ✅ | | | | Computer Vision (CV) | Semantic Segmentation | [DeepLabV3](https://gitee.com/mindspore/models/tree/master/official/cv/deeplabv3) | ✅ | | ✅ | -| Computer Vision (CV) | Semantic Segmentation | [DeepLabV3+](https://gitee.com/mindspore/models/tree/master/official/cv/deeplabv3plus) | ✅ | | | +| Computer Vision (CV) | Semantic Segmentation | [DeepLabV3+](https://gitee.com/mindspore/models/tree/master/research/cv/deeplabv3plus) | ✅ | | | | Computer Vision (CV) | Semantic Segmentation | [U-Net2D (Medical)](https://gitee.com/mindspore/models/tree/master/official/cv/unet) | ✅ | | | | Computer Vision (CV) | Semantic Segmentation | [U-Net3D (Medical)](https://gitee.com/mindspore/models/tree/master/official/cv/unet3d) | ✅ | | | | Computer Vision (CV) | Semantic Segmentation | [U-Net++](https://gitee.com/mindspore/models/tree/master/official/cv/unet) | ✅ | | | @@ -147,8 +147,8 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework, | Computer Vision (CV) | Image Classification |[fishnet99](https://gitee.com/mindspore/models/tree/master/research/cv/fishnet99) | ✅ | | | | Computer Vision (CV) | Image Classification |[GENET](https://gitee.com/mindspore/models/tree/master/research/cv/GENet_Res50) | ✅ | | | | Computer Vision (CV) | Image Classification |[GhostNet](https://gitee.com/mindspore/models/tree/master/research/cv/ghostnet) | ✅ | | | -| Computer Vision (CV) | Image Classification |[Glore_res200](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res200) | ✅ | | | -| Computer Vision (CV) | Image Classification |[Glore_res50](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res50) | ✅ | | | +| Computer Vision (CV) | Image Classification |[Glore_res200](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res) | ✅ | | | +| Computer Vision (CV) | Image Classification |[Glore_res50](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res) | ✅ | | | | Computer Vision (CV) | Image Classification |[HarDNet](https://gitee.com/mindspore/models/tree/master/research/cv/hardnet) | ✅ | | | | Computer Vision (CV) | Image Classification |[HourNAS](https://gitee.com/mindspore/models/tree/master/research/cv/HourNAS) | ✅ | | | | Computer Vision (CV) | Image Classification |[HRNetW48-cls](https://gitee.com/mindspore/models/tree/master/research/cv/HRNetW48_cls) | ✅ | | | diff --git a/README_CN.md b/README_CN.md index effed9e0cc89d83a90ec7fb369ce718c9302a751..92cb579daf7523ee270b5f69fed7aef4ec4ad5c3 100644 --- a/README_CN.md +++ b/README_CN.md @@ -75,7 +75,7 @@ | 计算机视觉(CV) | 文本检测(Text Detection) | [PSENet](https://gitee.com/mindspore/models/tree/master/official/cv/psenet) | ✅ | | | | 计算机视觉(CV) | 文本识别(Text Recognition) | [CNN+CTC](https://gitee.com/mindspore/models/tree/master/official/cv/cnnctc) | ✅ | | | | 计算机视觉(CV) | 语义分割(Semantic Segmentation) | [DeepLabV3](https://gitee.com/mindspore/models/tree/master/official/cv/deeplabv3) | ✅ | | ✅ | -| 计算机视觉(CV) | 语义分割(Semantic Segmentation) | [DeepLabV3+](https://gitee.com/mindspore/models/tree/master/official/cv/deeplabv3plus) | ✅ | | | +| 计算机视觉(CV) | 语义分割(Semantic Segmentation) | [DeepLabV3+](https://gitee.com/mindspore/models/tree/master/research/cv/deeplabv3plus) | ✅ | | | | 计算机视觉(CV) | 语义分割(Semantic Segmentation) | [U-Net2D (Medical)](https://gitee.com/mindspore/models/tree/master/official/cv/unet) | ✅ | | | | 计算机视觉(CV) | 语义分割(Semantic Segmentation) | [U-Net3D (Medical)](https://gitee.com/mindspore/models/tree/master/official/cv/unet3d) | ✅ | | | | 计算机视觉(CV) | 语义分割(Semantic Segmentation) | [U-Net++](https://gitee.com/mindspore/models/tree/master/official/cv/unet) | ✅ | | | @@ -147,8 +147,8 @@ | 计算机视觉(CV) | 图像分类(Image Classification) |[fishnet99](https://gitee.com/mindspore/models/tree/master/research/cv/fishnet99) | ✅ | | | | 计算机视觉(CV) | 图像分类(Image Classification) |[GENET](https://gitee.com/mindspore/models/tree/master/research/cv/GENet_Res50) | ✅ | | | | 计算机视觉(CV) | 图像分类(Image Classification) |[GhostNet](https://gitee.com/mindspore/models/tree/master/research/cv/ghostnet) | ✅ | | | -| 计算机视觉(CV) | 图像分类(Image Classification) |[Glore_res200](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res200) | ✅ | | | -| 计算机视觉(CV) | 图像分类(Image Classification) |[Glore_res50](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res50) | ✅ | | | +| 计算机视觉(CV) | 图像分类(Image Classification) |[Glore_res200](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res) | ✅ | | | +| 计算机视觉(CV) | 图像分类(Image Classification) |[Glore_res50](https://gitee.com/mindspore/models/tree/master/research/cv/glore_res) | ✅ | | | | 计算机视觉(CV) | 图像分类(Image Classification) |[HarDNet](https://gitee.com/mindspore/models/tree/master/research/cv/hardnet) | ✅ | | | | 计算机视觉(CV) | 图像分类(Image Classification) |[HourNAS](https://gitee.com/mindspore/models/tree/master/research/cv/HourNAS) | ✅ | | | | 计算机视觉(CV) | 图像分类(Image Classification) |[HRNetW48-cls](https://gitee.com/mindspore/models/tree/master/research/cv/HRNetW48_cls) | ✅ | | | diff --git a/community/cv/snn/README.md b/community/cv/snn/README.md index 962b59398f5d2feffa23966e42fcc72dcf768a91..11b575c134b9a913e203183cdaa30ef32ca50668 100644 --- a/community/cv/snn/README.md +++ b/community/cv/snn/README.md @@ -287,7 +287,7 @@ result: {'acc': 59.5400 %} ckpt=~/snn/train/output/checkpoint/lenet-5_250.ckpt | Total time | 7 mins | | Checkpoint for Fine tuning | 1.3M (.ckpt file) | | Accuracy | 59.54% | -| config | [Link](https://gitee.com/mindspore/models/community/cv/snn/config)| +| config | [Link](https://gitee.com/mindspore/models/tree/master/community/cv/snn/config)| # [Description of Random Situation](#contents)