diff --git a/.jenkins/check/config/filter_cpplint.txt b/.jenkins/check/config/filter_cpplint.txt
index f811161ea4789bfa5e6a6357e760dab7cec4d7c4..09420b5198f640e75374a91b860fda1cd5f3451a 100644
--- a/.jenkins/check/config/filter_cpplint.txt
+++ b/.jenkins/check/config/filter_cpplint.txt
@@ -45,3 +45,6 @@
"models/official/cv/squeezenet/infer/mxbase/src/squeezenetResidual.h" "runtime/references"
"models/official/cv/squeezenet/infer/mxbase/src/main.cpp" "runtime/references"
+"models/official/cv/posenet/infer/mxbase/src/Posenet.h" "runtime/references"
+"models/official/cv/posenet/infer/mxbase/src/Posenet.cpp" "runtime/references"
+"models/official/cv/posenet/infer/mxbase/src/main.cpp" "runtime/references"
\ No newline at end of file
diff --git a/official/cv/posenet/infer/README.md b/official/cv/posenet/infer/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..a8d1dbccc0b686461932343270e37e921c18b223
--- /dev/null
+++ b/official/cv/posenet/infer/README.md
@@ -0,0 +1,117 @@
+# 鎺ㄧ悊
+
+## 妯″瀷杞崲
+
+1. 鍑嗗妯″瀷鏂囦欢銆�
+
+ AIR妯″瀷涓哄湪鏄囪吘910鏈嶅姟鍣ㄤ笂瀵煎嚭鐨勬ā鍨嬶紝瀵煎嚭AIR妯″瀷鐨勮缁嗘楠よ鍙傝鈥滄ā鍨嬭缁冣€濄€�
+
+2. 鎵ц浠ヤ笅鍛戒护锛岃繘琛屾ā鍨嬭浆鎹€€�
+
+ 杞崲璇︾粏淇℃伅鍙煡鐪嬭浆鎹㈣剼鏈拰瀵瑰簲鐨凙IPP閰嶇疆鏂囦欢锛岃浆鎹㈠懡浠ゅ涓嬨€�
+
+ **bash convert/convert_om.sh** *air_path* *aipp_cfg_path* *om_path*
+
+ | 鍙傛暟 | 璇存槑 |
+ | ------------- | ------------------------------------------------- |
+ | air_path | 杞崲鑴氭湰AIR鏂囦欢璺緞銆� |
+ | aipp_cfg_path | AIPP閰嶇疆鏂囦欢璺緞銆� |
+ | om_path | 鐢熸垚鐨凮M鏂囦欢鍚嶏紝杞崲鑴氭湰浼氬湪姝ゅ熀纭€涓婃坊鍔�.om鍚庣紑銆� |
+
+ 杞崲绀轰緥濡備笅鎵€绀恒€�
+
+ ```bash
+
+ # 杞崲妯″瀷
+ bash convert/convert_om.sh xxx/posenet.air convert/aipp.cfg posenet
+
+ ```
+
+3. 灏嗚浆鎹㈠ソ鐨勬ā鍨嬬Щ鍔ㄥ埌瀛樻斁妯″瀷鐨勭洰褰曚笅銆�
+
+ ```bash
+
+ # 绉诲姩妯″瀷
+ mv posenet.om data/model/
+
+ ```
+
+## mxBase鎺ㄧ悊
+
+1. 缂栬瘧宸ョ▼銆�
+
+ 鐩墠mxBase鎺ㄧ悊浠呭疄鐜颁簡鍩轰簬DVPP鏂瑰紡鎺ㄧ悊銆�
+
+ ```bash
+
+ cd xxx/infer/mxbase
+ bash build.sh
+
+ ```
+
+2. 锛堝彲閫夛級淇敼閰嶇疆鏂囦欢銆�
+
+ 鍙牴鎹疄闄呮儏鍐典慨鏀癸紝閰嶇疆鏂囦欢浣嶄簬鈥渕xbase/src/main.cpp鈥濅腑锛屽彲淇敼鍙傛暟濡備笅銆�
+
+```c++
+
+namespace {
+const uint32_t DEVICE_ID = 0; // 鎸囧畾璁惧ID锛岄粯璁や负0,鍙牴鎹疄闄呮儏鍐佃皟鏁�
+std::string RESULT_PATH = "../data/mx_result/"; // 鎺ㄧ悊缁撴灉淇濆瓨璺緞
+} // namespace
+...
+
+```
+
+3. 杩愯鎺ㄧ悊鏈嶅姟銆�
+
+ 杩愯鎺ㄧ悊鏈嶅姟锛堢‘淇濅綘鐨勮緭鍑鸿矾寰勫瓨鍦紝鍚﹀垯浼氭姤閿欙級銆�
+ **./build/midas_mindspore** *om_path* *img_path* *dataset_name*
+ | 鍙傛暟 | 璇存槑 |
+ | ---------- | ------------------------------ |
+ | om_path | om瀛樻斁璺緞銆傚锛氣€�../data/model/posenet.om鈥濄€� |
+ | img_path | 鎺ㄧ悊鍥剧墖璺緞銆傚锛氣€�../dataset/KingsCollege/鈥濄€� |
+ | dataset_name | 鎺ㄧ悊鏁版嵁闆嗗悕绉般€傚锛氣€渟eq2鈥濄€� |
+
+4. 瑙傚療缁撴灉銆�
+ 鎺ㄧ悊缁撴灉浠in鏍煎紡淇濆瓨锛岃矾寰勪负鈥�./result_Files/鈥�.
+
+## MindX SDK鎺ㄧ悊
+
+1. 锛堝彲閫夛級淇敼閰嶇疆鏂囦欢銆�
+
+ 1. 鍙牴鎹疄闄呮儏鍐典慨鏀筽ipeline鏂囦欢銆�
+
+ ```python
+
+ 鈹溾攢鈹€ config
+ 鈹� 鈹溾攢鈹€ config.py
+ 鈹� 鈹斺攢鈹€ posenet.pipeline # PIPELINE鏂囦欢
+
+ ```
+
+2. 妯″瀷鎺ㄧ悊銆�
+
+ 1. 鎵ц鎺ㄧ悊銆�
+
+ 鍒囨崲鍒皊dk鐩綍涓嬶紝鎵ц鎺ㄧ悊鑴氭湰銆�
+ **python3.7 main.py** *--img_path*
+ | 鍙傛暟 | 璇存槑 |
+ | ----------- | ------------------------------------- |
+ | img_path | 鎺ㄧ悊鍥剧墖璺緞銆傚锛氣€�../dataset/KingsCollege鈥濄€� |
+
+3. 鎵ц绮惧害娴嬭瘯銆�
+ 鎺ㄧ悊绮惧害鑴氭湰瀛樻斁鍦�"sdk/eval"鐩綍涓嬨€備繚瀛樹负acc.log鏂囦欢,鑴氭湰鎺ュ彈1涓弬鏁帮紝渚濇鏄暟鎹泦璺緞銆傝剼鏈ず渚嬪涓嬶細
+
+ ```python
+ python eval_by_sdk.py --result_path ../infer_result >acc.log
+ ```
+
+4. 鏌ョ湅鎬ц兘缁撴灉銆�
+ 鎬ц兘缁撴灉濡備笅锛�
+
+ ```bash
+
+ Median error 1.8816218573685832 m and 4.192690626738049 degrees.
+
+ ```
diff --git a/official/cv/posenet/infer/convert/aipp.cfg b/official/cv/posenet/infer/convert/aipp.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..7a64c181d5b82bba102eeecab023a9cff961647a
--- /dev/null
+++ b/official/cv/posenet/infer/convert/aipp.cfg
@@ -0,0 +1,39 @@
+aipp_op {
+ aipp_mode : static
+ input_format : RGB888_U8
+ related_input_rank : 0
+
+ src_image_size_w: 224
+ src_image_size_h: 456
+
+ crop: true
+ load_start_pos_w: 0
+ load_start_pos_h: 116
+ crop_size_w: 224
+ crop_size_h: 224
+
+ csc_switch : false
+ rbuv_swap_switch : true
+ matrix_r0c0 : 256
+ matrix_r0c1 : 0
+ matrix_r0c2 : 359
+ matrix_r1c0 : 256
+ matrix_r1c1 : -88
+ matrix_r1c2 : -183
+ matrix_r2c0 : 256
+ matrix_r2c1 : 454
+ matrix_r2c2 : 0
+ input_bias_0 : 0
+ input_bias_1 : 128
+ input_bias_2 : 128
+
+ mean_chn_0 : 0
+ mean_chn_1 : 0
+ mean_chn_2 : 0
+ min_chn_0 : 123.675
+ min_chn_1 : 116.28
+ min_chn_2 : 103.53
+ var_reci_chn_0 : 0.0171247538316637
+ var_reci_chn_1 : 0.0175070028011204
+ var_reci_chn_2 : 0.0174291938997821
+}
diff --git a/official/cv/posenet/infer/convert/convert_om.sh b/official/cv/posenet/infer/convert/convert_om.sh
new file mode 100644
index 0000000000000000000000000000000000000000..6848e24222705cedb478e68da58169f080ecfd9a
--- /dev/null
+++ b/official/cv/posenet/infer/convert/convert_om.sh
@@ -0,0 +1,45 @@
+#!/bin/bash
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+
+# The number of parameters must be 3.
+if [ $# -ne 3 ]
+then
+ echo "Wrong parameter format."
