diff --git a/official/cv/MCNN/infer/Dockerfile b/official/cv/MCNN/infer/Dockerfile
new file mode 100644
index 0000000000000000000000000000000000000000..e413a3d0274e444b03fd1d72af160025327eb6a6
--- /dev/null
+++ b/official/cv/MCNN/infer/Dockerfile
@@ -0,0 +1,24 @@
+ARG FROM_IMAGE_NAME
+FROM ${FROM_IMAGE_NAME}
+
+# 閰嶇疆闀滃儚浠ｇ悊
+ENV http_proxy="http://192.168.88.254:8080"
+ENV https_proxy="http://192.168.88.254:8080"
+
+# 娣诲姞鐢ㄦ埛浠ュ強鐢ㄦ埛缁� username ID涓哄綋鍓嶇敤鎴�
+RUN useradd -d /home/hwMindX -u 9000 -m -s /bin/bash hwMindX && \
+ useradd -d /home/HwHiAiUser -u 1000 -m -s /bin/bash HwHiAiUser && \
+ useradd -d /home/sjtu_liu -u 1001 -m -s /bin/bash sjtu_liu -g HwHiAiUser && \
+ usermod -a -G HwHiAiUser hwMindX
+# 娣诲姞Python绗﹀彿閾炬帴
+RUN ln -s /usr/local/python3.7.5/bin/python3.7 /usr/bin/python
+# 瀹夎鐩稿叧渚濊禆鍖咃紝鏍规嵁瀹為檯妯″瀷渚濊禆淇敼
+RUN apt-get update && \
+ apt-get install libglib2.0-dev -y || \
+ rm -rf /var/lib/dpkg/info && \
+ mkdir /var/lib/dpkg/info && \
+ apt-get install libglib2.0-dev dos2unix -y && \
+ pip install pytest-runner==5.3.0
+# 瀹夎Python渚濊禆鍖咃紝鏍规嵁瀹為檯妯″瀷渚濊禆淇敼
+COPY requirements.txt .
+RUN pip3.7 install -r requirements.txt
\ No newline at end of file
diff --git a/official/cv/MCNN/infer/README.md b/official/cv/MCNN/infer/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..5eb3bcebc8cfde7862f540647146dfea6796dd31
--- /dev/null
+++ b/official/cv/MCNN/infer/README.md
@@ -0,0 +1,658 @@
+# MCNN妯″瀷浜や粯浠�-浼楁櫤
+
+## 浜や粯浠跺熀鏈俊鎭�
+
+**鍙戝竷鑰咃紙Publisher锛�**锛欻uawei
+
+**搴旂敤棰嗗煙锛圓pplication Domain锛�**锛欳rowd Counting
+
+**鐗堟湰锛圴ersion锛�**锛�1.1
+
+**淇敼鏃堕棿锛圡odified锛�**锛�2020.12.4
+
+**澶у皬锛圫ize锛�**锛�501 KB \(ckpt\)/541 KB \(air\)/916 KB \(om\)
+
+**妗嗘灦锛團ramework锛�**锛歁indSpore
+
+**妯″瀷鏍煎紡锛圡odel Format锛�**锛歝kpt/air/om
+
+**绮惧害锛圥recision锛�**锛歁ixed/FP16
+
+**澶勭悊鍣紙Processor锛�**锛氭槆鑵�910/鏄囪吘310
+
+**搴旂敤绾у埆锛圕ategories锛�**锛歊eleased
+
+Released锛堝彂琛岀増妯″瀷锛夛細鏄囪吘鎺ㄨ崘浣跨敤锛屾敮鎸佽缁冩帹鐞嗙鍒扮娴佺▼銆�
+
+銆怉绫籖esearch; B绫绘€ц兘<1.8鍊嶇敤Official锛孿>1.8鍊嶇敤Benchmark; C绫籖eleased銆�
+
+**鎻忚堪锛圖escription锛�**锛歁CNN鏄竴绉嶅鍒楀嵎绉缁忕綉缁滐紝鍙互浠庡嚑涔庝换浣曡搴﹀噯纭及璁″崟涓浘鍍忎腑鐨勪汉缇ゆ暟閲忋€�
+
+## 姒傝堪
+
+### 绠€杩�
+
+MCNN鍖呭惈涓変釜骞宠CNN锛屽叾婊ゆ尝鍣ㄥ叿鏈変笉鍚屽ぇ灏忕殑灞€閮ㄦ劅鍙楅噹銆備负浜嗙畝鍖栵紝闄や簡杩囨护鍣ㄧ殑澶у皬鍜屾暟閲忎箣澶栵紝鎴戜滑瀵规墍鏈夊垪锛堝嵆conv鈥損ooling鈥揷onv鈥損ooling锛変娇鐢ㄧ浉鍚岀殑缃戠粶缁撴瀯銆傛瘡涓�2脳2鍖哄煙閲囩敤鏈€澶ф睜锛岀敱浜庢牎姝ｇ嚎鎬у崟鍏冿紙ReLU锛夊CNN鍏锋湁鑹ソ鐨勬€ц兘锛屽洜姝ら噰鐢≧eLU浣滀负婵€娲诲嚱鏁般€�
+
+- 鍙傝€冭鏂囷細
+
+ [Yingying Zhang, Desen Zhou, Siqin Chen, Shenghua Gao, Yi Ma. Single-Image Crowd Counting via Multi-Column Convolutional Neural Network](https://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Zhang_Single-Image_Crowd_Counting_CVPR_2016_paper.pdf)
+
+- 鍙傝€冨疄鐜帮細[https://github.com/svishwa/crowdcount-mcnn](https://github.com/svishwa/crowdcount-mcnn)
+
+閫氳繃Git鑾峰彇瀵瑰簲commit\_id鐨勪唬鐮佹柟娉曞涓嬶細
+
+``` python
+git clone {repository_url} # 鍏嬮殕浠撳簱鐨勪唬鐮�
+cd {repository_name} # 鍒囨崲鍒版ā鍨嬬殑浠ｇ爜浠撶洰褰�
+git checkout {branch} # 鍒囨崲鍒板搴斿垎鏀�
+git reset --hard 锝沜ommit_id锝� # 浠ｇ爜璁剧疆鍒板搴旂殑commit_id
+cd 锝沜ode_path锝� # 鍒囨崲鍒版ā鍨嬩唬鐮佹墍鍦ㄨ矾寰勶紝鑻ヤ粨搴撲笅鍙湁璇ユā鍨嬶紝鍒欐棤闇€鍒囨崲
+```
+
+### 榛樿閰嶇疆
+
+- 璁粌闆嗛澶勭悊 :
+
+ 鍘熷鏁版嵁闆嗙殑姣忓紶鍥剧墖灏哄鍚勪笉鐩稿悓
+
+ 棰勫鐞嗗仛鐨勪簨鎯呮槸灏嗚繖浜涘浘鐗囩殑闀垮閮借皟鏁村埌256
+
+- 娴嬭瘯闆嗛澶勭悊 :
+
+ 鍘熷娴嬭瘯闆嗙殑姣忓紶鍥剧墖灏哄鍚勪笉鐩稿悓
+
+ 棰勫鐞嗗仛鐨勪簨鎯呮槸灏嗚繖浜涘浘鐗囩殑闀垮閮借皟鏁村埌1024锛堜负浜嗗拰om妯″瀷瀵瑰簲锛�
+
+- 璁粌瓒呭弬 :
+
+ Batch size : 1
+
+ Learning rate : 0.000028
+
+ Momentum : 0.0
+
+ Epoch_size : 800
+
+ Buffer_size : 1000
+
+ Save_checkpoint_steps : 1
+
+ Keep_checkpoint_max : 10
+
+ Air_name : "mcnn"
+
+### 鏀寔鐗规€�
+
+鏀寔鐨勭壒鎬у寘鎷細1銆佸垎甯冨紡骞惰璁粌銆�
+
+### 鍒嗗竷寮忚缁�
+
+MindSpore鏀寔鏁版嵁骞惰鍙婅嚜鍔ㄥ苟琛屻€傝嚜鍔ㄥ苟琛屾槸MindSpore铻嶅悎浜嗘暟鎹苟琛屻€佹ā鍨嬪苟琛屽強娣峰悎骞惰鐨勪竴绉嶅垎甯冨紡骞惰妯″紡锛屽彲浠ヨ嚜鍔ㄥ缓绔嬩唬浠锋ā鍨嬶紝涓虹敤鎴烽€夋嫨涓€绉嶅苟琛屾ā寮忋€傜浉鍏充唬鐮佺ず渚嬨€�
+
+``` python
+context.set_auto_parallel_context(device_num=args_opt.device_num, parallel_mode=ParallelMode.DATA_PARALLEL, gradients_mean=True)
+```
+
+## 鍑嗗宸ヤ綔
+
+### 鎺ㄧ悊鐜鍑嗗
+
+- 纭欢鐜銆佸紑鍙戠幆澧冨拰杩愯鐜鍑嗗璇峰弬瑙乕銆奀ANN 杞欢瀹夎鎸囧崡](https://support.huawei.com/enterprise/zh/ascend-computing/cann-pid-251168373?category=installation-upgrade)銆嬨€�
+- 瀹夸富鏈轰笂闇€瑕佸畨瑁匘ocker骞剁櫥褰昜Ascend Hub涓績](https://ascendhub.huawei.com/#/home)鑾峰彇闀滃儚銆�
+
+ 褰撳墠妯″瀷鏀寔鐨勯暅鍍忓垪琛ㄥ涓嬭〃鎵€绀恒€�
+
+ **琛� 1** 闀滃儚鍒楄〃
+
+ <a name="zh-cn_topic_0000001205858411_table1519011227314"></a>
+ <table><thead align="left"><tr id="zh-cn_topic_0000001205858411_row0190152218319"><th class="cellrowborder" valign="top" width="55.00000000000001%" id="mcps1.2.4.1.1"><p id="zh-cn_topic_0000001205858411_p1419132211315"><a name="zh-cn_topic_0000001205858411_p1419132211315"></a><a name="zh-cn_topic_0000001205858411_p1419132211315"></a>闀滃儚鍚嶇О</p>
+ </th>
+ <th class="cellrowborder" valign="top" width="20%" id="mcps1.2.4.1.2"><p id="zh-cn_topic_0000001205858411_p75071327115313"><a name="zh-cn_topic_0000001205858411_p75071327115313"></a><a name="zh-cn_topic_0000001205858411_p75071327115313"></a>闀滃儚鐗堟湰</p>
+ </th>
+ <th class="cellrowborder" valign="top" width="25%" id="mcps1.2.4.1.3"><p id="zh-cn_topic_0000001205858411_p1024411406234"><a name="zh-cn_topic_0000001205858411_p1024411406234"></a><a name="zh-cn_topic_0000001205858411_p1024411406234"></a>閰嶅CANN鐗堟湰</p>
+ </th>
+ </tr>
+ </thead>
+ <tbody><tr id="zh-cn_topic_0000001205858411_row71915221134"><td class="cellrowborder" valign="top" width="55.00000000000001%" headers="mcps1.2.4.1.1 "><p id="zh-cn_topic_0000001205858411_p58911145153514"><a name="zh-cn_topic_0000001205858411_p58911145153514"></a><a name="zh-cn_topic_0000001205858411_p58911145153514"></a>ARM/x86鏋舵瀯锛�<a href="https://ascendhub.huawei.com/#/detail/infer-modelzoo" target="_blank" rel="noopener noreferrer">infer-modelzoo</a></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="20%" headers="mcps1.2.4.1.2 "><p id="zh-cn_topic_0000001205858411_p14648161414516"><a name="zh-cn_topic_0000001205858411_p14648161414516"></a><a name="zh-cn_topic_0000001205858411_p14648161414516"></a>21.0.2</p>
+ </td>
+ <td class="cellrowborder" valign="top" width="25%" headers="mcps1.2.4.1.3 "><p id="zh-cn_topic_0000001205858411_p1264815147514"><a name="zh-cn_topic_0000001205858411_p1264815147514"></a><a name="zh-cn_topic_0000001205858411_p1264815147514"></a><a href="https://www.hiascend.com/software/cann/commercial" target="_blank" rel="noopener noreferrer">5.0.2</a></p>
+ </td>
+ </tr>
+ </tbody>
+ </table>
+
+### 婧愮爜浠嬬粛
+
+鑴氭湰鍜岀ず渚嬩唬鐮�
+
+``` python
+/MCNN
+鈹溾攢鈹€ infer # MindX楂樻€ц兘棰勮缁冩ā鍨嬫柊澧�
+鈹� 鈹溾攢鈹€ convert # 杞崲om妯″瀷鍛戒护
+鈹� 鈹� 鈹斺攢鈹€convert_om.sh
+鈹� 鈹溾攢鈹€ model # 瀛樻斁妯″瀷
+鈹� 鈹溾攢鈹€ test_data # 瀛樻斁鏁版嵁闆�
+鈹� 鈹溾攢鈹€ mxbase # 鍩轰簬mxbase鎺ㄧ悊
+鈹� 鈹� 鈹溾攢鈹€ src
+鈹� 鈹� 鈹� 鈹溾攢鈹€ Mcnn.cpp
+鈹� 鈹� 鈹� 鈹溾攢鈹€ Mcnn.h
+鈹� 鈹� 鈹� 鈹斺攢鈹€ main.cpp
+鈹� 鈹� 鈹溾攢鈹€ output # 瀛樻斁缁撴灉璺緞
+鈹� 鈹� 鈹溾攢鈹€ CMakeLists.txt
+鈹� 鈹� 鈹斺攢鈹€ build.sh
+鈹� 鈹斺攢鈹€ sdk # 鍩轰簬sdk.run鍖呮帹鐞嗭紱濡傛灉鏄疌++瀹炵幇锛屽瓨鏀捐矾寰勪竴鏍�
+鈹� 鈹� 鈹溾攢鈹€ out # 瀛樻斁缁撴灉璺緞
+鈹� 鈹� 鈹溾攢鈹€ main.py
+鈹� 鈹� 鈹溾攢鈹€ mcnn.pipeline
+鈹� 鈹� 鈹斺攢鈹€ run.sh
+鈹� 鈹斺攢鈹€docker_start_infer.sh # 鍚姩瀹瑰櫒鑴氭湰
+```
+
+## 鎺ㄧ悊
+
+- **[鍑嗗鎺ㄧ悊鏁版嵁](#鍑嗗鎺ㄧ悊鏁版嵁.md)**
+
+- **[妯″瀷杞崲](#妯″瀷杞崲.md)**
+
+- **[mxBase鎺ㄧ悊](#mxBase鎺ㄧ悊.md)**
+
+- **[MindX SDK鎺ㄧ悊](#MindX-SDK鎺ㄧ悊.md)**
+
+### 鍑嗗鎺ㄧ悊鏁版嵁
+
+鍑嗗妯″瀷杞崲鍜屾ā鍨嬫帹鐞嗘墍闇€鐩綍鍙婃暟鎹€�
+
+1. 涓嬭浇婧愮爜鍖呫€�
+
+ 鍗曞嚮鈥滀笅杞芥ā鍨嬭剼鏈€濆拰鈥滀笅杞芥ā鍨嬧€濓紝涓嬭浇鎵€闇€杞欢鍖呫€�
+
+2. 灏嗘簮鐮佷笂浼犺嚦鎺ㄧ悊鏈嶅姟鍣ㄤ换鎰忕洰褰曞苟瑙ｅ帇锛堝锛氣€�/home/MCNN鈥滐級銆傘€愩€愩€愭坊鍔犱互涓嬪懡浠わ紝鏈€缁堜笅杞芥ā鍨嬭剼鏈�"姝ラ寰楀埌鐨勬枃浠堕渶瑕佽繘琛屾牸寮忚浆鎹€€戙€戙€�
+
+ ```
+ #鍦ㄧ幆澧冧笂鎵ц
+ unzip MCNN_Mindspore_{version}_code.zip
+ cd {code_unzip_path}/MCNN_MindSpore_{version}_code/infer && dos2unix `find .`
+ ```
+
+3. 鍑嗗鏁版嵁銆�
+
+ 鐢变簬鍚庣画鎺ㄧ悊鍧囧湪瀹瑰櫒涓繘琛岋紝鍥犳闇€瑕佹妸鐢ㄤ簬鎺ㄧ悊鐨勫浘鐗囥€佹暟鎹泦銆佹ā鍨嬫枃浠躲€佷唬鐮佺瓑鍧囨斁鍦ㄥ悓涓€鏁版嵁璺緞涓紝鍚庣画绀轰緥灏嗕互鈥�/home/MCNN鈥滀负渚嬨€�
+
+ ```
+ ..
+ /MCNN
+ 鈹溾攢鈹€ infer # MindX楂樻€ц兘棰勮缁冩ā鍨嬫柊澧�
+ 鈹� 鈹溾攢鈹€ convert # 杞崲om妯″瀷鍛戒护
+ 鈹� 鈹� 鈹斺攢鈹€convert_om.sh
+ 鈹� 鈹溾攢鈹€ model # 瀛樻斁妯″瀷
+ 鈹� 鈹溾攢鈹€ test_data # 瀛樻斁鏁版嵁闆�
+ 鈹� 鈹溾攢鈹€ mxbase # 鍩轰簬mxbase鎺ㄧ悊
+ 鈹� 鈹� 鈹溾攢鈹€ src
+ 鈹� 鈹� 鈹� 鈹溾攢鈹€ Mcnn.cpp
+ 鈹� 鈹� 鈹� 鈹溾攢鈹€ Mcnn.h
+ 鈹� 鈹� 鈹� 鈹斺攢鈹€ main.cpp
+ 鈹� 鈹� 鈹溾攢鈹€ output # 瀛樻斁缁撴灉璺緞
+ 鈹� 鈹� 鈹溾攢鈹€ CMakeLists.txt
+ 鈹� 鈹� 鈹斺攢鈹€ build.sh
+ 鈹� 鈹斺攢鈹€ sdk # 鍩轰簬sdk.run鍖呮帹鐞嗭紱濡傛灉鏄疌++瀹炵幇锛屽瓨鏀捐矾寰勪竴鏍�
+ 鈹� 鈹� 鈹溾攢鈹€ out # 瀛樻斁缁撴灉璺緞
+ 鈹� 鈹� 鈹溾攢鈹€ main.py
+ 鈹� 鈹� 鈹溾攢鈹€ mcnn.pipeline
+ 鈹� 鈹� 鈹斺攢鈹€ run.sh
+ 鈹� 鈹斺攢鈹€docker_start_infer.sh # 鍚姩瀹瑰櫒鑴氭湰
+ ```
+
+ AIR妯″瀷鍙€氳繃鈥滄ā鍨嬭缁冣€濆悗杞崲鐢熸垚鎴栭€氳繃鈥滀笅杞芥ā鍨嬧€濊幏鍙栥€�
+
+ 灏唖hanghaitechA鏁版嵁闆唗est_data鏀惧埌鈥�/MCNN/infer/鈥濈洰褰曚笅銆�
+
+ 鏁版嵁闆嗛摼鎺�: https://pan.baidu.com/s/185jBeL91R85OUcbeARP9Sg 鎻愬彇鐮�: 5q9v
+
+4. 鍑嗗mxbase鐨勮緭鍑虹洰褰�/output銆傝鐩綍涓嬪瓨鍌ㄦ帹鐞嗙殑涓棿缁撴灉銆�
+
+ ```
+ #鍦ㄧ幆澧冧笂鎵ц
+ cd MCNN_Mindspore_{version}_code/infer/mxbase/
+ mkdir output
+ ```
+
+5. 鍚姩瀹瑰櫒銆�
+
+ 杩涘叆鈥渋nfer鈥滅洰褰曪紝鎵ц浠ヤ笅鍛戒护锛屽惎鍔ㄥ鍣ㄣ€�
+
+ bash docker_start_infer.sh docker_image data_path
+
+ **琛� 2** 鍙傛暟璇存槑
+
+ <a name="table8122633182517"></a>
+ <table><thead align="left"><tr id="row16122113320259"><th class="cellrowborder" valign="top" width="40%" id="mcps1.2.3.1.1"><p id="p16122163382512"><a name="p16122163382512"></a><a name="p16122163382512"></a>鍙傛暟</p>
+ </th>
+ <th class="cellrowborder" valign="top" width="60%" id="mcps1.2.3.1.2"><p id="p8122103342518"><a name="p8122103342518"></a><a name="p8122103342518"></a>璇存槑</p>
+ </th>
+ </tr>
+ </thead>
+ <tbody><tr id="row11225332251"><td class="cellrowborder" valign="top" width="40%" headers="mcps1.2.3.1.1 "><p id="p712210339252"><a name="p712210339252"></a><a name="p712210339252"></a><em id="i121225338257"><a name="i121225338257"></a><a name="i121225338257"></a>docker_image</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="60%" headers="mcps1.2.3.1.2 "><p id="p0122733152514"><a name="p0122733152514"></a><a name="p0122733152514"></a>鎺ㄧ悊闀滃儚鍚嶇О锛屾牴鎹疄闄呭啓鍏ャ€�</p>
+ </td>
+ </tr>
+ <tr id="row5835194195611"><td class="cellrowborder" valign="top" width="40%" headers="mcps1.2.3.1.1 "><p id="p59018537424"><a name="p59018537424"></a><a name="p59018537424"></a>data_path</p>
+ </td>
+ <td class="cellrowborder" valign="top" width="60%" headers="mcps1.2.3.1.2 "><p id="p1390135374214"><a name="p1390135374214"></a><a name="p1390135374214"></a>鏁版嵁闆嗚矾寰勩€�</p>
+ </td>
+ </tr>
+ </tbody>
+ </table>
+
+ 鍚姩瀹瑰櫒鏃朵細灏嗘帹鐞嗚姱鐗囧拰鏁版嵁璺緞鎸傝浇鍒板鍣ㄤ腑銆傚彲鏍规嵁闇€瑕侀€氳繃淇敼**docker\_start\_infer.sh**鐨刣evice鏉ユ寚瀹氭寕杞界殑鎺ㄧ悊鑺墖銆�
+
+ ```
+ docker run -it \
+ --device=/dev/davinci0 \ # 鍙牴鎹渶瑕佷慨鏀规寕杞界殑npu璁惧
+ --device=/dev/davinci_manager \
+
+ # 璇存槑锛歁indX SDK寮€鍙戝浠讹紙mxManufacture锛夊凡瀹夎鍦ㄥ熀纭€闀滃儚涓紝瀹夎璺緞锛氣€�/usr/local/sdk\_home鈥溿€�
+ ```
+
+### 妯″瀷杞崲
+
+1. 鍑嗗妯″瀷鏂囦欢銆�
+
+ 鍦╥nfer鐩綍涓嬪垱寤簃odel鐩綍锛屽皢mcnn.air鏀捐嚦姝ょ洰褰曚笅銆�
+
+ ```
+ cd MCNN_Mindspore_{version}_code/infer/
+ mkdir model
+ ```
+
+ 灏唌cnn.air鏀捐嚦infer/model/涓嬨€�
+
+2. 妯″瀷杞崲銆�
+
+ 杩涘叆鈥渋nfer/mcnn/convert鈥滅洰褰曡繘琛屾ā鍨嬭浆鎹紝**convert_om.sh**鑴氭湰鏂囦欢涓紝閰嶇疆鐩稿叧鍙傛暟銆�
+
+ ```
+ atc \
+ --model=${model} \
+ --output=${output} \
+ --soc_version=${soc_version} \
+ --input_shape=${input_shape} \
+ --framework=1 \
+ --input_format=NCHW
+ ```
+
+ 杞崲鍛戒护濡備笅銆�
+
+ ```
+ bash convert_om.sh --model=[model_path] --output=[output_model_name]
+ # model_path涓篴ir妯″瀷璺緞 output_model_name涓烘柊妯″瀷鐨勫悕瀛�
+ # 渚嬪瓙濡備笅锛�
+ bash convert_om.sh --model=../model/mcnn.air --output=../model/mcnn
+ ```
+
+ **琛� 1** 鍙傛暟璇存槑
+
+ <a name="table15982121511203"></a>
+ <table><thead align="left"><tr id="row1598241522017"><th class="cellrowborder" valign="top" width="40%" id="mcps1.2.3.1.1"><p id="p189821115192014"><a name="p189821115192014"></a><a name="p189821115192014"></a>鍙傛暟</p>
+ </th>
+ <th class="cellrowborder" valign="top" width="60%" id="mcps1.2.3.1.2"><p id="p1982161512206"><a name="p1982161512206"></a><a name="p1982161512206"></a>璇存槑</p>
+ </th>
+ </tr>
+ </thead>
+ <tbody><tr id="row0982101592015"><td class="cellrowborder" valign="top" width="40%" headers="mcps1.2.3.1.1 "><p id="p1598231542020"><a name="p1598231542020"></a><a name="p1598231542020"></a>model_path</p>
+ </td>
+ <td class="cellrowborder" valign="top" width="60%" headers="mcps1.2.3.1.2 "><p id="p598231511200"><a name="p598231511200"></a><a name="p598231511200"></a>AIR鏂囦欢璺緞銆�</p>
+ </td>
+ </tr>
+ <tr id="row109831315132011"><td class="cellrowborder" valign="top" width="40%" headers="mcps1.2.3.1.1 "><p id="p598319158204"><a name="p598319158204"></a><a name="p598319158204"></a>output_model_name</p>
+ </td>
+ <td class="cellrowborder" valign="top" width="60%" headers="mcps1.2.3.1.2 "><p id="p1898316155207"><a name="p1898316155207"></a><a name="p1898316155207"></a>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�</p>
+ </td>
+ </tr>
+ </tbody>
+ </table>
+
+### mxBase鎺ㄧ悊
+
+鍦ㄥ鍣ㄥ唴鐢╩xBase杩涜鎺ㄧ悊銆�
+
+1. 缂栬瘧宸ョ▼銆�
+
+ 杩涘叆/mxbase璺緞涓�
+
+ ```
+ bash build.sh
+ ```
+
+2. 杩愯鎺ㄧ悊鏈嶅姟銆�
+
+ ```
+ ./Mcnn [model_path] [data_path] [label_path] [output_path]
+ # model_path涓簅m妯″瀷璺緞 data_path涓烘暟鎹泦鏁版嵁閮ㄥ垎璺緞 label_path涓烘暟鎹泦鏍囩閮ㄥ垎璺緞 output_path涓鸿緭鍑鸿矾寰�
+ # 渚嬪瓙濡備笅锛�
+ ./Mcnn ../model/mcnn.om ../test_data/images/ ../test_data/ground_truth_csv/ ./output
+ ```
+
+3. 瑙傚療缁撴灉銆�
+
+ 鎺ㄧ悊缁撴灉鐨勫弬鏁拌В閲婏細
+
+ datasize: 杈撳叆鏁版嵁澶у皬
+
+ output_size: 杈撳嚭鏁版嵁澶у皬
+
+ output0_datatype: 杈撳嚭鏁版嵁绫诲瀷
+
+ output0_shape: 杈撳嚭鏁版嵁鐨勫舰鐘�
+
+ output0_bytesize: 杈撳嚭鏁版嵁瀛楄妭绫诲瀷
+
+ 鎺ヤ笅鏉ョ殑鏄祴璇曞浘鐗囩殑id銆侀娴嬪€笺€佺湡瀹炲€笺€�
+
+ 鏈€鍚庤緭鍑虹殑鏄暣涓祴璇曢泦鐨勭簿搴︺€�
+
+### MindX SDK鎺ㄧ悊
+
+1. 妫€鏌ョ幆澧冦€�
+
+ 纭繚mcnn.om妯″瀷鍦�/MCNN/infer/model涓嬨€�
+
+2. 淇敼閰嶇疆鏂囦欢銆�
+
+ 1. 淇敼pipeline鏂囦欢銆�
+
+ ```
+ {
+ "mcnn_opencv": {
+ "appsrc0": {
+ "factory": "appsrc",
+ "next": "mxpi_tensorinfer0"
+ },
+ "mxpi_tensorinfer0": {
+ "props": {
+ "dataSource": "appsrc0",
+ "modelPath": "../model/mcnn.om", //姝ゅ鏄綘鐨勬ā鍨嬪瓨鏀捐矾寰�
+ "waitingTime": "2000"
+ },
+ "factory": "mxpi_tensorinfer",
+ "next": "appsink0"
+ },
+ "appsink0": {
+ "factory": "appsink"
+ }
+ }
+ }
+ ```
+
+3. 鎵撳紑鎬ц兘缁熻寮€鍏炽€傚皢"enable_ps"鍙傛暟璁剧疆涓簍rue锛�"ps_interval_time"鍙傛暟璁剧疆涓�6銆�
+
+ vim ${MX_SDK_HOME}/config/sdk.conf
+
+ ```
+ # Mindx SDK configuration file
+ # whether to enable performance statistics锛宒efault is false [dynamic config]
+ enable_ps=true
+ ...