+ echo "Usage:"
+ echo " bash $0 [INPUT_AIR_PATH] [AIPP_PATH] [OUTPUT_OM_PATH_NAME]"
+ echo "Example: "
+ echo " bash convert_om.sh xxx.air ./aipp.cfg xx"
+
+ exit 1
+fi
+
+# The model path to be converted
+model_path=$1
+# The Aipp configuration file path
+aipp_cfg_file=$2
+# The name of the generated model
+output_model_name=$3
+
+atc \
+--model=$model_path \
+--framework=1 \
+--output=$output_model_name \
+--input_format=NCHW \
+--input_shape="x:1,3,224,224" \
+--enable_small_channel=1 \
+--log=error \
+--soc_version=Ascend310 \
+--insert_op_conf=$aipp_cfg_file
diff --git a/official/cv/posenet/infer/data/config/config.py b/official/cv/posenet/infer/data/config/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..e8d5a44bc3b9df2a3f90c6e1ae62c9a3534b8d72
--- /dev/null
+++ b/official/cv/posenet/infer/data/config/config.py
@@ -0,0 +1,25 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+
+
+STREAM_NAME = "im_posenet"
+MODEL_WIDTH = 224
+MODEL_HEIGHT = 224
+
+INFER_TIMEOUT = 100000
+
+TENSOR_DTYPE_FLOAT32 = 0
+TENSOR_DTYPE_FLOAT16 = 1
+TENSOR_DTYPE_INT8 = 2
diff --git a/official/cv/posenet/infer/data/config/posenet.pipeline b/official/cv/posenet/infer/data/config/posenet.pipeline
new file mode 100644
index 0000000000000000000000000000000000000000..5b6dc8faeb047688ce705f10eae1df972f0976d4
--- /dev/null
+++ b/official/cv/posenet/infer/data/config/posenet.pipeline
@@ -0,0 +1,44 @@
+{
+ "im_posenet": {
+ "stream_config": {
+ "deviceId": "0"
+ },
+ "appsrc0": {
+ "props": {
+ "blocksize": "409600"
+ },
+ "factory": "appsrc",
+ "next": "mxpi_imageresize0"
+ },
+ "mxpi_imageresize0": {
+ "props": {
+ "dataSource": "appsrc0",
+ "handleMethod": "opencv",
+ "resizeType": "Resizer_Stretch",
+ "resizeHeight": "456",
+ "resizeWidth": "224"
+ },
+ "factory": "mxpi_imageresize",
+ "next": "mxpi_modelinfer0"
+ },
+ "mxpi_modelinfer0": {
+ "props": {
+ "dataSource": "mxpi_imageresize0",
+ "modelPath": "../convert/posenet.om",
+ "outputDeviceId": "-1"
+ },
+ "factory": "mxpi_modelinfer",
+ "next": "mxpi_dataserialize0"
+ },
+ "mxpi_dataserialize0": {
+ "props": {
+ "outputDataKeys": "mxpi_modelinfer0"
+ },
+ "factory": "mxpi_dataserialize",
+ "next": "appsink0"
+ },
+ "appsink0": {
+ "factory": "appsink"
+ }
+ }
+}
diff --git a/official/cv/posenet/infer/dataset_test.txt b/official/cv/posenet/infer/dataset_test.txt
new file mode 100644
index 0000000000000000000000000000000000000000..37128eb31b5bc1cd30e529737feceb53725b81dd
--- /dev/null
+++ b/official/cv/posenet/infer/dataset_test.txt
@@ -0,0 +1,346 @@
+Visual Landmark Dataset V1
+ImageFile, Camera Position [X Y Z W P Q R]
+
+seq7/frame00030.png -20.134839 -16.641770 1.735459 0.672315 0.574745 -0.296687 0.360053
+seq7/frame00029.png -20.932895 -16.398778 1.587640 0.649817 0.579078 -0.314630 0.378702
+seq7/frame00032.png -18.625600 -17.393665 1.836093 0.658770 0.575333 -0.314400 0.369009
+seq7/frame00033.png -17.857495 -17.568780 1.790984 0.656993 0.584342 -0.320180 0.352689
+seq7/frame00034.png -17.040426 -17.714711 1.846034 0.657814 0.577350 -0.331544 0.352173
+seq7/frame00035.png -16.414970 -18.002380 1.733040 0.665271 0.590037 -0.314774 0.331945
+seq7/frame00028.png -21.519864 -15.970470 1.733840 0.638432 0.556592 -0.337607 0.410649
+seq7/frame00027.png -22.258832 -15.582319 1.699754 0.630068 0.565083 -0.346911 0.404163
+seq7/frame00031.png -19.509803 -17.016859 1.828394 0.680741 0.591615 -0.263813 0.342030
+seq7/frame00036.png -15.492117 -18.038837 2.012505 0.676508 0.580960 -0.310246 0.329500
+seq7/frame00037.png -14.823916 -18.303939 1.743378 0.685468 0.575526 -0.292651 0.336540
+seq7/frame00038.png -13.902669 -18.223222 1.869704 0.676583 0.571875 -0.308713 0.346252
+seq7/frame00039.png -13.182436 -18.442966 1.724784 0.678307 0.569025 -0.308146 0.348075
+seq7/frame00040.png -12.339218 -18.478848 1.774631 0.677755 0.562410 -0.318602 0.350479
+seq7/frame00041.png -11.531299 -18.548329 1.807577 0.685505 0.565523 -0.301249 0.345710
+seq7/frame00042.png -10.703305 -18.439226 1.876607 0.677126 0.569889 -0.305359 0.351403
+seq7/frame00043.png -9.931183 -18.680199 1.687524 0.690301 0.581122 -0.291632 0.317383
+seq7/frame00044.png -9.085261 -18.609865 1.823413 0.692639 0.575331 -0.284477 0.329117
+seq7/frame00045.png -8.413352 -18.817093 1.798918 0.708845 0.584995 -0.259047 0.297008
+seq7/frame00046.png -7.603774 -18.817994 1.954586 0.717915 0.575522 -0.253223 0.298750
+seq7/frame00047.png -6.843852 -19.194916 1.752180 0.718287 0.580690 -0.242047 0.297111
+seq7/frame00048.png -6.092491 -19.389024 1.980602 0.727145 0.579574 -0.234742 0.283285
+seq7/frame00049.png -5.386179 -19.751707 1.851691 0.723023 0.592302 -0.224914 0.275372
+seq7/frame00050.png -4.598479 -20.011251 1.890012 0.725292 0.578877 -0.241972 0.283376
+seq7/frame00051.png -3.963772 -20.312341 1.893778 0.723698 0.593926 -0.232298 0.263724
+seq7/frame00052.png -3.253335 -20.480189 1.889798 0.724990 0.593836 -0.234774 0.258128
+seq7/frame00053.png -2.470283 -20.774158 1.759759 0.736172 0.593938 -0.214720 0.243276
+seq7/frame00026.png -22.980050 -15.229048 1.661614 0.610755 0.549177 -0.377694 0.427469
+seq7/frame00025.png -23.660958 -14.852443 1.744996 0.627253 0.558269 -0.348565 0.416403
+seq7/frame00054.png -1.910129 -20.862950 1.822718 0.749814 0.593862 -0.189459 0.221839
+seq7/frame00055.png -1.131067 -21.084283 1.874709 0.744780 0.596975 -0.189060 0.230607
+seq7/frame00056.png -0.318291 -21.044916 1.979469 0.742911 0.603992 -0.177733 0.227349
+seq7/frame00057.png 0.442729 -21.277574 1.786215 0.740726 0.599125 -0.202078 0.227020
+seq7/frame00058.png 1.329111 -21.285416 1.849226 0.744088 0.599272 -0.205412 0.212159
+seq7/frame00059.png 2.011176 -21.496994 1.749186 0.742240 0.612652 -0.185565 0.198248
+seq7/frame00060.png 2.763441 -21.570304 1.823128 0.736954 0.620389 -0.188534 0.190975
+seq7/frame00061.png 3.512889 -21.796686 1.668700 0.743539 0.606749 -0.184085 0.212409
+seq7/frame00062.png 4.324028 -21.996924 1.791973 0.735588 0.620108 -0.187697 0.197852