+ ps_interval_time=6
+ ...
+ ```
+
+4. 杩愯鎺ㄧ悊鏈嶅姟銆�
+
+ 1. 鎵ц鎺ㄧ悊銆�
+
+ 杩涘叆/sdk鍚庯紝杩愯浠ヤ笅鍛戒护锛�
+
+ ```
+ bash run.sh [input_dir] [gt_dir]
+ # input_dir涓烘暟鎹泦鏁版嵁閮ㄥ垎璺緞 gt_dir涓烘暟鎹泦鏍囩閮ㄥ垎璺緞
+ # 渚嬪锛�
+ bash run.sh ../test_data/images/ ../test_data/ground_truth_csv/
+ ```
+
+ 2. 鏌ョ湅鎺ㄧ悊缁撴灉.
+
+5. 鎵ц绮惧害鍜屾€ц兘娴嬭瘯銆�
+
+6. 鍦ㄦ棩蹇楃洰褰曗€�$ {MX_SDK_HOME}/logs/鈥濇煡鐪嬫€ц兘缁熻缁撴灉銆�
+
+ ```
+ performance-statistics.log.e2e.xxx
+ performance-statistics.log.plugin.xxx
+ performance-statistics.log.tpr.xxx
+ ```
+
+ 鍏朵腑e2e鏃ュ織缁熻绔埌绔椂闂�,plugin鏃ュ織缁熻鍗曟彃浠舵椂闂淬€�
+
+## 鍦∕odelArts涓婂簲鐢�
+
+- **[鍒涘缓OBS妗禲(#鍒涘缓OBS妗�.md)**
+
+- **[鍒涘缓绠楁硶锛堥€傜敤浜嶮indSpore鍜孴ensorFlow锛塢(#鍒涘缓绠楁硶锛堥€傜敤浜嶮indSpore鍜孴ensorFlow锛�.md)**
+
+- **[鍒涘缓璁粌浣滀笟](#鍒涘缓璁粌浣滀笟.md)**
+
+- **[鏌ョ湅璁粌浠诲姟鏃ュ織](#鏌ョ湅璁粌浠诲姟鏃ュ織.md)**
+
+- **[杩佺Щ瀛︿範](#杩佺Щ瀛︿範.md)**
+
+### 鍒涘缓OBS妗�
+
+1.鐧诲綍[OBS绠＄悊鎺у埗鍙癩(https://storage.huaweicloud.com/obs)锛屽垱寤篛BS妗躲€傚叿浣撹鍙傝[鍒涘缓妗禲(https://support.huaweicloud.com/usermanual-obs/obs_03_0306.html)绔犺妭銆備緥濡傦紝鍒涘缓鍚嶇О涓衡€淢CNN鈥濈殑OBS妗躲€�
+
+鍒涘缓妗剁殑鍖哄煙闇€瑕佷笌ModelArts鎵€鍦ㄧ殑鍖哄煙涓€鑷淬€備緥濡傦細褰撳墠ModelArts鍦ㄥ崕鍖�-鍖椾含鍥涘尯鍩燂紝鍦ㄥ璞″瓨鍌ㄦ湇鍔″垱寤烘《鏃讹紝璇烽€夋嫨鍗庡寳-鍖椾含鍥涖€�
+
+鍒涘缓鐢ㄤ簬瀛樻斁鏁版嵁鐨勬枃浠跺す锛屽叿浣撹鍙傝[鏂板缓鏂囦欢澶筣(https://support.huaweicloud.com/usermanual-obs/obs_03_0316.html)绔犺妭銆備緥濡傦紝鍦ㄥ凡鍒涘缓鐨凮BS妗朵腑MCNN椤圭洰閲屽垱寤篸ata銆丩OG銆乼rain_output
+
+鐩綍缁撴瀯璇存槑锛�
+
+- MCNN锛氬瓨鏀捐缁冭剼鏈洰褰�
+- data锛氬瓨鏀捐缁冩暟鎹泦鐩綍
+- LOG锛氬瓨鏀捐缁冩棩蹇楃洰褰�
+- train_output锛氬瓨鏀捐缁僣kpt鏂囦欢鍜屽喕缁撶殑AIR妯″瀷锛坥utput涓璻esult鏂囦欢澶逛腑锛�
+
+鏁版嵁闆唖hanghaitechA浼犺嚦鈥渄ata鈥濈洰褰曘€�
+
+鏁版嵁闆嗛摼鎺�: https://pan.baidu.com/s/185jBeL91R85OUcbeARP9Sg 鎻愬彇鐮�: 5q9v
+
+娉ㄦ剰锛氶渶瑕佸皢modlearts涓嬬殑start_train.py绉昏嚦鏍圭洰褰曚笅杩涜璁粌銆�
+
+### 鍒涘缓绠楁硶锛堥€傜敤浜嶮indSpore鍜孴ensorFlow锛�
+
+1. 浣跨敤鍗庝负浜戝笎鍙风櫥褰昜ModelArts绠＄悊鎺у埗鍙癩(https://console.huaweicloud.com/modelarts)锛屽湪宸︿晶瀵艰埅鏍忎腑閫夋嫨鈥滅畻娉曠鐞嗏€濄€�
+2. 鍦ㄢ€滄垜鐨勭畻娉曠鐞嗏€濈晫闈紝鍗曞嚮宸︿笂瑙掆€滃垱寤衡€濓紝杩涘叆鈥滃垱寤虹畻娉曗€濋〉闈€€�
+3. 鍦ㄢ€滃垱寤虹畻娉曗€濋〉闈紝濉啓鐩稿叧鍙傛暟锛岀劧鍚庡崟鍑烩€滄彁浜も€濄€�
+ 1. 璁剧疆绠楁硶鍩烘湰淇℃伅銆�
+
+ 2. 璁剧疆鈥滃垱寤烘柟寮忊€濅负鈥滆嚜瀹氫箟鑴氭湰鈥濄€�
+
+ 鐢ㄦ埛闇€鏍规嵁瀹為檯绠楁硶浠ｇ爜鎯呭喌璁剧疆鈥淎I寮曟搸鈥濄€佲€滀唬鐮佺洰褰曗€濆拰鈥滃惎鍔ㄦ枃浠垛€濄€傞€夋嫨鐨凙I寮曟搸鍜岀紪鍐欑畻娉曚唬鐮佹椂閫夋嫨鐨勬鏋跺繀椤讳竴鑷淬€備緥濡傜紪鍐欑畻娉曚唬鐮佷娇鐢ㄧ殑鏄疢indSpore锛屽垯鍦ㄥ垱寤虹畻娉曟椂涔熻閫夋嫨MindSpore銆�
+
+ **琛� 1**
+
+ <a name="table09972489125"></a>
+ <table><thead align="left"><tr id="row139978484125"><th class="cellrowborder" valign="top" width="29.470000000000002%" id="mcps1.2.3.1.1"><p id="p16997114831219"><a name="p16997114831219"></a><a name="p16997114831219"></a><em id="i1199720484127"><a name="i1199720484127"></a><a name="i1199720484127"></a>鍙傛暟鍚嶇О</em></p>
+ </th>
+ <th class="cellrowborder" valign="top" width="70.53%" id="mcps1.2.3.1.2"><p id="p199976489122"><a name="p199976489122"></a><a name="p199976489122"></a><em id="i9997154816124"><a name="i9997154816124"></a><a name="i9997154816124"></a>璇存槑</em></p>
+ </th>
+ </tr>
+ </thead>
+ <tbody><tr id="row11997124871210"><td class="cellrowborder" valign="top" width="29.470000000000002%" headers="mcps1.2.3.1.1 "><p id="p1299734820121"><a name="p1299734820121"></a><a name="p1299734820121"></a><em id="i199764819121"><a name="i199764819121"></a><a name="i199764819121"></a>AI寮曟搸</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="70.53%" headers="mcps1.2.3.1.2 "><p id="p1899720481122"><a name="p1899720481122"></a><a name="p1899720481122"></a><em id="i9997848191217"><a name="i9997848191217"></a><a name="i9997848191217"></a>Ascend-Powered-Engine锛宮indspore_1.3.0-cann_5.0.2</em></p>
+ </td>
+ </tr>
+ <tr id="row5997348121218"><td class="cellrowborder" valign="top" width="29.470000000000002%" headers="mcps1.2.3.1.1 "><p id="p139971748141218"><a name="p139971748141218"></a><a name="p139971748141218"></a><em id="i1199784811220"><a name="i1199784811220"></a><a name="i1199784811220"></a>浠ｇ爜鐩綍</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="70.53%" headers="mcps1.2.3.1.2 "><p id="p2099724810127"><a name="p2099724810127"></a><a name="p2099724810127"></a><em id="i17997144871212"><a name="i17997144871212"></a><a name="i17997144871212"></a>绠楁硶浠ｇ爜瀛樺偍鐨凮BS璺緞銆備笂浼犺缁冭剼鏈紝濡傦細/mcnn/MCNN/</em></p>
+ </td>
+ </tr>
+ <tr id="row899794811124"><td class="cellrowborder" valign="top" width="29.470000000000002%" headers="mcps1.2.3.1.1 "><p id="p799714482129"><a name="p799714482129"></a><a name="p799714482129"></a><em id="i399704871210"><a name="i399704871210"></a><a name="i399704871210"></a>鍚姩鏂囦欢</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="70.53%" headers="mcps1.2.3.1.2 "><p id="p13997154831215"><a name="p13997154831215"></a><a name="p13997154831215"></a><em id="i11997648161214"><a name="i11997648161214"></a><a name="i11997648161214"></a>鍚姩鏂囦欢锛氬惎鍔ㄨ缁冪殑python鑴氭湰锛屽锛�/mcnn/MCNN/start_train.py</em></p>
+ <div class="notice" id="note1799734891214"><a name="note1799734891214"></a><a name="note1799734891214"></a><span class="noticetitle"> 椤荤煡锛� </span><div class="noticebody"><p id="p7998194814127"><a name="p7998194814127"></a><a name="p7998194814127"></a><em id="i199987481127"><a name="i199987481127"></a><a name="i199987481127"></a>闇€瑕佹妸modelArts/鐩綍涓嬬殑start.py鍚姩鑴氭湰鎷疯礉鍒版牴鐩綍涓嬨€�</em></p>
+ </div></div>
+ </td>
+ </tr>
+ <tr id="row59981448101210"><td class="cellrowborder" valign="top" width="29.470000000000002%" headers="mcps1.2.3.1.1 "><p id="p19998124812123"><a name="p19998124812123"></a><a name="p19998124812123"></a><em id="i1399864831211"><a name="i1399864831211"></a><a name="i1399864831211"></a>杈撳叆鏁版嵁閰嶇疆</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="70.53%" headers="mcps1.2.3.1.2 "><p id="p139982484129"><a name="p139982484129"></a><a name="p139982484129"></a><em id="i299816484122"><a name="i299816484122"></a><a name="i299816484122"></a>浠ｇ爜璺緞鍙傛暟锛歞ata_url</em></p>
+ </td>
+ </tr>
+ <tr id="row179981948151214"><td class="cellrowborder" valign="top" width="29.470000000000002%" headers="mcps1.2.3.1.1 "><p id="p89981948191220"><a name="p89981948191220"></a><a name="p89981948191220"></a><em id="i599844831217"><a name="i599844831217"></a><a name="i599844831217"></a>杈撳嚭鏁版嵁閰嶇疆</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="70.53%" headers="mcps1.2.3.1.2 "><p id="p599814485120"><a name="p599814485120"></a><a name="p599814485120"></a><em id="i189981748171218"><a name="i189981748171218"></a><a name="i189981748171218"></a>浠ｇ爜璺緞鍙傛暟锛歵rain_url</em></p>
+ </td>
+ </tr>
+ </tbody>
+ </table>
+
+ 3. 濉啓瓒呭弬鏁般€�
+
+ 鍗曞嚮鈥滄坊鍔犺秴鍙傗€濓紝鎵嬪姩娣诲姞瓒呭弬銆傞厤缃唬鐮佷腑鐨勫懡浠よ鍙傛暟鍊硷紝璇锋牴鎹偍缂栧啓鐨勭畻娉曚唬鐮侀€昏緫杩涜濉啓锛岀‘淇濆弬鏁板悕绉板拰浠ｇ爜鐨勫弬鏁板悕绉颁繚鎸佷竴鑷达紝鍙～鍐欏涓弬鏁般€�
+
+ **琛� 2** _瓒呭弬璇存槑_
+
+ <a name="table29981482127"></a>
+ <table><thead align="left"><tr id="row1599894881216"><th class="cellrowborder" valign="top" width="25%" id="mcps1.2.6.1.1"><p id="p89988484121"><a name="p89988484121"></a><a name="p89988484121"></a><em id="i89985485123"><a name="i89985485123"></a><a name="i89985485123"></a>鍙傛暟鍚嶇О</em></p>
+ </th>
+ <th class="cellrowborder" valign="top" width="15%" id="mcps1.2.6.1.2"><p id="p1999114814121"><a name="p1999114814121"></a><a name="p1999114814121"></a><em id="i7999448181212"><a name="i7999448181212"></a><a name="i7999448181212"></a>绫诲瀷</em></p>
+ </th>
+ <th class="cellrowborder" valign="top" width="17%" id="mcps1.2.6.1.3"><p id="p6999124810126"><a name="p6999124810126"></a><a name="p6999124810126"></a><em id="i17999144818126"><a name="i17999144818126"></a><a name="i17999144818126"></a>榛樿鍊�</em></p>
+ </th>
+ <th class="cellrowborder" valign="top" width="18%" id="mcps1.2.6.1.4"><p id="p69992486123"><a name="p69992486123"></a><a name="p69992486123"></a><em id="i1599916488127"><a name="i1599916488127"></a><a name="i1599916488127"></a>鏄惁蹇呭～</em></p>
+ </th>
+ <th class="cellrowborder" valign="top" width="25%" id="mcps1.2.6.1.5"><p id="p1999248121214"><a name="p1999248121214"></a><a name="p1999248121214"></a><em id="i299915481121"><a name="i299915481121"></a><a name="i299915481121"></a>鎻忚堪</em></p>
+ </th>
+ </tr>
+ </thead>
+ <tbody><tr id="row9999134818128"><td class="cellrowborder" valign="top" width="25%" headers="mcps1.2.6.1.1 "><p id="p14999124811212"><a name="p14999124811212"></a><a name="p14999124811212"></a><em id="i39991748101218"><a name="i39991748101218"></a><a name="i39991748101218"></a>batch_size</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="15%" headers="mcps1.2.6.1.2 "><p id="p599924815129"><a name="p599924815129"></a><a name="p599924815129"></a><em id="i8999184811212"><a name="i8999184811212"></a><a name="i8999184811212"></a>int</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="17%" headers="mcps1.2.6.1.3 "><p id="p179992484129"><a name="p179992484129"></a><a name="p179992484129"></a><em id="i1799913488128"><a name="i1799913488128"></a><a name="i1799913488128"></a>1</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="18%" headers="mcps1.2.6.1.4 "><p id="p179991348181213"><a name="p179991348181213"></a><a name="p179991348181213"></a><em id="i20999134812126"><a name="i20999134812126"></a><a name="i20999134812126"></a>鍚�</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="25%" headers="mcps1.2.6.1.5 "><p id="p899916487125"><a name="p899916487125"></a><a name="p899916487125"></a><em id="i99999482127"><a name="i99999482127"></a><a name="i99999482127"></a>璁粌闆嗙殑batch_size銆�</em></p>
+ </td>
+ </tr>
+ <tr id="row14999148161210"><td class="cellrowborder" valign="top" width="25%" headers="mcps1.2.6.1.1 "><p id="p199915488129"><a name="p199915488129"></a><a name="p199915488129"></a><em id="i11999448141216"><a name="i11999448141216"></a><a name="i11999448141216"></a>lr</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="15%" headers="mcps1.2.6.1.2 "><p id="p7999124813124"><a name="p7999124813124"></a><a name="p7999124813124"></a><em id="i7999748151214"><a name="i7999748151214"></a><a name="i7999748151214"></a>float</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="17%" headers="mcps1.2.6.1.3 "><p id="p902049121213"><a name="p902049121213"></a><a name="p902049121213"></a><em id="i100124914123"><a name="i100124914123"></a><a name="i100124914123"></a>0.000028</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="18%" headers="mcps1.2.6.1.4 "><p id="p19004917125"><a name="p19004917125"></a><a name="p19004917125"></a><em id="i208494126"><a name="i208494126"></a><a name="i208494126"></a>鍚�</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="25%" headers="mcps1.2.6.1.5 "><p id="p10134915129"><a name="p10134915129"></a><a name="p10134915129"></a><em id="i101949121214"><a name="i101949121214"></a><a name="i101949121214"></a>璁粌鏃剁殑瀛︿範鐜�.褰撲娇鐢�8鍗¤缁冩椂锛屽涔犵巼涓�0.000028銆�</em></p>
+ </td>
+ </tr>
+ <tr id="row100124911121"><td class="cellrowborder" valign="top" width="25%" headers="mcps1.2.6.1.1 "><p id="p150849131211"><a name="p150849131211"></a><a name="p150849131211"></a><em id="i1101549151218"><a name="i1101549151218"></a><a name="i1101549151218"></a>momentum</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="15%" headers="mcps1.2.6.1.2 "><p id="p19054914124"><a name="p19054914124"></a><a name="p19054914124"></a><em id="i10144919126"><a name="i10144919126"></a><a name="i10144919126"></a>float</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="17%" headers="mcps1.2.6.1.3 "><p id="p6011490123"><a name="p6011490123"></a><a name="p6011490123"></a><em id="i00144917122"><a name="i00144917122"></a><a name="i00144917122"></a>0</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="18%" headers="mcps1.2.6.1.4 "><p id="p301449191215"><a name="p301449191215"></a><a name="p301449191215"></a><em id="i180104910126"><a name="i180104910126"></a><a name="i180104910126"></a>鍚�</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="25%" headers="mcps1.2.6.1.5 "><p id="p1702495127"><a name="p1702495127"></a><a name="p1702495127"></a><em id="i170249181214"><a name="i170249181214"></a><a name="i170249181214"></a>璁粌鏃剁殑鍔ㄩ噺銆�</em></p>
+ </td>
+ </tr>
+ <tr id="row001549161215"><td class="cellrowborder" valign="top" width="25%" headers="mcps1.2.6.1.1 "><p id="p1608498123"><a name="p1608498123"></a><a name="p1608498123"></a><em id="i501049191215"><a name="i501049191215"></a><a name="i501049191215"></a>epoch_size</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="15%" headers="mcps1.2.6.1.2 "><p id="p1064915124"><a name="p1064915124"></a><a name="p1064915124"></a><em id="i20104911127"><a name="i20104911127"></a><a name="i20104911127"></a>int</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="17%" headers="mcps1.2.6.1.3 "><p id="p80164951212"><a name="p80164951212"></a><a name="p80164951212"></a><em id="i190184921219"><a name="i190184921219"></a><a name="i190184921219"></a>800</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="18%" headers="mcps1.2.6.1.4 "><p id="p1811749171212"><a name="p1811749171212"></a><a name="p1811749171212"></a><em id="i161114981216"><a name="i161114981216"></a><a name="i161114981216"></a>鍚�</em></p>
+ </td>
+ <td class="cellrowborder" valign="top" width="25%" headers="mcps1.2.6.1.5 "><p id="p8114941212"><a name="p8114941212"></a><a name="p8114941212"></a><em id="i9174981214"><a name="i9174981214"></a><a name="i9174981214"></a>鎬昏缁冭疆鏁�</em></p>
+ </td>
+ </tr>
+ </tbody>
+ </table>
+
+### 鍒涘缓璁粌浣滀笟
+
+1. 鐧诲綍ModelArts銆�
+2. 鍒涘缓璁粌浣滀笟銆�
+
+1. 浣跨敤鍗庝负浜戝笎鍙风櫥褰昜ModelArts绠＄悊鎺у埗鍙癩(https://console.huaweicloud.com/modelarts)锛屽湪宸︿晶瀵艰埅鏍忎腑閫夋嫨鈥滆缁冪鐞� \> 璁粌浣滀笟锛圢ew锛夆€濓紝榛樿杩涘叆鈥滆缁冧綔涓氣€濆垪琛ㄣ€�
+2. 鍗曞嚮鈥滃垱寤鸿缁冧綔涓氣€濓紝杩涘叆鈥滃垱寤鸿缁冧綔涓氣€濋〉闈紝鍦ㄨ椤甸潰濉啓璁粌浣滀笟鐩稿叧鍙傛暟銆�
+
+ 1. 濉啓鍩烘湰淇℃伅銆�
+
+ 鍩烘湰淇℃伅鍖呭惈鈥滃悕绉扳€濆拰鈥滄弿杩扳€濄€�
+
+ 2. 濉啓浣滀笟鍙傛暟銆�
+
+ 鍖呭惈鏁版嵁鏉ユ簮銆佺畻娉曟潵婧愮瓑鍏抽敭淇℃伅銆傛湰姝ラ鍙彁渚涜缁冧换鍔￠儴鍒嗗弬鏁伴厤缃鏄庯紝鍏朵粬鍙傛暟閰嶇疆璇︽儏璇峰弬瑙乕銆奙odelArts AI 宸ョ▼甯堢敤鎴锋寚鍗梋(https://support.huaweicloud.com/modelarts/index.html)銆嬩腑鈥滆缁冪鐞嗭紙new锛夆€濄€�
+
+ **MindSpore鍜孴ensorFlow鍒涘缓璁粌浣滀笟姝ラ**
+
+ **琛� 1** 鍙傛暟璇存槑
+
+ <a name="table96111035134613"></a>
+ <table><thead align="left"><tr id="zh-cn_topic_0000001178072725_row1727593212228"><th class="cellrowborder" valign="top" width="20%" id="mcps1.2.4.1.1"><p id="zh-cn_topic_0000001178072725_p102751332172212"><a name="zh-cn_topic_0000001178072725_p102751332172212"></a><a name="zh-cn_topic_0000001178072725_p102751332172212"></a>鍙傛暟鍚嶇О</p>
+ </th>
+ <th class="cellrowborder" valign="top" width="20%" id="mcps1.2.4.1.2"><p id="zh-cn_topic_0000001178072725_p186943411156"><a name="zh-cn_topic_0000001178072725_p186943411156"></a><a name="zh-cn_topic_0000001178072725_p186943411156"></a>瀛愬弬鏁�</p>
+ </th>
+ <th class="cellrowborder" valign="top" width="60%" id="mcps1.2.4.1.3"><p id="zh-cn_topic_0000001178072725_p1827543282216"><a name="zh-cn_topic_0000001178072725_p1827543282216"></a><a name="zh-cn_topic_0000001178072725_p1827543282216"></a>璇存槑</p>
+ </th>
+ </tr>
+ </thead>
+ <tbody><tr id="zh-cn_topic_0000001178072725_row780219161358"><td class="cellrowborder" valign="top" width="20%" headers="mcps1.2.4.1.1 "><p id="zh-cn_topic_0000001178072725_p0803121617510"><a name="zh-cn_topic_0000001178072725_p0803121617510"></a><a name="zh-cn_topic_0000001178072725_p0803121617510"></a>绠楁硶</p>
+ </td>
+ <td class="cellrowborder" valign="top" width="20%" headers="mcps1.2.4.1.2 "><p id="zh-cn_topic_0000001178072725_p186947411520"><a name="zh-cn_topic_0000001178072725_p186947411520"></a><a name="zh-cn_topic_0000001178072725_p186947411520"></a>鎴戠殑绠楁硶</p>
+ </td>
+ <td class="cellrowborder" valign="top" width="60%" headers="mcps1.2.4.1.3 "><p id="zh-cn_topic_0000001178072725_p20803141614514"><a name="zh-cn_topic_0000001178072725_p20803141614514"></a><a name="zh-cn_topic_0000001178072725_p20803141614514"></a>閫夋嫨鈥滄垜鐨勭畻娉曗€濋〉绛撅紝鍕鹃€変笂鏂囦腑鍒涘缓鐨勭畻娉曘€�</p>
+ <p id="zh-cn_topic_0000001178072725_p24290418284"><a name="zh-cn_topic_0000001178072725_p24290418284"></a><a name="zh-cn_topic_0000001178072725_p24290418284"></a>濡傛灉娌℃湁鍒涘缓绠楁硶锛岃鍗曞嚮鈥滃垱寤衡€濊繘鍏ュ垱寤虹畻娉曢〉闈紝璇︾粏鎿嶄綔鎸囧鍙傝鈥滃垱寤虹畻娉曗€濄€�</p>
+ </td>
+ </tr>
+ <tr id="zh-cn_topic_0000001178072725_row1927503211228"><td class="cellrowborder" valign="top" width="20%" headers="mcps1.2.4.1.1 "><p id="zh-cn_topic_0000001178072725_p327583216224"><a name="zh-cn_topic_0000001178072725_p327583216224"></a><a name="zh-cn_topic_0000001178072725_p327583216224"></a>璁粌杈撳叆</p>
+ </td>
+ <td class="cellrowborder" valign="top" width="20%" headers="mcps1.2.4.1.2 "><p id="zh-cn_topic_0000001178072725_p1069419416510"><a name="zh-cn_topic_0000001178072725_p1069419416510"></a><a name="zh-cn_topic_0000001178072725_p1069419416510"></a>鏁版嵁鏉ユ簮</p>
+ </td>
+ <td class="cellrowborder" valign="top" width="60%" headers="mcps1.2.4.1.3 "><p id="zh-cn_topic_0000001178072725_p142750323227"><a name="zh-cn_topic_0000001178072725_p142750323227"></a><a name="zh-cn_topic_0000001178072725_p142750323227"></a>閫夋嫨OBS涓婃暟鎹泦瀛樻斁鐨勭洰褰曘€�</p>
+ </td>
+ </tr>
+ <tr id="zh-cn_topic_0000001178072725_row127593211227"><td class="cellrowborder" valign="top" width="20%" headers="mcps1.2.4.1.1 "><p id="zh-cn_topic_0000001178072725_p9744151562"><a name="zh-cn_topic_0000001178072725_p9744151562"></a><a name="zh-cn_topic_0000001178072725_p9744151562"></a>璁粌杈撳嚭</p>
+ </td>
+ <td class="cellrowborder" valign="top" width="20%" headers="mcps1.2.4.1.2 "><p id="zh-cn_topic_0000001178072725_p1027563212210"><a name="zh-cn_topic_0000001178072725_p1027563212210"></a><a name="zh-cn_topic_0000001178072725_p1027563212210"></a>妯″瀷杈撳嚭</p>
+ </td>
+ <td class="cellrowborder" valign="top" width="60%" headers="mcps1.2.4.1.3 "><p id="zh-cn_topic_0000001178072725_p13275113252214"><a name="zh-cn_topic_0000001178072725_p13275113252214"></a><a name="zh-cn_topic_0000001178072725_p13275113252214"></a>閫夋嫨璁粌缁撴灉鐨勫瓨鍌ㄤ綅缃紙OBS璺緞锛夛紝璇峰敖閲忛€夋嫨绌虹洰褰曟潵浣滀负璁粌杈撳嚭璺緞銆�</p>
+ </td>
+ </tr>
+ <tr id="zh-cn_topic_0000001178072725_row18750142834916"><td class="cellrowborder" valign="top" width="20%" headers="mcps1.2.4.1.1 "><p id="zh-cn_topic_0000001178072725_p5751172811492"><a name="zh-cn_topic_0000001178072725_p5751172811492"></a><a name="zh-cn_topic_0000001178072725_p5751172811492"></a>瑙勬牸</p>
+ </td>
+ <td class="cellrowborder" valign="top" width="20%" headers="mcps1.2.4.1.2 "><p id="zh-cn_topic_0000001178072725_p107514288495"><a name="zh-cn_topic_0000001178072725_p107514288495"></a><a name="zh-cn_topic_0000001178072725_p107514288495"></a>-</p>
+ </td>
+ <td class="cellrowborder" valign="top" width="60%" headers="mcps1.2.4.1.3 "><p id="zh-cn_topic_0000001178072725_p3751142811495"><a name="zh-cn_topic_0000001178072725_p3751142811495"></a><a name="zh-cn_topic_0000001178072725_p3751142811495"></a>Ascend: 1*Ascend 910(32GB) | ARM: 24 鏍� 96GB</p>
+ </td>
+ </tr>
+ <tr id="zh-cn_topic_0000001178072725_row16275103282219"><td class="cellrowborder" valign="top" width="20%" headers="mcps1.2.4.1.1 "><p id="zh-cn_topic_0000001178072725_p15275132192213"><a name="zh-cn_topic_0000001178072725_p15275132192213"></a><a name="zh-cn_topic_0000001178072725_p15275132192213"></a>浣滀笟鏃ュ織璺緞</p>
+ </td>
+ <td class="cellrowborder" valign="top" width="20%" headers="mcps1.2.4.1.2 "><p id="zh-cn_topic_0000001178072725_p1369484117516"><a name="zh-cn_topic_0000001178072725_p1369484117516"></a><a name="zh-cn_topic_0000001178072725_p1369484117516"></a>-</p>
+ </td>
+ <td class="cellrowborder" valign="top" width="60%" headers="mcps1.2.4.1.3 "><p id="zh-cn_topic_0000001178072725_p227563218228"><a name="zh-cn_topic_0000001178072725_p227563218228"></a><a name="zh-cn_topic_0000001178072725_p227563218228"></a>璁剧疆璁粌鏃ュ織瀛樻斁鐨勭洰褰曘€傝娉ㄦ剰閫夋嫨鐨凮BS鐩綍鏈夎鍐欐潈闄愩€�</p>
+ </td>
+ </tr>
+ </tbody>
+ </table>
+
+3. 鍗曞嚮鈥滄彁浜も€濓紝瀹屾垚璁粌浣滀笟鐨勫垱寤恒€�
+
+ 璁粌浣滀笟涓€鑸渶瑕佽繍琛屼竴娈垫椂闂达紝鏍规嵁鎮ㄩ€夋嫨鐨勬暟鎹噺鍜岃祫婧愪笉鍚岋紝璁粌鏃堕棿灏嗚€楁椂鍑犲垎閽熷埌鍑犲崄鍒嗛挓涓嶇瓑銆�
+
+### 鏌ョ湅璁粌浠诲姟鏃ュ織
+
+1. 鍦∕odelArts绠＄悊鎺у埗鍙帮紝鍦ㄥ乏渚у鑸爮涓€夋嫨鈥滆缁冪鐞� \> 璁粌浣滀笟锛圢ew锛夆€濓紝榛樿杩涘叆鈥滆缁冧綔涓氣€濆垪琛ㄣ€俖
+2. 鍦ㄨ缁冧綔涓氬垪琛ㄤ腑锛屾偍鍙互鍗曞嚮浣滀笟鍚嶇О锛屾煡鐪嬭浣滀笟鐨勮鎯呫€�
+
+ 璇︽儏涓寘鍚綔涓氱殑鍩烘湰淇℃伅銆佽缁冨弬鏁般€佹棩蹇楄鎯呭拰璧勬簮鍗犵敤鎯呭喌銆�
+
+ 鍦∣BS妗剁殑train_output鏂囦欢澶逛笅鍙互鐪嬪埌ckpt妯″瀷鍜宎ir妯″瀷鐨勭敓鎴愩€�
diff --git a/official/cv/MCNN/infer/convert/convert_om.sh b/official/cv/MCNN/infer/convert/convert_om.sh
new file mode 100644
index 0000000000000000000000000000000000000000..c0b209e928d2233929ede9a77cd46dbbba0cc887
--- /dev/null
+++ b/official/cv/MCNN/infer/convert/convert_om.sh
@@ -0,0 +1,61 @@
+#!/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.