+seq7/frame00063.png 5.062083 -22.135850 1.807266 0.732778 0.618931 -0.195359 0.204442
+seq7/frame00064.png 5.871245 -22.145514 1.906262 0.740236 0.618086 -0.170983 0.201954
+seq7/frame00065.png 6.623529 -22.285303 1.907085 0.748097 0.608516 -0.179827 0.194219
+seq7/frame00066.png 7.480523 -22.373368 1.730820 0.765808 0.598968 -0.170964 0.159832
+seq7/frame00067.png 8.198709 -22.460965 1.748254 0.764411 0.608538 -0.152823 0.148331
+seq7/frame00068.png 8.920337 -22.738723 1.834570 0.769459 0.613496 -0.129266 0.121845
+seq7/frame00069.png 9.711602 -22.799802 1.608074 0.781506 0.608808 -0.097772 0.095087
+seq7/frame00070.png 10.233350 -23.024696 1.862208 0.777161 0.624425 -0.064681 0.043936
+seq7/frame00071.png 11.137815 -23.263750 1.980607 0.777863 0.624057 -0.055555 0.048954
+seq7/frame00072.png 11.915640 -23.576071 1.714673 0.776329 0.628560 -0.037820 0.028179
+seq7/frame00073.png 12.608373 -23.747977 1.845003 0.777898 0.627975 -0.021355 0.008143
+seq7/frame00074.png 13.236864 -24.132282 1.828876 0.769271 0.637893 -0.030718 0.019230
+seq7/frame00075.png 13.727763 -24.404897 2.025082 0.777170 0.628241 -0.034767 -0.010528
+seq7/frame00076.png 14.628859 -24.777264 1.881960 0.762735 0.645918 -0.031750 0.004187
+seq7/frame00077.png 15.161935 -25.064914 2.094405 0.769715 0.637865 -0.023526 0.010625
+seq7/frame00078.png 15.885105 -25.527937 1.877668 0.776165 0.630256 0.009150 -0.016152
+seq7/frame00079.png 16.542913 -25.732379 2.042813 0.788732 0.614613 -0.001659 0.012234
+seq7/frame00081.png 17.877780 -26.056916 1.943285 0.772265 0.634455 0.032078 -0.006607
+seq7/frame00080.png 17.202593 -25.964246 1.917686 0.775751 0.629480 0.041409 -0.015838
+seq7/frame00082.png 18.804973 -26.229792 1.945266 0.767357 0.638709 0.054500 -0.015585
+seq7/frame00083.png 19.584452 -26.324690 1.993557 0.766080 0.633166 0.085784 -0.069741
+seq7/frame00085.png 21.019635 -26.439089 1.905365 0.772953 0.624955 0.078520 -0.076218
+seq7/frame00084.png 20.284757 -26.554089 1.704921 0.761300 0.635009 0.103977 -0.079835
+seq2/frame00060.png -12.960270 -17.745061 1.905141 0.665089 0.638548 -0.267225 0.280186
+seq2/frame00059.png -10.964422 -18.003095 1.948263 0.667120 0.654447 -0.240937 0.261915
+seq2/frame00058.png -9.017906 -18.339121 1.861857 0.687444 0.641992 -0.225948 0.253405
+seq2/frame00061.png -14.954063 -17.336136 1.834820 0.660323 0.620394 -0.285394 0.312465
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diff --git a/official/cv/posenet/infer/docker_start_infer.sh b/official/cv/posenet/infer/docker_start_infer.sh
new file mode 100644
index 0000000000000000000000000000000000000000..2fb4b47bb87b0e7b306034bcf2b8b25f384309aa
--- /dev/null
+++ b/official/cv/posenet/infer/docker_start_infer.sh
@@ -0,0 +1,42 @@
+#!/bin/bash
+
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+docker_image=$1
+share_dir=$2
+echo "$1"
+echo "$2"
+if [ -z "${docker_image}" ]; then
+ echo "please input docker_image"
+ exit 1
+fi
+
+if [ ! -d "${share_dir}" ]; then
+ echo "please input share directory that contains dataset, models and codes"
+ exit 1
+fi
+
+
+docker run -it \
+ --device=/dev/davinci0 \
+ --device=/dev/davinci_manager \
+ --device=/dev/devmm_svm \
+ --device=/dev/hisi_hdc \
+ --privileged \
+ -v //usr/local/bin/npu-smi:/usr/local/bin/npu-smi \
+ -v /usr/local/Ascend/driver:/usr/local/Ascend/driver \
+ -v ${share_dir}:${share_dir} \
+ ${docker_image} \
+ /bin/bash
\ No newline at end of file
diff --git a/official/cv/posenet/infer/mxbase/CMakeLists.txt b/official/cv/posenet/infer/mxbase/CMakeLists.txt
new file mode 100644
index 0000000000000000000000000000000000000000..821d9dd79fbb4281e16761a607c8084cd2c54594
--- /dev/null
+++ b/official/cv/posenet/infer/mxbase/CMakeLists.txt
@@ -0,0 +1,42 @@
+cmake_minimum_required(VERSION 3.5.2)
+project(posenet)
+add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)
+
+#set(PLUGIN_NAME "midas_mindspore_post")
+
+set(TARGET_MAIN posenet_mindspore)
+
+set(ACL_LIB_PATH $ENV{ASCEND_HOME}/nnrt/latest/acllib)
+
+include_directories(${CMAKE_CURRENT_BINARY_DIR})
+
+include_directories($ENV{MX_SDK_HOME}/include)
+include_directories($ENV{MX_SDK_HOME}/opensource/include)
+include_directories($ENV{MX_SDK_HOME}/opensource/include/opencv4)
+include_directories($ENV{MX_SDK_HOME}/opensource/include/gstreamer-1.0)
+include_directories($ENV{MX_SDK_HOME}/opensource/include/glib-2.0)
+include_directories($ENV{MX_SDK_HOME}/opensource/lib/glib-2.0/include)
+
+link_directories($ENV{MX_SDK_HOME}/lib)
+link_directories($ENV{MX_SDK_HOME}/opensource/lib/)
+
+
+add_compile_options(-std=c++11 -fPIC -fstack-protector-all -pie -Wno-deprecated-declarations)
+add_compile_options("-DPLUGIN_NAME=${PLUGIN_NAME}")
+add_compile_options("-Dgoogle=mindxsdk_private")
+
+add_definitions(-DENABLE_DVPP_INTERFACE)
+
+#message("ACL_LIB_PATH:${ACL_LIB_PATH}/lib64/.")
+#include_directories(${CMAKE_CURRENT_BINARY_DIR})
+include_directories(${ACL_LIB_PATH}/include)
+link_directories(${ACL_LIB_PATH}/lib64/)
+
+
+
+
+add_executable(${TARGET_MAIN} src/main.cpp src/Posenet.cpp)
+target_link_libraries(${TARGET_MAIN} glib-2.0 gstreamer-1.0 gobject-2.0 gstbase-1.0 gmodule-2.0)
+target_link_libraries(${TARGET_MAIN} plugintoolkit mxpidatatype mxbase)
+target_link_libraries(${TARGET_MAIN} -Wl,-z,relro,-z,now,-z,noexecstack -s)
+target_link_libraries(${TARGET_MAIN} glog cpprest mxbase libascendcl.so opencv_world)
diff --git a/official/cv/posenet/infer/mxbase/build.sh b/official/cv/posenet/infer/mxbase/build.sh
new file mode 100644
index 0000000000000000000000000000000000000000..76812328b8ff08340fcd476644b0f87cfad562e2
--- /dev/null
+++ b/official/cv/posenet/infer/mxbase/build.sh
@@ -0,0 +1,47 @@
+#!/bin/bash
+
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+
+
+# env
+
+mkdir -p build
+cd build || exit
+
+function make_plugin() {
+ if ! cmake ..;
+ then
+ echo "cmake failed."
+ return 1
+ fi
+
+ if ! (make);
+ then
+ echo "make failed."
+ return 1
+ fi
+
+ return 0
+}
+
+if make_plugin;
+then
+ echo "INFO: Build successfully."
+else
+ echo "ERROR: Build failed."
+fi
+
+cd - || exit
diff --git a/official/cv/posenet/infer/mxbase/src/Posenet.cpp b/official/cv/posenet/infer/mxbase/src/Posenet.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..ce94d9cc1b64759ff3ce1b4c32689aa0494a9cc5
--- /dev/null
+++ b/official/cv/posenet/infer/mxbase/src/Posenet.cpp
@@ -0,0 +1,354 @@
+/*
+ * Copyright (c) 2021. Huawei Technologies Co., Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include <sys/stat.h>
+#include <dirent.h>
+#include <string>
+#include <fstream>
+#include <memory>
+#include <boost/property_tree/json_parser.hpp>
+#include <opencv4/opencv2/core.hpp>
+#include <opencv4/opencv2/opencv.hpp>
+#include "acl/acl.h"
+#include "MxBase/DeviceManager/DeviceManager.h"
+#include "MxBase/CV/ObjectDetection/Nms/Nms.h"
+#include "MxBase/Log/Log.h"
+#include "Posenet.h"
+namespace {
+ const uint32_t YUV_BYTE_NU = 3;
+ const uint32_t YUV_BYTE_DE = 2;
+ const uint32_t MODEL_HEIGHT = 224;
+ const uint32_t MODEL_WIDTH = 224;
+} // namespace
+
+void PrintTensorShape(const std::vector<MxBase::TensorDesc> &tensorDescVec, const std::string &tensorName) {
+ LogInfo << "The shape of " << tensorName << " is as follows:";
+ for (size_t i = 0; i < tensorDescVec.size(); ++i) {
+ LogInfo << " Tensor " << i << ":";
+ for (size_t j = 0; j < tensorDescVec[i].tensorDims.size(); ++j) {
+ LogInfo << " dim: " << j << ": " << tensorDescVec[i].tensorDims[j];
+ }
+ }
+}
+
+APP_ERROR Posenet::Init(const InitParam &initParam) {
+ deviceId_ = initParam.deviceId;
+ APP_ERROR ret = MxBase::DeviceManager::GetInstance()->InitDevices();
+ if (ret != APP_ERR_OK) {
+ LogError << "Init devices failed, ret=" << ret << ".";
+ return ret;
+ }
+ ret = MxBase::TensorContext::GetInstance()->SetContext(initParam.deviceId);
+ if (ret != APP_ERR_OK) {
+ LogError << "Set context failed, ret=" << ret << ".";
+ return ret;
+ }
+ dvppWrapper_ = std::make_shared<MxBase::DvppWrapper>();
+ ret = dvppWrapper_->Init();
+ if (ret != APP_ERR_OK) {
+ LogError << "DvppWrapper init failed, ret=" << ret << ".";
+ return ret;
+ }
+ model_ = std::make_shared<MxBase::ModelInferenceProcessor>();
+ ret = model_->Init(initParam.modelPath, modelDesc_);
+ if (ret != APP_ERR_OK) {
+ LogError << "ModelInferenceProcessor init failed, ret=" << ret << ".";
+ return ret;
+ }
+ PrintTensorShape(modelDesc_.inputTensors, "Model Input Tensors");
+ PrintTensorShape(modelDesc_.outputTensors, "Model Output Tensors");
+ return APP_ERR_OK;
+}
+
+APP_ERROR Posenet::DeInit() {
+ dvppWrapper_->DeInit();
+ model_->DeInit();
+ MxBase::DeviceManager::GetInstance()->DestroyDevices();
+ return APP_ERR_OK;
+}
+
+APP_ERROR Posenet::Inference(const std::vector<MxBase::TensorBase> &inputs,
+ std::vector<MxBase::TensorBase> &outputs) {
+ auto dtypes = model_->GetOutputDataType();
+ for (size_t i = 0; i < modelDesc_.outputTensors.size(); ++i) {
+ std::vector<uint32_t> shape = {};
+ for (size_t j = 0; j < modelDesc_.outputTensors[i].tensorDims.size(); ++j) {
+ shape.push_back((uint32_t)modelDesc_.outputTensors[i].tensorDims[j]);
+ }
+ MxBase::TensorBase tensor(shape, dtypes[i], MxBase::MemoryData::MemoryType::MEMORY_DEVICE, deviceId_);
+ APP_ERROR ret = MxBase::TensorBase::TensorBaseMalloc(tensor);
+ if (ret != APP_ERR_OK) {
+ LogError << "TensorBaseMalloc failed, ret=" << ret << ".";
+ return ret;
+ }
+ outputs.push_back(tensor);
+ }
+ MxBase::DynamicInfo dynamicInfo = {};
+ dynamicInfo.dynamicType = MxBase::DynamicType::STATIC_BATCH;
+ auto startTime = std::chrono::high_resolution_clock::now();
+ APP_ERROR ret = model_->ModelInference(inputs, outputs, dynamicInfo);
+ auto endTime = std::chrono::high_resolution_clock::now();
+ double costMs = std::chrono::duration<double, std::milli>(endTime - startTime).count(); // save time
+ inferCostTimeMilliSec += costMs;
+ if (ret != APP_ERR_OK) {
+ LogError << "ModelInference failed, ret=" << ret << ".";
+ return ret;
+ }
+ return APP_ERR_OK;
+}
+
+APP_ERROR Posenet::Process(const std::string &imgPath, const std::string &resultPath, const std::string &dataset_name) {
+ ImageShape imageShape{};
+ ImageShape resizedImageShape{};
+ std::vector<std::string> dirs;
+
+ std::string data_set = imgPath;
+ dirs = GetAlldir(data_set, dataset_name);
+
+ for (const auto &dir : dirs) {
+ std::vector<std::string> images;
+ if (dataset_name == "TUM") {
+ images = GetAlldir(data_set, "TUM");
+ } else {
+ images = GetAllFiles(data_set + dir);
+ }
+ for (const auto& image_file : images) {
+ cv::Mat imageMat;
+ APP_ERROR ret = ReadImageCV(image_file, imageMat, imageShape);
+ if (ret != APP_ERR_OK) {
+ LogError << "ReadImage failed, ret=" << ret << ".";
+ return ret;
+ }
+ ret = ResizeImage(imageMat, imageMat, resizedImageShape);
+ if (ret != APP_ERR_OK) {
+ LogError << "ResizeImage failed, ret=" << ret << ".";
+ return ret;
+ }
+ MxBase::TensorBase tensorBase;
+ ret = CVMatToTensorBase(imageMat, tensorBase);
+ if (ret != APP_ERR_OK) {
+ LogError << "CVMatToTensorBase failed, ret=" << ret << ".";
+ return ret;
+ }
+ std::vector<MxBase::TensorBase> inputs = {};
+ std::vector<MxBase::TensorBase> outputs = {};
+ inputs.push_back(tensorBase);
+ std::cout << "inputsshapeis" << inputs[0].GetShape()[0] << " "
+ << inputs[0].GetShape()[1] << " " << inputs[0].GetShape()[2] << std::endl;
+ auto startTime = std::chrono::high_resolution_clock::now();
+ ret = Inference(inputs, outputs);
+ auto endTime = std::chrono::high_resolution_clock::now();
+ double costMs = std::chrono::duration<double, std::milli>(endTime - startTime).count(); // save time
+ inferCostTimeMilliSec += costMs;
+ if (ret != APP_ERR_OK) {
+ LogError << "Inference failed, ret=" << ret << ".";
+ return ret;
+ }
+ WriteResult(image_file, outputs, dataset_name, dir);
+ }
+ }
+ return APP_ERR_OK;
+}
+
+std::vector<std::string> GetAlldir(const std::string& dir_name, const std::string& data_name) {
+ std::vector<std::string> res;
+ if (data_name == "TUM") {
+ std::string txt_name = dir_name + "/associate.txt";
+ std::ifstream infile;
+ infile.open(txt_name.data());
+ std::string s;
+ while (getline(infile, s)) {
+ std::stringstream input(s);
+ std::string result;
+ input >> result;
+ res.emplace_back(dir_name + "/" + result);
+ }
+ return res;
+ }
+ struct dirent *filename;
+ DIR *dir = OpenDir(dir_name);
+ if (dir == nullptr) {
+ return {};
+ }
+ if (data_name == "Kitti") {
+ while ((filename = readdir(dir)) != nullptr) {
+ std::string d_name = std::string(filename->d_name);
+ // get rid of "." and ".."
+ if (d_name == "." || d_name == ".." || filename->d_type != DT_DIR)
+ continue;
+ res.emplace_back(d_name + "/image");
+ std::cout << "image_file name is " << d_name << std::endl;
+ }
+ } else {
+ while ((filename = readdir(dir)) != nullptr) {
+ std::string d_name = std::string(filename->d_name);
+ // get rid of "." and ".."
+ if (d_name == "." || d_name == ".." || filename->d_type != DT_DIR)
+ continue;
+ res.emplace_back(d_name);
+ }
+ }
+ return res;
+}
+
+APP_ERROR Posenet::GetMetaMap(const ImageShape imgShape,
+ const ImageShape resizeimgShape,
+ std::map<std::string, float> &meta) {
+ int a = 2;
+ int b = 4;
+ std::vector<float> c = {static_cast<float>(imgShape.width) / a, static_cast<float>(imgShape.height) / a};
+ float s = std::max(static_cast<float>(resizeimgShape.width) / static_cast<float>(resizeimgShape.height)
+ * static_cast<float>(imgShape.height), static_cast<float>(imgShape.width)) * 1.0;
+ meta["c1"] = c[0];
+ meta["c2"] = c[1];
+ meta["s"] = s;
+ meta["out_height"] = resizeimgShape.height / b;
+ meta["out_width"] = resizeimgShape.width / b;
+ return APP_ERR_OK;
+}
+
+APP_ERROR Posenet::CVMatToTensorBase(const cv::Mat &imageMat, MxBase::TensorBase &tensorBase) {
+ const uint32_t dataSize = imageMat.cols * imageMat.rows * imageMat.channels();
+ MxBase::MemoryData memoryDataDst(dataSize, MxBase::MemoryData::MEMORY_DEVICE, deviceId_);
+ MxBase::MemoryData memoryDataSrc(imageMat.data, dataSize, MxBase::MemoryData::MEMORY_HOST_MALLOC);
+ APP_ERROR ret = MxBase::MemoryHelper::MxbsMallocAndCopy(memoryDataDst, memoryDataSrc);
+ if (ret != APP_ERR_OK) {
+ LogError << GetError(ret) << "Memory malloc failed.";
+ return ret;
+ }
+ std::vector<uint32_t> shape = {static_cast<uint32_t>(imageMat.rows),
+ static_cast<uint32_t>(imageMat.cols),
+ static_cast<uint32_t>(imageMat.channels())};
+ tensorBase = MxBase::TensorBase(memoryDataDst, false, shape, MxBase::TENSOR_DTYPE_UINT8);
+ return APP_ERR_OK;
+}
+
+APP_ERROR Posenet::ResizeImage(const cv::Mat &srcImageMat, cv::Mat &dstImageMat, ImageShape &imgShape) {
+ int height = 456;
+ int width = 224;
+ cv::resize(srcImageMat, dstImageMat, cv::Size(width, height), 0, 0);
+ LogInfo << dstImageMat.cols << dstImageMat.rows;
+ imgShape.width = dstImageMat.cols;
+ imgShape.height = dstImageMat.rows;
+ return APP_ERR_OK;
+}
+
+APP_ERROR Posenet::ReadImageCV(const std::string &imgPath, cv::Mat &imageMat, ImageShape &imgShape) {