+# ============================================================================
+soc_version=Ascend310
+input_shape="x:1,1,1024,1024"
+# 甯姪淇℃伅锛屼笉闇€瑕佷慨鏀�
+if [[ $1 == --help || $1 == -h ]];then
+ echo"usage:bash ./ATC_AIR_2_OM.sh <args>"
+ echo " "
+ echo "parameter explain:"
+ echo "--model set model place, e.g. --model=/home/mcnn.air"
+ echo "--output set the name and place of OM model, e.g. --output=/home/HwHiAiUser/fixmatch310_tune4"
+ echo "--soc_version set the soc_version, default: --soc_version=Ascend310"
+ echo "--input_shape set the input node and shape, default: --input_shape=x:1,1,1024,1024"
+ echo "-h/--help show help message"
+ exit 1
+fi
+
+for para in "$@"
+do
+ if [[ $para == --model* ]];then
+ model=`echo ${para#*=}`
+ elif [[ $para == --output* ]];then
+ output=`echo ${para#*=}`
+ elif [[ $para == --soc_version* ]];then
+ soc_version=`echo ${para#*=}`
+ elif [[ $para == --input_shape* ]];then
+ input_shape=`echo ${para#*=}`
+ fi
+done
+
+if [[ $model == "" ]];then
+ echo "[Error] para \"model \" must be config"
+ exit 1
+fi
+
+
+if [[ $output == "" ]];then
+ echo "[Error] para \"output \" must be config"
+ exit 1
+fi
+
+atc \
+ --model=${model} \
+ --output=${output} \
+ --soc_version=${soc_version} \
+ --input_shape=${input_shape} \
+ --framework=1 \
+ --input_format=NCHW
\ No newline at end of file
diff --git a/official/cv/MCNN/infer/docker_start_infer.sh b/official/cv/MCNN/infer/docker_start_infer.sh
new file mode 100644
index 0000000000000000000000000000000000000000..e25760deaf85985e879203642656cfa7c306619d
--- /dev/null
+++ b/official/cv/MCNN/infer/docker_start_infer.sh
@@ -0,0 +1,48 @@
+#!/usr/bin/env 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
+data_path=$2
+
+function show_help() {
+ echo "Usage: docker_start.sh docker_image data_path"
+}
+
+function param_check() {
+ if [ -z "${docker_image}" ]; then
+ echo "please input docker_image"
+ show_help
+ exit 1
+ fi
+
+ if [ -z "${data_path}" ]; then
+ echo "please input data_path"
+ show_help
+ exit 1
+ fi
+}
+
+param_check
+
+docker run -it \
+ --device=/dev/davinci0 \
+ --device=/dev/davinci_manager \
+ --device=/dev/devmm_svm \
+ --device=/dev/hisi_hdc \
+ -v /usr/local/Ascend/driver:/usr/local/Ascend/driver \
+ -v ${data_path}:${data_path} \
+ ${docker_image} \
+ /bin/bash
diff --git a/official/cv/MCNN/infer/mxbase/CMakeLists.txt b/official/cv/MCNN/infer/mxbase/CMakeLists.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ff0685d87eb4793f5560e7a4e9ef197fe970f3e8
--- /dev/null
+++ b/official/cv/MCNN/infer/mxbase/CMakeLists.txt
@@ -0,0 +1,48 @@
+cmake_minimum_required(VERSION 3.14.0)
+project(mcnn)
+set(TARGET_MAIN Mcnn)
+
+add_definitions(-D_GLIBCXX_USE_CXX11_ABI=0)
+add_definitions(-Dgoogle=mindxsdk_private)
+add_compile_options(-std=c++11 -fPIE -fstack-protector-all -fPIC -Wall)
+add_link_options(-Wl,-z,relro,-z,now,-z,noexecstack -s -pie)
+
+if(NOT DEFINED ENV{ASCEND_HOME})
+ message(FATAL_ERROR "please define environment variable:ASCEND_HOME")
+endif()
+
+if(NOT DEFINED ENV{ARCH_PATTERN})
+ message(WARNING "please define environment variable:ARCH_PATTERN")
+endif()
+
+set(ACL_LIB_PATH $ENV{ASCEND_HOME}/nnrt/latest/acllib)
+set(MXBASE_ROOT_DIR $ENV{MX_SDK_HOME})
+set(MXBASE_INC ${MXBASE_ROOT_DIR}/include)
+set(MXBASE_LIB_DIR ${MXBASE_ROOT_DIR}/lib)
+set(MXBASE_POST_LIB_DIR ${MXBASE_ROOT_DIR}/lib/modelpostprocessors)
+set(MXBASE_POST_PROCESS_DIR ${MXBASE_ROOT_DIR}/include/MxBase/postprocess/include)
+
+if(NOT DEFINED ENV{MXSDK_OPENSOURCE_DIR})
+ message(WARNING "please define environment variable:MXSDK_OPENSOURCE_DIR")
+endif()
+
+set(OPENSOURCE_DIR $ENV{MXSDK_OPENSOURCE_DIR})
+
+include_directories(src)
+include_directories(${ACL_INC_DIR})
+include_directories(${OPENSOURCE_DIR}/include)
+include_directories(${OPENSOURCE_DIR}/include/opencv4)
+
+
+include_directories(${MXBASE_INC})
+include_directories(${MXBASE_POST_PROCESS_DIR})
+
+link_directories(${ACL_LIB_DIR})
+link_directories(${OPENSOURCE_DIR}/lib)
+link_directories(${MXBASE_LIB_DIR})
+link_directories(${MXBASE_POST_LIB_DIR})
+
+
+add_executable(${TARGET_MAIN} src/main.cpp src/Mcnn.cpp)
+
+target_link_libraries(${TARGET_MAIN} glog cpprest mxbase opencv_world)
diff --git a/official/cv/MCNN/infer/mxbase/build.sh b/official/cv/MCNN/infer/mxbase/build.sh
new file mode 100644
index 0000000000000000000000000000000000000000..5c2b02fccb384c5d9b014e8d20ff2a620180ede8
--- /dev/null
+++ b/official/cv/MCNN/infer/mxbase/build.sh
@@ -0,0 +1,59 @@
+#!/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.
+# ============================================================================
+
+path_cur=$(dirname $0)
+
+
+function check_env()
+{
+ # set ASCEND_VERSION to ascend-toolkit/latest when it was not specified by user
+ if [ ! "${ASCEND_VERSION}" ]; then
+ export ASCEND_VERSION=ascend-toolkit/latest
+ echo "Set ASCEND_VERSION to the default value: ${ASCEND_VERSION}"
+ else
+ echo "ASCEND_VERSION is set to ${ASCEND_VERSION} by user"
+ fi
+
+ if [ ! "${ARCH_PATTERN}" ]; then
+ # set ARCH_PATTERN to ./ when it was not specified by user
+ export ARCH_PATTERN=./
+ echo "ARCH_PATTERN is set to the default value: ${ARCH_PATTERN}"
+ else
+ echo "ARCH_PATTERN is set to ${ARCH_PATTERN} by user"
+ fi
+}
+
+function build_mcnn()
+{
+ cd $path_cur
+ rm -rf build
+ mkdir -p build
+ cd build
+ cmake ..
+ make
+ ret=$?
+ if [ ${ret} -ne 0 ]; then
+ echo "Failed to build srgan."
+ exit ${ret}
+ fi
+ mv Mcnn ../
+}
+export ASCEND_VERSION=nnrt/latest
+export ARCH_PATTERN=.
+export MXSDK_OPENSOURCE_DIR=${MX_SDK_HOME}/opensource
+export LD_LIBRARY_PATH="${MX_SDK_HOME}/lib/plugins:${MX_SDK_HOME}/opensource/lib64:${MX_SDK_HOME}/lib:${MX_SDK_HOME}/lib/modelpostprocessors:${MX_SDK_HOME}/opensource/lib:${LD_LIBRARY_PATH}"
+check_env
+build_mcnn
\ No newline at end of file
diff --git a/official/cv/MCNN/infer/mxbase/src/Mcnn.cpp b/official/cv/MCNN/infer/mxbase/src/Mcnn.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..8c05e4a6103b2e0e7fd6018e4a06d9faa44e398f
--- /dev/null
+++ b/official/cv/MCNN/infer/mxbase/src/Mcnn.cpp
@@ -0,0 +1,315 @@
+/*
+ * 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.
+ * ============================================================================
+ */
+
+#include "Mcnn.h"
+#include <iostream>
+#include <fstream>
+#include <sstream>
+#include <string>
+#include <vector>
+#include <cstdlib>
+#include "MxBase/DeviceManager/DeviceManager.h"
+#include "MxBase/Log/Log.h"
+#include <opencv2/opencv.hpp>
+
+
+using MxBase::TensorDesc;
+using MxBase::TensorBase;
+using MxBase::MemoryData;
+using MxBase::MemoryHelper;
+using MxBase::TENSOR_DTYPE_FLOAT32;
+using MxBase::DynamicInfo;
+using MxBase::DynamicType;
+
+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];
+ }
+ }
+}
+
+void PrintInputShape(const std::vector<MxBase::TensorBase> &input) {
+ MxBase::TensorBase img = input[0];
+ LogInfo << " -------------------------input0 ";
+ LogInfo << img.GetDataType();
+ LogInfo << img.GetShape()[0] << ", " << img.GetShape()[1] \
+ << ", " << img.GetShape()[2] << ", " << img.GetShape()[3];
+ LogInfo << img.GetSize();
+}
+
+APP_ERROR Mcnn::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;
+ }
+ srPath_ = initParam.srPath;
+ gtPath_ = initParam.gtPath;
+ PrintTensorShape(modelDesc_.inputTensors, "Model Input Tensors");
+ PrintTensorShape(modelDesc_.outputTensors, "Model Output Tensors");
+
+
+ return APP_ERR_OK;
+}
+
+APP_ERROR Mcnn::DeInit() {
+ dvppWrapper_->DeInit();
+ model_->DeInit();
+
+ MxBase::DeviceManager::GetInstance()->DestroyDevices();
+
+ return APP_ERR_OK;
+}
+
+
+APP_ERROR Mcnn::ReadImage(const std::string &imgPath, cv::Mat *imageMat) {
+ *imageMat = cv::imread(imgPath, 0);
+ return APP_ERR_OK;
+}
+
+
+std::string Trim(const std::string &str) {
+ std::string str_new = str;
+ str_new.erase(0, str.find_first_not_of(" \t\r\n"));
+ str_new.erase(str.find_last_not_of(" \t\r\n") + 1);
+ return str_new;
+}
+
+
+float ReadCsv(std::string csvName) {
+ std::ifstream fin(csvName);
+ std::string line;
+ float num = 0;
+ while (getline(fin, line)) {
+ std::istringstream sin(line);
+ std::vector<std::string> fields;
+ std::string field;
+ int len = 0;
+ while (getline(sin, field, ',')) {
+ len++;
+ fields.push_back(field);
+ }
+ for (int i = 0; i < len; i++) {
+ std::string name = Trim(fields[i]);
+ float num_float = std::stof(name);
+ num = num + num_float;
+ }
+ }
+ return num;
+}
+
+
+APP_ERROR Mcnn::PadImage(const cv::Mat &imageMat, cv::Mat *imgPad) {
+ size_t W_o = imageMat.cols, H_o = imageMat.rows;
+ size_t W_b = 512 - W_o / 2;
+ size_t H_b = 512 - H_o / 2;
+ size_t W_e = W_b + W_o;
+ size_t H_e = H_b + H_o;
+ for (size_t h = 0; h < 1024; h++) {
+ for (size_t w = 0; w < 1024; w++) {
+ if (H_b <= h && h < H_e && W_b <= w && w < W_e) {
+ imgPad->at<uchar>(h, w) = imageMat.at<uchar>(h - H_b, w - W_b);
+ } else {
+ imgPad->at<uchar>(h, w) = 0;
+ }
+ }
+ }
+ return APP_ERR_OK;
+}
+
+
+APP_ERROR Mcnn::CVMatToTensorBase(const cv::Mat &imageMat, MxBase::TensorBase *tensorBase) {
+ uint32_t dataSize = 1;
+ for (size_t i = 0; i < modelDesc_.inputTensors.size(); ++i) {
+ std::vector <uint32_t> shape = {};
+ for (size_t j = 0; j < modelDesc_.inputTensors[i].tensorDims.size(); ++j) {
+ shape.push_back((uint32_t) modelDesc_.inputTensors[i].tensorDims[j]);
+ }
+ for (uint32_t s = 0; s < shape.size(); ++s) {
+ dataSize *= shape[s];
+ }
+ }
+ APP_ERROR ret = PadImage(imageMat, &imgPad_);
+ if (ret != APP_ERR_OK) {
+ LogError << GetError(ret) << "Img pad error";
+ return ret;
+ }
+ // mat NHWC to NCHW
+ size_t H = 1024, W = 1024, C = 1;
+ LogInfo << "dataSize:" << dataSize;
+ dataSize = dataSize * 4;
+ int id;
+
+ for (size_t c = 0; c < C; c++) {
+ for (size_t h = 0; h < H; h++) {
+ for (size_t w = 0; w < W; w++) {
+ id = (C - c - 1) * (H * W) + h * W + w;
+ mat_data_[id] = static_cast<float>(imgPad_.at<uchar>(h, w));
+ }
+ }
+ }
+
+ MemoryData memoryDataDst(dataSize, MemoryData::MEMORY_DEVICE, deviceId_);
+ MemoryData memoryDataSrc(reinterpret_cast<void *>(&mat_data_[0]), dataSize, MemoryData::MEMORY_HOST_MALLOC);
+ ret = MemoryHelper::MxbsMallocAndCopy(memoryDataDst, memoryDataSrc);
+ if (ret != APP_ERR_OK) {
+ LogError << GetError(ret) << "Memory malloc failed.";
+ return ret;
+ }
+ std::vector <uint32_t> shape = {1, 1, 1024, 1024};
+ *tensorBase = MxBase::TensorBase(memoryDataDst, false, shape, TENSOR_DTYPE_FLOAT32);
+ return APP_ERR_OK;
+}
+
+
+APP_ERROR Mcnn::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], MemoryData::MemoryType::MEMORY_DEVICE, deviceId_);
+ APP_ERROR ret = TensorBase::TensorBaseMalloc(tensor);
+ if (ret != APP_ERR_OK) {
+ LogError << "TensorBaseMalloc failed, ret=" << ret << ".";
+ return ret;
+ }
+ outputs->push_back(tensor);
+ }
+ MxBase::DynamicInfo dynamicInfo = {};
+ dynamicInfo.dynamicType = DynamicType::STATIC_BATCH;
+ dynamicInfo.batchSize = 1;
+
+ APP_ERROR ret = model_->ModelInference(inputs, *outputs, dynamicInfo);
+ if (ret != APP_ERR_OK) {
+ LogError << "ModelInference failed, ret=" << ret << ".";
+ return ret;
+ }
+ return APP_ERR_OK;
+}
+
+
+APP_ERROR Mcnn::PostProcess(std::vector<MxBase::TensorBase> outputs, const std::string &imgName) {
+ LogInfo << "output_size:" << outputs.size();
+ LogInfo << "output0_datatype:" << outputs[0].GetDataType();
+ LogInfo << "output0_shape:" << outputs[0].GetShape()[0] << ", " \
+ << outputs[0].GetShape()[1] << ", " << outputs[0].GetShape()[2] << ", " << outputs[0].GetShape()[3];
+ LogInfo << "output0_bytesize:" << outputs[0].GetByteSize();
+
+ APP_ERROR ret = outputs[0].ToHost();
+ if (ret != APP_ERR_OK) {
+ LogError << GetError(ret) << "tohost fail.";
+ return ret;
+ }
+ float *outputPtr = reinterpret_cast<float *>(outputs[0].GetBuffer());
+
+ size_t H = 1024/4 , W = 1024/4 , C = 1;
+
+ float tmpNum;
+ float pre = 0;
+ for (size_t c = 0; c < C; c++) {
+ for (size_t h = 0; h < H; h++) {
+ for (size_t w = 0; w < W; w++) {
+ tmpNum = static_cast<float>(*(outputPtr + (C - c - 1) * (H * W) + h * W + w));
+ pre = pre + tmpNum;
+ }
+ }
+ }
+ std::string imgName2 = imgName;
+ int len = imgName.length();
+ imgName2[len-3] = 'c';
+ imgName2[len-2] = 's';
+ imgName2[len-1] = 'v';
+ std::string gtName = gtPath_;
+ gtName.append(imgName2);
+ LogInfo << gtName;
+ LogInfo << "pre:" << pre;
+ float gt_count = ReadCsv(gtName);
+ LogInfo << "gt:" << gt_count;
+ mae += fabs(gt_count - pre);
+ mse = mse+ (gt_count - pre)*(gt_count - pre);
+ LogInfo << "mae:" << fabs(gt_count - pre);
+ return APP_ERR_OK;
+}
+
+
+APP_ERROR Mcnn::Process(const std::string &imgPath, const std::string &imgName) {
+ LogInfo << imgName;
+ cv::Mat imageMat;
+ APP_ERROR ret = ReadImage(imgPath, &imageMat);
+
+ if (ret != APP_ERR_OK) {
+ LogError << "ReadImage failed, ret=" << ret << ".";
+ return ret;
+ }
+
+ size_t o_img_W = imageMat.cols, o_img_H = imageMat.rows, o_img_C = imageMat.channels();
+ LogInfo << o_img_C << "," << o_img_H << "," << o_img_W;
+
+
+ std::vector<MxBase::TensorBase> inputs = {};
+ std::vector<MxBase::TensorBase> outputs = {};
+
+ MxBase::TensorBase tensorBase;
+ ret = CVMatToTensorBase(imageMat, &tensorBase);
+ cv::imwrite(srPath_ + "/" + imgName, imgPad_);
+ if (ret != APP_ERR_OK) {
+ LogError << "CVMatToTensorBase failed, ret=" << ret << ".";
+ return ret;
+ }
+ inputs.push_back(tensorBase);
+
+ 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;
+ }
+ ret = PostProcess(outputs, imgName);
+ if (ret != APP_ERR_OK) {
+ LogError << "PostProcess failed, ret=" << ret << ".";
+ return ret;
+ }
+
+ return APP_ERR_OK;
+}
diff --git a/official/cv/MCNN/infer/mxbase/src/Mcnn.h b/official/cv/MCNN/infer/mxbase/src/Mcnn.h
new file mode 100644
index 0000000000000000000000000000000000000000..75182defcd38405c3b3176edaf8651d1d44e0923
--- /dev/null
+++ b/official/cv/MCNN/infer/mxbase/src/Mcnn.h
@@ -0,0 +1,76 @@
+/*
+ * 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.