+ imageMat = cv::imread(imgPath, cv::IMREAD_COLOR);
+ imgShape.width = imageMat.cols;
+ imgShape.height = imageMat.rows;
+ return APP_ERR_OK;
+}
+
+std::vector<std::string> GetAllFiles(std::string dirName) {
+ struct dirent *filename;
+ DIR *dir = OpenDir(dirName);
+ std::cout << dirName << std::endl;
+ if (dir == nullptr) {
+ return {};
+ }
+ std::vector<std::string> res;
+ while ((filename = readdir(dir)) != nullptr) {
+ std::string dName = std::string(filename->d_name);
+ if (dName == "." || dName == ".." || filename->d_type != DT_REG) {
+ continue;
+ }
+ res.emplace_back(std::string(dirName) + "/" + filename->d_name);
+ }
+ std::sort(res.begin(), res.end());
+ for (auto &f : res) {
+ std::cout << "image file: " << f << std::endl;
+ }
+ return res;
+}
+
+std::string RealPath(std::string path) {
+ char realPathMem[PATH_MAX] = {0};
+ char *realPathRet = nullptr;
+ realPathRet = realpath(path.data(), realPathMem);
+ if (realPathRet == nullptr) {
+ std::cout << "File: " << path << " is not exist.";
+ return "";
+ }
+ std::string realPath(realPathMem);
+ std::cout << path << " realpath is: " << realPath << std::endl;
+ return realPath;
+}
+
+DIR *OpenDir(std::string dirName) {
+ if (dirName.empty()) {
+ std::cout << " dirName is null ! " << std::endl;
+ return nullptr;
+ }
+ std::string realPath = RealPath(dirName);
+ struct stat s;
+ lstat(realPath.c_str(), &s);
+ if (!S_ISDIR(s.st_mode)) {
+ std::cout << "dirName is not a valid directory !" << std::endl;
+ return nullptr;
+ }
+ DIR *dir = opendir(realPath.c_str());
+ if (dir == nullptr) {
+ std::cout << "Can not open dir " << dirName << std::endl;
+ return nullptr;
+ }
+ std::cout << "Successfully opened the dir " << dirName << std::endl;
+ return dir;
+}
+
+APP_ERROR Posenet::WriteResult(const std::string& imageFile, std::vector<MxBase::TensorBase> &outputs,
+ const std::string & dataset_name, const std::string& seq) {
+ std::string homePath;
+ if (dataset_name == "Kitti") {
+ int pos = seq.find('/');
+ std::string seq1(seq, 0, pos);
+ homePath = "./result_Files/"+ dataset_name + "/" + seq1;
+ std::cout << "1" << std::endl;
+ } else {
+ homePath = "./result_Files/"+ dataset_name + "/" + seq;
+ }
+ std::string path1 = "mkdir -p " + homePath;
+ system(path1.c_str());
+ std::cout << "homePath is " << homePath << std::endl;
+ for (size_t i = 0; i < outputs.size(); ++i) {
+ size_t outputSize;
+ APP_ERROR ret = outputs[i].ToHost();
+ if (ret != APP_ERR_OK) {
+ LogError << GetError(ret) << "tohost fail.";
+ return ret;
+ }
+ void *netOutput = outputs[i].GetBuffer();
+ std::vector<uint32_t> out_shape = outputs[i].GetShape();
+ LogDebug << "shape is "<< out_shape[0] << " " << out_shape[1] << " " << out_shape[2];
+ outputSize = outputs[i].GetByteSize();
+ std::cout << "outputsize is " << outputSize << std::endl;
+ int pos = imageFile.rfind('/');
+ std::string fileName(imageFile, pos + 1);
+ fileName.replace(fileName.rfind('.'), fileName.size() - fileName.rfind('.'), '_' + std::to_string(i) + ".bin");
+ std::string outFileName = homePath + "/" + fileName;
+ std::cout << "output file is " << outFileName << std::endl;
+ FILE *outputFile = fopen(outFileName.c_str(), "wb");
+ if (outputFile == nullptr) {
+ std::cout << "read fail" << std::endl;
+ return ret;
+ }
+ auto count1 = fwrite(netOutput, outputSize, sizeof(char), outputFile);
+ std::cout << "count is " << count1 << " " << sizeof(char) << std::endl;
+ fclose(outputFile);
+ outputFile = nullptr;
+ }
+ LogDebug << "PosenetMindspore write results success.";
+ return APP_ERR_OK;
+}
diff --git a/official/cv/posenet/infer/mxbase/src/Posenet.h b/official/cv/posenet/infer/mxbase/src/Posenet.h
new file mode 100644
index 0000000000000000000000000000000000000000..524926f13dff66d3b0cf3e3f05745ca2f689fee4
--- /dev/null
+++ b/official/cv/posenet/infer/mxbase/src/Posenet.h
@@ -0,0 +1,90 @@
+/*
+ * Copyright (c) 2021. Huawei Technologies Co., Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef POSENET_H
+#define POSENET_H
+
+#include <dirent.h>
+#include <sys/stat.h>
+#include <map>
+#include <vector>
+#include <string>
+#include <sstream>
+#include <algorithm>
+#include <memory>
+#include <opencv4/opencv2/opencv.hpp>
+#include "MxBase/CV/Core/DataType.h"
+#include "MxBase/DeviceManager/DeviceManager.h"
+#include "MxBase/DvppWrapper/DvppWrapper.h"
+#include "MxBase/ErrorCode/ErrorCode.h"
+#include "MxBase/ModelInfer/ModelInferenceProcessor.h"
+#include "MxBase/PostProcessBases/ObjectPostProcessBase.h"
+#include "MxBase/Tensor/TensorContext/TensorContext.h"
+
+struct InitParam {
+ uint32_t deviceId;
+ std::string labelPath;
+ std::string dataset_name;
+ bool checkTensor;
+ std::string modelPath;
+};
+
+struct ImageShape {
+ uint32_t width;
+ uint32_t height;
+};
+std::vector<std::string> GetAllFiles(std::string dirName);
+std::vector<std::string> GetAlldir(const std::string &dir_name,
+ const std::string &data_name);
+std::string RealPath(std::string path);
+DIR *OpenDir(std::string dirName);
+
+class Posenet {
+ public:
+ APP_ERROR Init(const InitParam &initParam);
+ APP_ERROR DeInit();
+ APP_ERROR Inference(const std::vector<MxBase::TensorBase> &inputs,
+ std::vector<MxBase::TensorBase> &outputs);
+ APP_ERROR PostProcess(const std::vector<MxBase::TensorBase> &inputs,
+ const std::map<std::string, float> &meta,
+ std::string &seq, std::string &image_file);
+ APP_ERROR Process(const std::string &imgPath, const std::string &resultPath,
+ const std::string &dataset_name);
+ APP_ERROR ReadImageCV(const std::string &imgPath, cv::Mat &imageMat,
+ ImageShape &imgShape);
+ APP_ERROR ResizeImage(const cv::Mat &srcImageMat, cv::Mat &dstImageMat,
+ ImageShape &imgShape);
+ APP_ERROR CVMatToTensorBase(const cv::Mat &imageMat,
+ MxBase::TensorBase &tensorBase);
+ APP_ERROR GetMetaMap(const ImageShape imgShape,
+ const ImageShape resizeimgShape,
+ std::map<std::string, float> &meta);
+ APP_ERROR WriteResult(const std::string &imageFile,
+ std::vector<MxBase::TensorBase> &outputs,
+ const std::string &dataset_name,
+ const std::string &seq);
+
+ private:
+ APP_ERROR GetImageMeta(const ImageShape &imageShape,
+ MxBase::TensorBase &imgMetas) const;
+ std::shared_ptr<MxBase::DvppWrapper> dvppWrapper_;
+ std::shared_ptr<MxBase::ModelInferenceProcessor> model_;
+ MxBase::ModelDesc modelDesc_;
+ uint32_t deviceId_ = 0;
+ double inferCostTimeMilliSec = 0.0;
+};
+
+#endif // posenet_H
diff --git a/official/cv/posenet/infer/mxbase/src/main.cpp b/official/cv/posenet/infer/mxbase/src/main.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..f84da3f8f8bc04203d30cc28003cde816669c012
--- /dev/null
+++ b/official/cv/posenet/infer/mxbase/src/main.cpp
@@ -0,0 +1,49 @@
+/*
+ * Copyright (c) 2021. Huawei Technologies Co., Ltd. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "MxBase/Log/Log.h"
+#include "Posenet.h"
+
+namespace {
+ const uint32_t DEVICE_ID = 0;
+ const std::string RESULT_PATH = "./result";
+} // namespace
+
+int main(int argc, char *argv[]) {
+ if (argc <= 3) {
+ LogWarn << "Please input image path, such as './ [om_file_path] [img_path] [dataset_name]'.";
+ return APP_ERR_OK;
+ }
+ InitParam initParam = {};
+ initParam.deviceId = DEVICE_ID;
+ initParam.checkTensor = true;
+ initParam.modelPath = argv[1];
+ auto inferPosenet = std::make_shared<Posenet>();
+ APP_ERROR ret = inferPosenet->Init(initParam);
+ if (ret != APP_ERR_OK) {
+ LogError << "Posenet init failed, ret=" << ret << ".";
+ return ret;
+ }
+ std::string imgPath = argv[2];
+ std::string dataset_name = argv[3];
+ ret = inferPosenet->Process(imgPath, RESULT_PATH, dataset_name);
+ if (ret != APP_ERR_OK) {
+ LogError << "Posenet process failed, ret=" << ret << ".";
+ inferPosenet->DeInit();
+ return ret;
+ }
+ inferPosenet->DeInit();
+ return APP_ERR_OK;
+}
diff --git a/official/cv/posenet/infer/sdk/api/infer.py b/official/cv/posenet/infer/sdk/api/infer.py
new file mode 100644
index 0000000000000000000000000000000000000000..de51d2783aa093903696e3d5e689923dcff12aeb
--- /dev/null
+++ b/official/cv/posenet/infer/sdk/api/infer.py
@@ -0,0 +1,143 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+"""sdk infer"""
+import json
+import logging
+import MxpiDataType_pb2 as MxpiDataType
+from StreamManagerApi import StreamManagerApi, MxDataInput, InProtobufVector, MxProtobufIn, StringVector
+from config import config as cfg
+
+class SdkApi:
+ """sdk api"""
+ INFER_TIMEOUT = cfg.INFER_TIMEOUT
+ STREAM_NAME = cfg.STREAM_NAME
+
+ def __init__(self, pipeline_cfg):
+ self.pipeline_cfg = pipeline_cfg
+ self._stream_api = None
+ self._data_input = None
+ self._device_id = None
+
+ def init(self):
+ """sdk init """
+ with open(self.pipeline_cfg, 'r') as fp:
+ self._device_id = int(
+ json.loads(fp.read())[self.STREAM_NAME]["stream_config"]
+ ["deviceId"])
+ print(f"The device id: {self._device_id}.")