+ * ============================================================================
+ */
+
+#ifndef MCNN_H
+#define MCNN_H
+#include <dirent.h>
+#include <memory>
+#include <vector>
+#include <map>
+#include <string>
+#include <fstream>
+#include <iostream>
+#include <opencv2/opencv.hpp>
+#include "MxBase/Log/Log.h"
+#include "MxBase/DvppWrapper/DvppWrapper.h"
+#include "MxBase/ModelInfer/ModelInferenceProcessor.h"
+#include "MxBase/Tensor/TensorContext/TensorContext.h"
+#include "MxBase/DeviceManager/DeviceManager.h"
+
+struct InitParam {
+ uint32_t deviceId;
+ bool checkTensor;
+ std::string modelPath;
+ std::string srPath;
+ std::string gtPath;
+};
+
+
+class Mcnn {
+ public:
+ APP_ERROR Init(const InitParam &initParam);
+ APP_ERROR DeInit();
+ APP_ERROR ReadImage(const std::string &imgPath, cv::Mat *imageMat);
+ APP_ERROR PadImage(const cv::Mat &img, cv::Mat *imgPad);
+ APP_ERROR CVMatToTensorBase(const cv::Mat &imageMat, MxBase::TensorBase *tensorBase);
+ APP_ERROR Inference(const std::vector<MxBase::TensorBase> &inputs, std::vector<MxBase::TensorBase> *outputs);
+ APP_ERROR PostProcess(std::vector<MxBase::TensorBase> outputs, const std::string &imgName);
+ APP_ERROR Process(const std::string &imgPath, const std::string &imgName);
+ // get infer time
+ double GetInferCostMilliSec() const {return inferCostTimeMilliSec;}
+ double GetPSNR() const {return psnr_;}
+ float getmae() const {return mae;}
+ float getmse() const {return mse;}
+
+ private:
+ std::shared_ptr<MxBase::DvppWrapper> dvppWrapper_;
+ std::shared_ptr<MxBase::ModelInferenceProcessor> model_;
+ std::string srPath_;
+ std::string gtPath_;
+ MxBase::ModelDesc modelDesc_;
+ double_t psnr_ = 0;
+ uint32_t deviceId_ = 0;
+ // infer time
+ double inferCostTimeMilliSec = 0.0;
+ float *mat_data_ = new float[1048576];
+ cv::Mat imgPad_ = cv::Mat(1024, 1024, CV_32FC1);
+ float mae = 0.0;
+ float mse = 0.0;
+};
+
+
+#endif
diff --git a/official/cv/MCNN/infer/mxbase/src/main.cpp b/official/cv/MCNN/infer/mxbase/src/main.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..059505d8d789bb033c2d70b9bb942122f4d1bfb6
--- /dev/null
+++ b/official/cv/MCNN/infer/mxbase/src/main.cpp
@@ -0,0 +1,102 @@
+/*
+ * 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.
+ * ============================================================================
+ */
+
+#include "Mcnn.h"
+
+
+APP_ERROR ScanImages(const std::string &path, std::vector<std::string> *imgFiles) {
+ DIR *dirPtr = opendir(path.c_str());
+ if (dirPtr == nullptr) {
+ LogError << "opendir failed. dir:" << path;
+ return APP_ERR_INTERNAL_ERROR;
+ }
+ dirent *direntPtr = nullptr;
+ while ((direntPtr = readdir(dirPtr)) != nullptr) {
+ std::string fileName = direntPtr->d_name;
+ if (fileName == "." || fileName == "..")
+ continue;
+
+ imgFiles->emplace_back(fileName);
+ }
+ closedir(dirPtr);
+ return APP_ERR_OK;
+}
+
+
+int main(int argc, char* argv[]) {
+ if (argc <= 4) {
+ LogWarn << "Please input image path, such as './Mcnn [model_path] [data_path] [label_path] [output_path]'.";
+ return APP_ERR_OK;
+ }
+
+ const std::string modelPath = argv[1];
+ std::string inputPath = argv[2];
+ std::string gtPath = argv[3];
+ std::string srPath = argv[4];
+
+ InitParam initParam = {};
+ initParam.deviceId = 0;
+ initParam.checkTensor = true;
+ initParam.modelPath = modelPath;
+ initParam.srPath = srPath;
+ initParam.gtPath = gtPath;
+
+ auto mcnn = std::make_shared<Mcnn>();
+ APP_ERROR ret = mcnn->Init(initParam);
+ if (ret != APP_ERR_OK) {
+ LogError << "mcnn init failed, ret=" << ret << ".";
+ return ret;
+ }
+
+ std::vector<std::string> imgFilePaths;
+ ret = ScanImages(inputPath, &imgFilePaths);
+ if (ret != APP_ERR_OK) {
+ LogError << "mcnn lq img scan error, ret=" << ret << ".";
+ return ret;
+ }
+
+ auto startTime = std::chrono::high_resolution_clock::now();
+
+ int totalNum = 0;
+
+ sort(imgFilePaths.begin(), imgFilePaths.end());
+ int imgFilePaths_size = imgFilePaths.size();
+ for (int i = 0; i < imgFilePaths_size; i++) {
+ LogInfo << imgFilePaths[i];
+ }
+
+ for (auto &imgFile : imgFilePaths) {
+ LogInfo << totalNum;
+ ret = mcnn->Process(inputPath+'/'+imgFile, imgFile);
+ ++totalNum;
+ if (ret != APP_ERR_OK) {
+ LogError << "mcnn process failed, ret=" << ret << ".";
+ mcnn->DeInit();
+ return ret;
+ }
+ }
+ float mae = mcnn->getmae()/totalNum;
+ float mse = sqrt(mcnn->getmse()/totalNum);
+ LogInfo << "mae:" << mae;
+ LogInfo << "mse:" << mse;
+ auto endTime = std::chrono::high_resolution_clock::now();
+ mcnn->DeInit();
+ double costMilliSecs = std::chrono::duration<double, std::milli>(endTime - startTime).count();
+ double fps = 1000.0 * imgFilePaths.size() / mcnn->GetInferCostMilliSec();
+ LogInfo << "[Process Delay] cost: " << costMilliSecs << " ms\tfps: " << fps << " imgs/sec";
+ return APP_ERR_OK;
+}
diff --git a/official/cv/MCNN/infer/sdk/main.py b/official/cv/MCNN/infer/sdk/main.py
new file mode 100644
index 0000000000000000000000000000000000000000..dd13dc952ac3f979aaf6189871e2ddc50c1137b6
--- /dev/null
+++ b/official/cv/MCNN/infer/sdk/main.py
@@ -0,0 +1,141 @@
+# coding=utf-8
+# 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.
+# ============================================================================
+
+import datetime
+import os
+import sys
+import numpy as np
+import cv2
+
+from StreamManagerApi import StreamManagerApi
+from StreamManagerApi import MxDataInput
+from StreamManagerApi import StringVector
+from StreamManagerApi import MxProtobufIn
+from StreamManagerApi import InProtobufVector
+import MxpiDataType_pb2 as MxpiDataType
+
+if __name__ == '__main__':
+ # init stream manager
+ stream_manager_api = StreamManagerApi()
+ ret = stream_manager_api.InitManager()
+ if ret != 0:
+ print("Failed to init Stream manager, ret=%s" % str(ret))
+ exit()
+
+ # create streams by pipeline config file
+ with open("./mcnn.pipeline", 'rb') as f:
+ pipelineStr = f.read()
+ ret = stream_manager_api.CreateMultipleStreams(pipelineStr)
+ if ret != 0:
+ print("Failed to create Stream, ret=%s" % str(ret))
+ exit()
+
+ # Construct the input of the stream
+ data_input = MxDataInput()
+
+ dir_name = sys.argv[1]
+ gt_name = sys.argv[2]
+
+ file_list = os.listdir(dir_name)
+ file_list.sort()
+ mae = 0
+ mse = 0
+ start_time = datetime.datetime.now()
+ for file_name in file_list:
+ file_path = os.path.join(dir_name, file_name)
+ gt_path = os.path.join(gt_name, file_name[:-3] + 'csv')
+ if not (file_name.lower().endswith(".jpg") or file_name.lower().endswith(".jpeg") \
+ or file_name.lower().endswith(".png")):
+ continue
+
+ empty_data = []
+ stream_name = b'mcnn_opencv'
+ in_plugin_id = 0
+ input_key = 'appsrc0'
+
+ img = cv2.imread(file_path, 0)
+ img = img.astype(np.float32, copy=False)
+ ht = img.shape[0]
+ wd = img.shape[1]
+ hang_left = 512 - int(ht / 2)
+ hang_right = 1024 - hang_left - ht
+ lie_left = 512 - int(wd / 2)
+ lie_right = 1024 - lie_left - wd
+ img = np.pad(img, ((hang_left, hang_right), (lie_left, lie_right)), 'constant')
+
+ img = img.reshape((1, 1, 1024, 1024))
+ tensor_list = MxpiDataType.MxpiTensorPackageList()
+ tensor_pkg = tensor_list.tensorPackageVec.add()
+
+ tensor_vec = tensor_pkg.tensorVec.add()
+ tensor_vec.memType = 0
+ tensor_vec.tensorShape.extend(img.shape)
+ tensor_vec.tensorDataType = 0
+ tensor_vec.dataStr = img.tobytes()
+ tensor_vec.tensorDataSize = len(img)
+ buf_type = b"MxTools.MxpiTensorPackageList"
+
+ protobuf = MxProtobufIn()
+ protobuf.key = input_key.encode("utf-8")
+ protobuf.type = buf_type
+ protobuf.protobuf = tensor_list.SerializeToString()
+ protobuf_vec = InProtobufVector()
+ protobuf_vec.push_back(protobuf)
+ err_code = stream_manager_api.SendProtobuf(stream_name, in_plugin_id, protobuf_vec)
+ if err_code != 0:
+ print(
+ "Failed to send data to stream, stream_name(%s), plugin_id(%s), element_name(%s), "
+ "buf_type(%s), err_code(%s).", stream_name, in_plugin_id,
+ input_key, buf_type, err_code)
+
+ keys = [b"mxpi_tensorinfer0",]
+ keyVec = StringVector()
+ for key in keys:
+ keyVec.push_back(key)
+ infer_result = stream_manager_api.GetProtobuf(stream_name, 0, keyVec)
+ if infer_result.size() == 0:
+ print("infer_result is null")
+ exit()
+
+ if infer_result[0].errorCode != 0:
+ print("GetProtobuf error. errorCode=%d" % (
+ infer_result[0].errorCode))
+ exit()
+
+ TensorList = MxpiDataType.MxpiTensorPackageList()
+ TensorList.ParseFromString(infer_result[0].messageBuf)
+ data = np.frombuffer(TensorList.tensorPackageVec[0].tensorVec[0].dataStr, dtype=np.float32)
+
+ den = np.loadtxt(open(gt_path, "rb"), delimiter=",", skiprows=0)
+ den = den.astype(np.float32, copy=False)
+ gt_count = np.sum(den)
+ et_count = np.sum(data)
+ mae += abs(gt_count - et_count)
+ mse += ((gt_count - et_count) * (gt_count - et_count))
+ print(file_path, "True value:", np.sum(den), "predictive value:", np.sum(data))
+
+ mae = mae / 182
+ mse = np.sqrt(mse / 182)
+ end_time = datetime.datetime.now()
+ print("*********************************************")
+ print("Final accuracy of the project:")
+ print('MAE:', mae, ' MSE:', mse)
+ print("*********************************************")
+ print("Overall project performance:")
+ print(182 / (end_time - start_time).seconds, "images/seconds")
+
+ # destroy streams
+ stream_manager_api.DestroyAllStreams()
diff --git a/official/cv/MCNN/infer/sdk/mcnn.pipeline b/official/cv/MCNN/infer/sdk/mcnn.pipeline
new file mode 100644
index 0000000000000000000000000000000000000000..6214003074b94cb8267c53fd8800b54dc6b84d41
--- /dev/null
+++ b/official/cv/MCNN/infer/sdk/mcnn.pipeline
@@ -0,0 +1,20 @@
+{
+ "mcnn_opencv": {
+ "appsrc0": {
+ "factory": "appsrc",
+ "next": "mxpi_tensorinfer0"
+ },
+ "mxpi_tensorinfer0": {
+ "props": {
+ "dataSource": "appsrc0",
+ "modelPath": "../model/mcnn.om",
+ "waitingTime": "2000"
+ },
+ "factory": "mxpi_tensorinfer",
+ "next": "appsink0"
+ },
+ "appsink0": {
+ "factory": "appsink"
+ }
+ }
+}
\ No newline at end of file
diff --git a/official/cv/MCNN/infer/sdk/run.sh b/official/cv/MCNN/infer/sdk/run.sh
new file mode 100644
index 0000000000000000000000000000000000000000..fe3f2c190d07b43305090365a2bf3fa5aff04457
--- /dev/null
+++ b/official/cv/MCNN/infer/sdk/run.sh
@@ -0,0 +1,31 @@
+#!/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.
+# ============================================================================
+input_dir=$1
+gt_dir=$2
+
+set -e
+
+
+# Simple log helper functions
+info() { echo -e "\033[1;34m[INFO ][MxStream] $1\033[1;37m" ; }
+warn() { echo >&2 -e "\033[1;31m[WARN ][MxStream] $1\033[1;37m" ; }
+
+
+#to set PYTHONPATH, import the StreamManagerApi.py
+export PYTHONPATH=$PYTHONPATH:${MX_SDK_HOME}/python
+
+python3.7 main.py $input_dir $gt_dir
+exit 0
\ No newline at end of file
diff --git a/official/cv/MCNN/modelarts/start_train.py b/official/cv/MCNN/modelarts/start_train.py
new file mode 100644
index 0000000000000000000000000000000000000000..62eb9ec5460e5037a4a41e8fc930d98291435fec
--- /dev/null
+++ b/official/cv/MCNN/modelarts/start_train.py
@@ -0,0 +1,146 @@
+# 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 mcnn example ########################
+train mcnn and get network model files(.ckpt) :
+python train.py
+"""
+import os
+import argparse
+import ast
+import numpy as np
+import mindspore.nn as nn
+import mindspore
+from mindspore.context import ParallelMode
+from mindspore import context, Tensor
+from mindspore.communication.management import init, get_rank
+from mindspore.train.callback import LossMonitor, TimeMonitor
+from mindspore.train.serialization import export, load_checkpoint
+from mindspore.train import Model
+from src.data_loader import ImageDataLoader
+from src.config import crowd_cfg as cfg
+from src.dataset import create_dataset
+from src.mcnn import MCNN
+from src.generator_lr import get_lr_sha
+from src.Mcnn_Callback import mcnn_callback
+
+parser = argparse.ArgumentParser(description='MindSpore MCNN Example')
+parser.add_argument('--run_offline', type=ast.literal_eval,
+ default=False, help='run in offline is False or True')
+parser.add_argument('--device_target', type=str, default="Ascend", choices=['Ascend', 'GPU', 'CPU'],
+ help='device where the code will be implemented (default: Ascend)')
+parser.add_argument("--batch_size", type=int, default=1, help="batch size")
+parser.add_argument("--lr", type=float, default=cfg['lr'], help="batch size")
+parser.add_argument("--momentum", type=float, default=cfg['momentum'], help="batch size")
+parser.add_argument("--epoch_size", type=int, default=cfg['epoch_size'], help="batch size")
+parser.add_argument("--input_size", type=int, default=1024, help="batch size")
+parser.add_argument('--ckpt_path', type=str, default="./train_output", help='Location of ckpt.')
+
+parser.add_argument('--data_url', default=None, help='Location of data.')
+parser.add_argument('--train_url', default=None, help='Location of training outputs.')
+
+parser.add_argument('--train_path', default='../MCNN/data/formatted_trainval/shanghaitech_part_A_patches_9/train',
+ help='Location of data.')
+parser.add_argument('--train_gt_path',
+ default='../MCNN/data/formatted_trainval/shanghaitech_part_A_patches_9/train_den',
+ help='Location of data.')
+parser.add_argument('--val_path', default='../MCNN/data/formatted_trainval/shanghaitech_part_A_patches_9/val',
+ help='Location of data.')
+parser.add_argument('--val_gt_path', default='../MCNN/data/formatted_trainval/shanghaitech_part_A_patches_9/val_den',
+ help='Location of data.')
+args = parser.parse_args()
+rand_seed = 64678
+np.random.seed(rand_seed)
+
+if __name__ == "__main__":
+ device_num = int(os.getenv("RANK_SIZE", '1'))
+ device_id = int(os.getenv("DEVICE_ID", '0'))
+
+ print("device_id:", device_id)
+ print("device_num:", device_num)
+ device_target = args.device_target
+ context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target)
+ context.set_context(save_graphs=False)
+ print(args.data_url)
+
+ if device_target == "GPU":
+ context.set_context(enable_graph_kernel=True)
+ device_id = 0
+ if device_num > 1:
+ init()
+ context.reset_auto_parallel_context()
+ context.set_auto_parallel_context(device_num=device_num, parallel_mode=ParallelMode.DATA_PARALLEL,
+ gradients_mean=True)
+ device_id = get_rank()
+ elif device_target == "Ascend":
+ context.set_context(device_id=device_id)
+
+ if device_num > 1:
+ context.reset_auto_parallel_context()
+ context.set_auto_parallel_context(device_num=device_num, parallel_mode=ParallelMode.DATA_PARALLEL,
+ gradients_mean=True)
+ init()
+ else:
+ raise ValueError("Unsupported platform.")
+ if args.run_offline:
+ local_data1_url = args.train_path
+ local_data2_url = args.train_gt_path
+ local_data3_url = args.val_path
+ local_data4_url = args.val_gt_path
+ else:
+ import moxing as mox
+ local_data1_url = '/cache/train_path'
+ local_data2_url = '/cache/train_gt_path'
+ local_data3_url = '/cache/val_path'
+ local_data4_url = '/cache/val_gt_path'
+
+ args.train_path = os.path.join(args.data_url, "formatted_trainval/shanghaitech_part_A_patches_9/train")
+ args.train_gt_path = os.path.join(args.data_url, "formatted_trainval/shanghaitech_part_A_patches_9/train_den")
+ args.val_path = os.path.join(args.data_url, "formatted_trainval/shanghaitech_part_A_patches_9/val")
+ args.val_gt_path = os.path.join(args.data_url, "formatted_trainval/shanghaitech_part_A_patches_9/val_den")
+ args.ckpt_path = args.train_url
+ mox.file.copy_parallel(src_url=args.train_path, dst_url=local_data1_url) # pcl
+ mox.file.copy_parallel(src_url=args.train_gt_path, dst_url=local_data2_url) # pcl
+ mox.file.copy_parallel(src_url=args.val_path, dst_url=local_data3_url) # pcl
+ mox.file.copy_parallel(src_url=args.val_gt_path, dst_url=local_data4_url) # pcl
+
+ data_loader = ImageDataLoader(local_data1_url, local_data2_url, shuffle=True, gt_downsample=True, pre_load=True)
+ data_loader_val = ImageDataLoader(local_data3_url, local_data4_url,
+ shuffle=False, gt_downsample=True, pre_load=True)
+ ds_train = create_dataset(data_loader, target=args.device_target)
+ ds_val = create_dataset(data_loader_val, target=args.device_target, train=False)
+
+ ds_train = ds_train.batch(args.batch_size)
+ ds_val = ds_val.batch(1)
+
+ network = MCNN()
+ net_loss = nn.MSELoss(reduction='mean')
+ lr = Tensor(get_lr_sha(0, args.lr, args.epoch_size, ds_train.get_dataset_size()))
+ net_opt = nn.Adam(list(filter(lambda p: p.requires_grad, network.get_parameters())), learning_rate=lr)
+
+ model = Model(network, net_loss, net_opt, amp_level="O2")
+
+ print("============== Starting Training ==============")
+ time_cb = TimeMonitor(data_size=ds_train.get_dataset_size())
+ eval_callback = mcnn_callback(network, ds_val, args.run_offline, args.ckpt_path)
+ model.train(args.epoch_size, ds_train, callbacks=[time_cb, eval_callback, LossMonitor(1)])
+ if not args.run_offline:
+ mox.file.copy_parallel(src_url='/cache/train_output', dst_url=args.ckpt_path)
+
+ load_checkpoint('/cache/train_output/best.ckpt', net=network)
+ inputs = Tensor(np.ones([args.batch_size, 1, args.input_size, args.input_size]), mindspore.float32)
+ export(network, inputs, file_name="mcnn", file_format="AIR")
+ print("MCNN exported")
+ mox.file.copy(src_url='mcnn.air', dst_url=os.path.join(args.train_url, 'mcnn.air'))
diff --git a/official/cv/MCNN/scripts/docker_start.sh b/official/cv/MCNN/scripts/docker_start.sh
new file mode 100644
index 0000000000000000000000000000000000000000..b1bfbb37c3dba0324536837af4f1b68ef02b1f73
--- /dev/null
+++ b/official/cv/MCNN/scripts/docker_start.sh
@@ -0,0 +1,38 @@
+#!/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
+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 ~/ascend/log/npu/conf/slog/slog.conf:/var/log/npu/conf/slog/slog.conf \
+ -v ~/ascend/log/npu/slog/:/var/log/npu/slog -v ~/ascend/log/npu/profiling/:/var/log/npu/profiling \
+ -v ~/ascend/log/npu/dump/:/var/log/npu/dump -v ~/ascend/log/npu/:/usr/slog ${docker_image} \
+ /bin/bash
\ No newline at end of file