+
+ # create api
+ self._stream_api = StreamManagerApi()
+
+ # init stream mgr
+ ret = self._stream_api.InitManager()
+ if ret != 0:
+ print(f"Failed to init stream manager, ret={ret}.")
+ return False
+
+ # create streams
+ with open(self.pipeline_cfg, 'rb') as fp:
+ pipe_line = fp.read()
+
+ ret = self._stream_api.CreateMultipleStreams(pipe_line)
+ if ret != 0:
+ print(f"Failed to create stream, ret={ret}.")
+ return False
+
+ self._data_input = MxDataInput()
+
+ return True
+
+ def __del__(self):
+ """del sdk"""
+ if not self._stream_api:
+ return
+
+ self._stream_api.DestroyAllStreams()
+
+ def send_data_input(self, stream_name, plugin_id, input_data):
+ """input data use SendData"""
+ data_input = MxDataInput()
+ data_input.data = input_data
+ unique_id = self._stream_api.SendData(stream_name, plugin_id,
+ data_input)
+ if unique_id < 0:
+ logging.error("Fail to send data to stream.")
+ return False
+ return True
+
+ def _send_protobuf(self, stream_name, plugin_id, element_name, buf_type,
+ pkg_list):
+ """input data use SendProtobuf"""
+ protobuf = MxProtobufIn()
+ protobuf.key = element_name.encode("utf-8")
+ protobuf.type = buf_type
+ protobuf.protobuf = pkg_list.SerializeToString()
+ protobuf_vec = InProtobufVector()
+ protobuf_vec.push_back(protobuf)
+ err_code = self._stream_api.SendProtobuf(stream_name, plugin_id,
+ protobuf_vec)
+ if err_code != 0:
+ logging.error(
+ "Failed to send data to stream, stream_name(%s), plugin_id(%s), element_name(%s), "
+ "buf_type(%s), err_code(%s).", stream_name, plugin_id,
+ element_name, buf_type, err_code)
+ return False
+ return True
+
+ def send_img_input(self, stream_name, plugin_id, element_name, input_data,
+ img_size):
+ """use cv input to sdk"""
+ vision_list = MxpiDataType.MxpiVisionList()
+ vision_vec = vision_list.visionVec.add()
+ vision_vec.visionInfo.format = 1
+ vision_vec.visionInfo.width = img_size[1]
+ vision_vec.visionInfo.height = img_size[0]
+ vision_vec.visionInfo.widthAligned = img_size[1]
+ vision_vec.visionInfo.heightAligned = img_size[0]
+ vision_vec.visionData.memType = 0
+ vision_vec.visionData.dataStr = input_data
+ vision_vec.visionData.dataSize = len(input_data)
+ buf_type = b"MxTools.MxpiVisionList"
+ return self._send_protobuf(stream_name, plugin_id, element_name,
+ buf_type, vision_list)
+
+ #pylint: disable=R1710
+ def get_result(self, stream_name, out_plugin_id=0):
+ """get_result
+ """
+ key_vec = StringVector()
+ key_vec.push_back(b'mxpi_modelinfer0')
+ infer_result = self._stream_api.GetProtobuf(
+ stream_name, out_plugin_id, key_vec)
+ if infer_result.size() == 0:
+ print("inferResult is null")
+ return
+ if infer_result[0].errorCode != 0:
+ print("GetProtobuf error. errorCode=%d" % infer_result[0].errorCode)
+ return
+ result = MxpiDataType.MxpiTensorPackageList()
+ result.ParseFromString(infer_result[0].messageBuf)
+
+ print('datastr', type(result.tensorPackageVec[0].tensorVec[0].dataStr))
+ print('datastr', type(result.tensorPackageVec[0].tensorVec[1].dataStr))
+ print('datastr', type(result.tensorPackageVec[0].tensorVec[2].dataStr))
+ print('datastr', type(result.tensorPackageVec[0].tensorVec[3].dataStr))
+ print('datastr', type(result.tensorPackageVec[0].tensorVec[4].dataStr))
+ print('datastr', type(result.tensorPackageVec[0].tensorVec[5].dataStr))
+
+ return result.tensorPackageVec[0].tensorVec[0].dataStr, result.tensorPackageVec[0].tensorVec[1].dataStr, \
+ result.tensorPackageVec[0].tensorVec[2].dataStr, result.tensorPackageVec[0].tensorVec[3].dataStr, \
+ result.tensorPackageVec[0].tensorVec[4].dataStr, result.tensorPackageVec[0].tensorVec[5].dataStr
diff --git a/official/cv/posenet/infer/sdk/config/config.py b/official/cv/posenet/infer/sdk/config/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..e8d5a44bc3b9df2a3f90c6e1ae62c9a3534b8d72
--- /dev/null
+++ b/official/cv/posenet/infer/sdk/config/config.py
@@ -0,0 +1,25 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+
+
+STREAM_NAME = "im_posenet"
+MODEL_WIDTH = 224
+MODEL_HEIGHT = 224
+
+INFER_TIMEOUT = 100000
+
+TENSOR_DTYPE_FLOAT32 = 0
+TENSOR_DTYPE_FLOAT16 = 1
+TENSOR_DTYPE_INT8 = 2
diff --git a/official/cv/posenet/infer/sdk/config/posenet.pipeline b/official/cv/posenet/infer/sdk/config/posenet.pipeline
new file mode 100644
index 0000000000000000000000000000000000000000..5b6dc8faeb047688ce705f10eae1df972f0976d4
--- /dev/null
+++ b/official/cv/posenet/infer/sdk/config/posenet.pipeline
@@ -0,0 +1,44 @@
+{
+ "im_posenet": {
+ "stream_config": {
+ "deviceId": "0"
+ },
+ "appsrc0": {
+ "props": {
+ "blocksize": "409600"
+ },
+ "factory": "appsrc",
+ "next": "mxpi_imageresize0"
+ },
+ "mxpi_imageresize0": {
+ "props": {
+ "dataSource": "appsrc0",
+ "handleMethod": "opencv",
+ "resizeType": "Resizer_Stretch",
+ "resizeHeight": "456",
+ "resizeWidth": "224"
+ },
+ "factory": "mxpi_imageresize",
+ "next": "mxpi_modelinfer0"
+ },
+ "mxpi_modelinfer0": {
+ "props": {
+ "dataSource": "mxpi_imageresize0",
+ "modelPath": "../convert/posenet.om",
+ "outputDeviceId": "-1"
+ },
+ "factory": "mxpi_modelinfer",
+ "next": "mxpi_dataserialize0"
+ },
+ "mxpi_dataserialize0": {
+ "props": {
+ "outputDataKeys": "mxpi_modelinfer0"
+ },
+ "factory": "mxpi_dataserialize",
+ "next": "appsink0"
+ },
+ "appsink0": {
+ "factory": "appsink"
+ }
+ }
+}
diff --git a/official/cv/posenet/infer/sdk/eval/eval_by_sdk.py b/official/cv/posenet/infer/sdk/eval/eval_by_sdk.py
new file mode 100644
index 0000000000000000000000000000000000000000..ec8a749a74f33d6a604a2b278bf1d4477f71959c
--- /dev/null
+++ b/official/cv/posenet/infer/sdk/eval/eval_by_sdk.py
@@ -0,0 +1,88 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+"""post process for 310 inference"""
+import os
+import argparse
+import math
+import numpy as np
+
+parser = argparse.ArgumentParser(description='postprocess for posenet')
+parser.add_argument("--result_path", type=str, required=True, help="result file path")
+
+args = parser.parse_args()
+
+def get_result(result_path):
+ results = np.zeros((343, 2))
+ txt_file = "../dataset_test.txt"
+ step = 0
+ i = 0
+ with open(txt_file, 'r') as f:
+ next(f)
+ next(f)
+ next(f)
+ for line in f:
+ fname, p0, p1, p2, p3, p4, p5, p6 = line.split()
+ fname = str(fname)
+ p0 = float(p0)
+ p1 = float(p1)
+ p2 = float(p2)
+ p3 = float(p3)
+ p4 = float(p4)
+ p5 = float(p5)
+ p6 = float(p6)
+ image_poses = []
+ image_poses.append((p0, p1, p2, p3, p4, p5, p6))
+ poses = np.array(image_poses)
+ pose_x = np.squeeze(poses[:, 0:3])
+ pose_q = np.squeeze(poses[:, 3:])
+ file_name = "posenet" + "_" + str(i)
+ i = i + 1
+ result_path_0 = os.path.join(result_path, file_name + "_0.bin")
+ result_path_1 = os.path.join(result_path, file_name + "_1.bin")
+ result_path_2 = os.path.join(result_path, file_name + "_2.bin")
+ result_path_3 = os.path.join(result_path, file_name + "_3.bin")
+ result_path_4 = os.path.join(result_path, file_name + "_4.bin")
+ result_path_5 = os.path.join(result_path, file_name + "_5.bin")
+ p1_x = np.fromfile(result_path_0, dtype=np.float32).reshape(1, 3)
+ p1_q = np.fromfile(result_path_1, dtype=np.float32).reshape(1, 4)
+ p2_x = np.fromfile(result_path_2, dtype=np.float32).reshape(1, 3)
+ p2_q = np.fromfile(result_path_3, dtype=np.float32).reshape(1, 4)
+ p3_x = np.fromfile(result_path_4, dtype=np.float32).reshape(1, 3)
+ p3_q = np.fromfile(result_path_5, dtype=np.float32).reshape(1, 4)
+ print(p1_x)
+ print(p1_q)
+ print(p2_x)
+ print(p2_q)
+ print(p3_x)
+ print(p3_q)
+ predicted_x = p3_x
+ predicted_q = p3_q
+ q1 = pose_q / np.linalg.norm(pose_q)
+ q2 = predicted_q / np.linalg.norm(predicted_q)
+ d = abs(np.sum(np.multiply(q1, q2)))
+
+ a = 2
+ b = 180
+ theta = a * np.arccos(d) * b / math.pi
+ error_x = np.linalg.norm(pose_x - predicted_x)
+ results[step, :] = [error_x, theta]
+ step = step + 1
+ print('Iteration: ', step, ', Error XYZ (m): ', error_x, ', Error Q (degrees): ', theta)
+
+ median_result = np.median(results, axis=0)
+ print('Median error ', median_result[0], 'm and ', median_result[1], 'degrees.')
+
+if __name__ == '__main__':
+ get_result(args.result_path)
diff --git a/official/cv/posenet/infer/sdk/main.py b/official/cv/posenet/infer/sdk/main.py
new file mode 100644
index 0000000000000000000000000000000000000000..d54bbc78f40337661995f6210b8d268817a225e3
--- /dev/null
+++ b/official/cv/posenet/infer/sdk/main.py
@@ -0,0 +1,186 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+"""main"""
+
+import argparse
+import os
+import time
+import cv2
+from api.infer import SdkApi
+from config import config as cfg
+
+
+def parser_args():
+ """parser_args"""
+ parser = argparse.ArgumentParser(description="fairmot inference")
+
+ parser.add_argument("--img_path",
+ type=str,
+ required=False,
+ help="image directory.")
+ parser.add_argument(
+ "--pipeline_path",
+ type=str,
+ required=False,
+ default="/home/data/xd_mindx/rsd/infer/sdk/config/posenet.pipeline",
+ help="image file path. The default is '/home/data/xd_mindx/czp/fairmot/infer/sdk/config/fairmot.pipeline'. ")
+ parser.add_argument(
+ "--model_type",
+ type=str,
+ required=False,
+ default="dvpp",
+ help=
+ "rgb: high-precision, dvpp: high performance. The default is 'dvpp'.")
+ parser.add_argument(
+ "--infer_mode",
+ type=str,
+ required=False,
+ default="infer",
+ help=
+ "infer:only infer, eval: accuracy evaluation. The default is 'infer'.")
+ parser.add_argument(
+ "--infer_result_dir",
+ type=str,
+ required=False,
+ default="./infer_result",
+ help=
+ "cache dir of inference result. The default is '../data/infer_result'."
+ )
+ arg = parser.parse_args()
+ return arg
+
+
+def process_img(img_file):
+ #img2 = Image.open(img_file)
+ #img1 = img2.resize((224, 455),Image.ANTIALIAS)
+ img = cv2.imread(img_file)
+ #pad_img = cv2.resize(img, (224, 455), interpolation=cv2.INTER_AREA)
+ #img,__, _, _ = letterbox(img0, height=cfg.MODEL_HEIGHT, width=cfg.MODEL_WIDTH)
+ return img
+
+def letterbox(img, height=608, width=1088, color=(127.5, 127.5, 127.5)):
+ """resize a rectangular image to a padded rectangular"""
+ shape = img.shape[:2] # shape = [height, width]
+ ratio = min(float(height) / shape[0], float(width) / shape[1])
+ new_shape = (round(shape[1] * ratio), round(shape[0] * ratio)) # new_shape = [width, height]
+ dw = (width - new_shape[0]) / 2 # width padding
+ dh = (height - new_shape[1]) / 2 # height padding
+ top, bottom = round(dh - 0.1), round(dh + 0.1)
+ left, right = round(dw - 0.1), round(dw + 0.1)
+ img = cv2.resize(img, new_shape, interpolation=cv2.INTER_AREA) # resized, no border
+ img = cv2.copyMakeBorder(img, top, bottom, left, right, cv2.BORDER_CONSTANT, value=color) # padded rectangular
+ return img, ratio, dw, dh
+
+
+def image_inference(pipeline_path, stream_name, img_dir, result_dir):
+ """image_inference"""
+ sdk_api = SdkApi(pipeline_path)
+ if not sdk_api.init():
+ exit(-1)
+ print(stream_name)
+ if not os.path.exists(result_dir):
+ os.makedirs(result_dir)
+ img_data_plugin_id = 0
+ i = 0
+ print(f"\nBegin to inference for {img_dir}.\n")
+ file_list = os.listdir(img_dir)
+ txt_file = "../dataset_test.txt"
+ with open(txt_file, 'r') as f:
+ next(f)
+ next(f)
+ next(f)
+ for line in f:
+ fname, _, _, _, _, _, _, _ = line.split()
+ file_name1 = fname.split('/')[0] # seq
+ file_name2 = fname.split('/')[1] # frame0009
+ for filedirname in os.listdir(img_dir): # bianli file name
+ if filedirname == file_name1:
+ files = img_dir + "/" + file_name1
+ file_list = os.listdir(files)
+ for img_id, file_name in enumerate(file_list):
+ total_len = len(file_list)
+ if file_name == file_name2:
+ file_name1 = file_name1 + "/" + file_name
+ file_path = os.path.join(img_dir, file_name1)
+ file_binname0 = "posenet" + "_" + str(i) + "_0.bin"
+ file_binname1 = "posenet" + "_" + str(i) + "_1.bin"
+ file_binname2 = "posenet" + "_" + str(i) + "_2.bin"
+ file_binname3 = "posenet" + "_" + str(i) + "_3.bin"
+ file_binname4 = "posenet" + "_" + str(i) + "_4.bin"
+ file_binname5 = "posenet" + "_" + str(i) + "_5.bin"
+ i = i + 1
+ save_path = [os.path.join(result_dir, file_binname0),
+ os.path.join(result_dir, file_binname1),
+ os.path.join(result_dir, file_binname2),
+ os.path.join(result_dir, file_binname3),
+ os.path.join(result_dir, file_binname4),
+ os.path.join(result_dir, file_binname5)]
+ img_np = process_img(file_path)
+ img_shape = img_np.shape
+ sdk_api.send_img_input(stream_name,
+ img_data_plugin_id, "appsrc0",
+ img_np.tobytes(), img_shape)
+ start_time = time.time()
+ result = sdk_api.get_result(stream_name)
+ end_time = time.time() - start_time
+ with open(save_path[0], "wb") as fp:
+ fp.write(result[0])
+ print(
+ f"End-2end inference, file_name: {file_path}, "
+ f"{img_id + 1}/{total_len}, elapsed_time: {end_time}.\n"
+ )
+ with open(save_path[1], "wb") as fp:
+ fp.write(result[1])
+ print(
+ f"End-2end inference, file_name: {file_path}, "
+ f"{img_id + 1}/{total_len}, elapsed_time: {end_time}.\n"
+ )
+ with open(save_path[2], "wb") as fp:
+ fp.write(result[2])
+ print(
+ f"End-2end inference, file_name: {file_path}, "
+ f"{img_id + 1}/{total_len}, elapsed_time: {end_time}.\n"
+ )
+ with open(save_path[3], "wb") as fp:
+ fp.write(result[3])
+ print(
+ f"End-2end inference, file_name: {file_path}, "
+ f"{img_id + 1}/{total_len}, elapsed_time: {end_time}.\n"
+ )
+ with open(save_path[4], "wb") as fp:
+ fp.write(result[4])
+ print(
+ f"End-2end inference, file_name: {file_path}, "
+ f"{img_id + 1}/{total_len}, elapsed_time: {end_time}.\n"
+ )
+ with open(save_path[5], "wb") as fp:
+ fp.write(result[5])
+ print(
+ f"End-2end inference, file_name: {file_path}, "
+ f"{img_id + 1}/{total_len}, elapsed_time: {end_time}.\n"
+ )
+
+
+
+
+if __name__ == "__main__":
+ args = parser_args()
+ seqs_str = '''MOT20-01
+ MOT20-02
+ MOT20-03
+ MOT20-05
+ '''
+ image_inference(args.pipeline_path, cfg.STREAM_NAME.encode("utf-8"), args.img_path,
+ args.infer_result_dir)
diff --git a/official/cv/posenet/modelarts/train_start.py b/official/cv/posenet/modelarts/train_start.py
new file mode 100644
index 0000000000000000000000000000000000000000..421fb309e454892b6d80a271e25dba717d26140d
--- /dev/null
+++ b/official/cv/posenet/modelarts/train_start.py
@@ -0,0 +1,158 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+"""train posenet"""
+import ast
+import argparse
+import os
+import shutil
+import numpy as np
+from mindspore.common import set_seed
+from mindspore import Tensor, load_checkpoint, load_param_into_net, export, context
+from mindspore.context import ParallelMode
+from mindspore.communication.management import init, get_rank
+from mindspore.nn import Adagrad
+from mindspore.train.model import Model
+from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor, TimeMonitor
+import mindspore.common.dtype as ms
+from src.posenet import PoseNet
+from src.config import common_config, KingsCollege, StMarysChurch
+from src.dataset import create_posenet_dataset
+from src.loss import PosenetWithLoss
+
+set_seed(1)
+
+parser = argparse.ArgumentParser(description='Posenet train.')
+parser.add_argument("--run_distribute", type=ast.literal_eval, default=False, help="Run distribute, default is false.")
+parser.add_argument('--dataset', type=str, default='KingsCollege',
+ choices=['KingsCollege', 'StMarysChurch'], help='Name of dataset.')
+parser.add_argument('--device_num', type=int, default=1, help='Number of device.')
+# 妯″瀷杈撳嚭鐩綍
+parser.add_argument('--train_url', type=str, default='', help='the path model saved')
+# 鏁版嵁闆嗙洰褰�
+parser.add_argument('--data_url', type=str, default='', help='the training data')
+# 鎶藉彇鍑烘潵鐨勮秴鍙傞厤缃�
+parser.add_argument('--pre_trained', type=ast.literal_eval, default=False, help='Pretrained checkpoint path')
+parser.add_argument('--device_id', type=int, default=None, help='device id of GPU or Ascend. (Default: None)')
+parser.add_argument('--device_target', type=str, default='Ascend', choices=("Ascend", "GPU", "CPU"),
+ help="Device target, support Ascend, GPU and CPU.")
+parser.add_argument('--max_steps', type=int, default=30000, help='max_steps')
+parser.add_argument('--save_checkpoint_epochs', type=int, default=5, help='save_checkpoint_epochs')
+parser.add_argument('--keep_checkpoint_max', type=int, default=10, help='keep_checkpoint_max')
+parser.add_argument('--save_checkpoint', type=ast.literal_eval, default=True, help='save_checkpoint')
+parser.add_argument("--file_name", type=str, default="posenet", help="output file name.")
+parser.add_argument('--is_modelarts', type=ast.literal_eval, default=True, help='Train in Modelarts.')
+args_opt = parser.parse_args()
+CACHE_TRAINING_URL = "/cache/training/"
+CACHE = "/cache/"
+src = "/"
+local_data_path = '/cache/data/'
+if not os.path.isdir(CACHE_TRAINING_URL):
+ os.makedirs(CACHE_TRAINING_URL)
+
+if __name__ == '__main__':
+ cfg = common_config
+ if args_opt.dataset == "KingsCollege":
+ dataset_cfg = KingsCollege
+ elif args_opt.dataset == "StMarysChurch":
+ dataset_cfg = StMarysChurch
+
+ device_target = args_opt.device_target
+ context.set_context(mode=context.GRAPH_MODE, device_target=device_target)
+ if args_opt.run_distribute:
+ if device_target == "Ascend":
+ device_id = int(os.getenv('DEVICE_ID'))
+ context.set_context(device_id=device_id, enable_auto_mixed_precision=True)
+ context.set_auto_parallel_context(parallel_mode=ParallelMode.DATA_PARALLEL,
+ gradients_mean=True,
+ auto_parallel_search_mode="recursive_programming")
+ init()
+ elif device_target == "GPU":
+ init()
+ context.set_auto_parallel_context(device_num=args_opt.device_num,
+ parallel_mode=ParallelMode.DATA_PARALLEL,
+ gradients_mean=True,
+ auto_parallel_search_mode="recursive_programming")
+ else:
+ if args_opt.device_id is not None:
+ context.set_context(device_id=args_opt.device_id)
+ else:
+ context.set_context(device_id=cfg.device_id)
+
+ train_dataset_path = dataset_cfg.dataset_path
+ if args_opt.is_modelarts:
+ import moxing as mox
+ mox.file.copy_parallel(args_opt.data_url, CACHE)
+ if args_opt.dataset == "KingsCollege":
+ mindrecord_file_name = "KingsCollege_posenet_train.mindrecord"
+ elif args_opt.dataset == "StMarysChurch":
+ mindrecord_file_name = "StMarysChurch_posenet_train.mindrecord"
+ mindrecord_file = os.path.join(CACHE, mindrecord_file_name)
+ dataset = create_posenet_dataset(mindrecord_file, batch_size=dataset_cfg.batch_size,
+ device_num=args_opt.device_num, is_training=True)
+ step_per_epoch = dataset.get_dataset_size()
+
+ net_with_loss = PosenetWithLoss(args_opt.pre_trained)
+ opt = Adagrad(params=net_with_loss.trainable_params(),
+ learning_rate=dataset_cfg.lr_init,
+ weight_decay=dataset_cfg.weight_decay)
+ model = Model(net_with_loss, optimizer=opt)
+
+ time_cb = TimeMonitor(data_size=step_per_epoch)
+ loss_cb = LossMonitor()
+ cb = [time_cb, loss_cb]
+ if args_opt.save_checkpoint:
+ config_ck = CheckpointConfig(save_checkpoint_steps=args_opt.save_checkpoint_epochs * step_per_epoch,
+ keep_checkpoint_max=args_opt.keep_checkpoint_max)
+ if args_opt.is_modelarts:
+ save_checkpoint_path = CACHE_TRAINING_URL
+ if args_opt.device_num == 1:
+ ckpt_cb = ModelCheckpoint(prefix='train_posenet_' + args_opt.dataset,
+ directory=save_checkpoint_path,
+ config=config_ck)
+ cb += [ckpt_cb]
+ if args_opt.device_num > 1 and get_rank() % 8 == 0:
+ ckpt_cb = ModelCheckpoint(prefix='train_posenet_' + args_opt.dataset,
+ directory=save_checkpoint_path,
+ config=config_ck)
+ cb += [ckpt_cb]
+ else:
+ save_checkpoint_path = cfg.checkpoint_dir
+ if not os.path.isdir(save_checkpoint_path):
+ os.makedirs(save_checkpoint_path)
+
+ if args_opt.device_num == 1:
+ ckpt_cb = ModelCheckpoint(prefix='train_posenet_' + args_opt.dataset,
+ directory=save_checkpoint_path,
+ config=config_ck)
+ cb += [ckpt_cb]
+ if args_opt.device_num > 1 and get_rank() % 8 == 0:
+ ckpt_cb = ModelCheckpoint(prefix='train_posenet_' + args_opt.dataset,
+ directory=save_checkpoint_path,
+ config=config_ck)
+ cb += [ckpt_cb]
+
+ epoch_size = args_opt.max_steps // args_opt.device_num // step_per_epoch
+ model.train(1, dataset, callbacks=cb)
+
+ net = PoseNet()
+ file_name1 = "train_posenet_KingsCollege-1_16.ckpt"
+ assert cfg.checkpoint_dir is not None, "cfg.checkpoint_dir is None."
+ param_dict = load_checkpoint(os.path.join(CACHE_TRAINING_URL, file_name1))
+ load_param_into_net(net, param_dict)
+ input_arr = Tensor(np.ones([1, 3, 224, 224]), ms.float32)
+ export(net, input_arr, file_name=args_opt.file_name, file_format='AIR')
+ shutil.copy('posenet.air', CACHE_TRAINING_URL)
+ if args_opt.is_modelarts:
+ mox.file.copy_parallel(src_url=CACHE_TRAINING_URL, dst_url=args_opt.train_url)
diff --git a/official/cv/posenet/scripts/docker_start.sh b/official/cv/posenet/scripts/docker_start.sh
new file mode 100644
index 0000000000000000000000000000000000000000..e39553192b435f70dae6aa6b6adbfd6ffe901b40
--- /dev/null
+++ b/official/cv/posenet/scripts/docker_start.sh
@@ -0,0 +1,35 @@
+#!/bin/bash
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.mitations under the License.
+
+docker_image=$1
+data_dir=$2
+model_dir=$3
+
+docker run -it --ipc=host \
+ --device=/dev/davinci0 \
+ --device=/dev/davinci1 \
+ --device=/dev/davinci2 \
+ --device=/dev/davinci3 \
+ --device=/dev/davinci4 \
+ --device=/dev/davinci5 \
+ --device=/dev/davinci6 \
+ --device=/dev/davinci7 \
+ --device=/dev/davinci_manager \
+ --device=/dev/devmm_svm --device=/dev/hisi_hdc \
+ -v /usr/local/Ascend/driver:/usr/local/Ascend/driver \
+ -v /usr/local/Ascend/add-ons/:/usr/local/Ascend/add-ons/ \
+ -v ${model_dir}:${model_dir} \
+ -v ${data_dir}:${data_dir} \
+ -v /root/ascend/log:/root/ascend/log ${docker_image} /bin/bash
\ No newline at end of file