算法部署-使用OpenVINO在CPU平台部署实时图像分割算法DeeplabV3-项目源码-优质项目实战.zip

# OpenVINO-DeeplabV3 # Environment - LattePanda Alpha (Intel 7th Core m3-7y30) or LaptopPC (Intel 8th Core i7-8750H) - Ubuntu 16.04 x86_64 - OpenVINO toolkit 2018 R4 (2018.4.420) - Python 3.5 - OpenCV 3.4.3 - PIL - Tensorflow v1.11.0 or Tensorflow-GPU v1.11.0 (pip install) - DeeplabV3 + MobilenetV2 (Pascal VOC 2012) - USB Camera (PlaystationEye) / Movie file (mp4) - 【option】 Intel Neural Compute Stick / Intel Neural Compute Stick 2 or GPU # Usage ### 1. Installation of OpenVINO main unit #### 1.1 Download ```bash $ cd ~/Downloads $ curl -sc /tmp/cookie "https://drive.google.com/uc?export=download&id=18-TeUzeN34CV-QqM0rO3wpdEGODTWrBc" > /dev/null $ CODE="$(awk '/_warning_/ {print $NF}' /tmp/cookie)" $ curl -Lb /tmp/cookie "https://drive.google.com/uc?export=download&confirm=${CODE}&id=18-TeUzeN34CV-QqM0rO3wpdEGODTWrBc" -o l_openvino_toolkit_p_2018.4.420.tgz $ tar -zxf l_openvino_toolkit_p_2018.4.420.tgz $ rm l_openvino_toolkit_p_2018.4.420.tgz $ cd l_openvino_toolkit_p_2018.4.420 ``` #### 1.2 Install basic functions ```bash ## GUI version installer $ sudo ./install_GUI.sh or ## CUI version installer $ sudo ./install.sh ``` <img src="media/01.jpg" width=60%> <img src="media/02.jpg" width=60%> <img src="media/03.jpg" width=60%> ```bash $ cd /opt/intel/computer_vision_sdk/install_dependencies $ sudo -E ./install_cv_sdk_dependencies.sh $ nano ~/.bashrc source /opt/intel/computer_vision_sdk/bin/setupvars.sh $ source ~/.bashrc $ cd /opt/intel/computer_vision_sdk/deployment_tools/model_optimizer/install_prerequisites $ sudo ./install_prerequisites.sh ``` #### 1.3 Install optional features ##### 1.3.1 【Optional execution】 Additional installation steps for the Intel® Movidius™ Neural Compute Stick v1 and Intel® Neural Compute Stick v2 ```bash $ sudo usermod -a -G users "$(whoami)" $ cat <<EOF > 97-usbboot.rules SUBSYSTEM=="usb", ATTRS{idProduct}=="2150", ATTRS{idVendor}=="03e7", GROUP="users", MODE="0666", ENV{ID_MM_DEVICE_IGNORE}="1" SUBSYSTEM=="usb", ATTRS{idProduct}=="2485", ATTRS{idVendor}=="03e7", GROUP="users", MODE="0666", ENV{ID_MM_DEVICE_IGNORE}="1" SUBSYSTEM=="usb", ATTRS{idProduct}=="f63b", ATTRS{idVendor}=="03e7", GROUP="users", MODE="0666", ENV{ID_MM_DEVICE_IGNORE}="1" EOF $ sudo cp 97-usbboot.rules /etc/udev/rules.d/ $ sudo udevadm control --reload-rules $ sudo udevadm trigger $ cd /opt/intel/common/mdf/lib64 $ sudo mv igfxcmrt64.so igfxcmrt64.so.org $ sudo ln -s libigfxcmrt64.so igfxcmrt64.so $ cd /opt/intel/mediasdk/lib64 $ sudo mv libmfxhw64.so.1 libmfxhw64.so.1.org $ sudo mv libmfx.so.1 libmfx.so.1.org $ sudo mv libva-glx.so.2 libva-glx.so.2.org $ sudo mv libva.so.2 libva.so.2.org $ sudo mv libigdgmm.so.1 libigdgmm.so.1.org $ sudo mv libva-drm.so.2 libva-drm.so.2.org $ sudo mv libva-x11.so.2 libva-x11.so.2.org $ sudo ln -s libmfxhw64.so.1.28 libmfxhw64.so.1 $ sudo ln -s libmfx.so.1.28 libmfx.so.1 $ sudo ln -s libva-glx.so.2.300.0 libva-glx.so.2 $ sudo ln -s libva.so.2.300.0 libva.so.2 $ sudo ln -s libigdgmm.so.1.0.0 libigdgmm.so.1 $ sudo ln -s libva-drm.so.2.300.0 libva-drm.so.2 $ sudo ln -s libva-x11.so.2.300.0 libva-x11.so.2 $ sudo ldconfig $ rm 97-usbboot.rules ``` ##### 1.3.2 【Optional execution】 Additional installation steps for processor graphics (GPU) ```bash $ cd /opt/intel/computer_vision_sdk/install_dependencies/ $ sudo -E su $ uname -r 4.15.0-42-generic #<--- display kernel version sample ### Execute only when the kernel version is older than 4.14 $ ./install_4_14_kernel.sh $ ./install_NEO_OCL_driver.sh $ sudo reboot ``` ### 2. Downgrade to stable OpenCV Since OpenCV 4.0.0-pre introduced by default had bug in Gstreamer and it did not work properly, we will reinstall OpenCV 3.4.3 on our own. ```bash $ sudo -H pip3 install opencv-python==3.4.3.18 $ nano ~/.bashrc export PYTHONPATH=/usr/local/lib/python3.5/dist-packages/cv2:$PYTHONPATH $ source ~/.bashrc ``` ### 3. Upgrade to Tensorflow v1.11.0 Upgrade to old version Tensorflow v1.9.0, introduced by default, to Tensorflow v1.11.0, as subsequent model optimizer processing will fail. ```bash $ sudo -H pip3 install pip --upgrade $ python3 -c 'import tensorflow as tf; print(tf.__version__)' 1.9.0 #<--- display Tensorflow version sample $ sudo -H pip3 install tensorflow==1.11.0 --upgrade or $ sudo -H pip3 install tensorflow-gpu==1.11.0 --upgrade ``` ### 4. Settings for offloading custom layer behavior to Tensorflow ```bash $ sudo apt-get install -y git pkg-config zip g++ zlib1g-dev unzip $ cd ~ $ wget https://github.com/bazelbuild/bazel/releases/download/0.18.1/bazel-0.18.1-installer-linux-x86_64.sh $ sudo chmod +x bazel-0.18.1-installer-linux-x86_64.sh $ ./bazel-0.18.1-installer-linux-x86_64.sh --user $ echo 'export PATH=$PATH:$HOME/bin' >> ~/.bashrc $ source ~/.bashrc $ cd /opt $ sudo git clone -b v1.11.0 https://github.com/tensorflow/tensorflow.git $ cd tensorflow $ sudo git checkout -b v1.11.0 $ echo 'export TF_ROOT_DIR=/opt/tensorflow' >> ~/.bashrc $ source ~/.bashrc $ sudo nano /opt/intel/computer_vision_sdk/bin/setupvars.sh #Before INSTALLDIR=/opt/intel//computer_vision_sdk_2018.4.420 ↓ #After INSTALLDIR=/opt/intel/computer_vision_sdk_2018.4.420 $ source /opt/intel/computer_vision_sdk/bin/setupvars.sh $ sudo nano /opt/intel/computer_vision_sdk/deployment_tools/model_optimizer/tf_call_ie_layer/build.sh #Before bazel build --config=monolithic //tensorflow/cc/inference_engine_layer:libtensorflow_call_layer.so ↓ #After sudo -H $HOME/bin/bazel build --config monolithic //tensorflow/cc/inference_engine_layer:libtensorflow_call_layer.so or sudo -H $HOME/bin/bazel --host_jvm_args=-Xmx512m build --config monolithic --local_resources 1024.0,0.5,0.5 //tensorflow/cc/inference_engine_layer:libtensorflow_call_layer.so $ sudo -E /opt/intel/computer_vision_sdk/deployment_tools/model_optimizer/tf_call_ie_layer/build.sh $ su - $ cp /opt/tensorflow/bazel-bin/tensorflow/cc/inference_engine_layer/libtensorflow_call_layer.so /usr/local/lib $ exit $ nano ~/.bashrc export PYTHONPATH=$PYTHONPATH:/usr/local/lib $ source ~/.bashrc $ sudo ldconfig ``` ### 5. 【Optional execution】 Build sample programs and CPU extension ```bash $ cd /opt/intel/computer_vision_sdk/deployment_tools/inference_engine/samples $ sudo ./build_samples.sh ### The prebuilt binary is saved in the following path ### ~/inference_engine_samples_build/intel64/Release/ ``` ### 6. 【Optional execution】【Example】 Conversion of Tensorflow-DeeplabV3 model to lr format #### 6-1. Pascal VOC ```bash $ cd ~ $ mkdir model $ wget http://download.tensorflow.org/models/deeplabv3_mnv2_pascal_train_aug_2018_01_29.tar.gz $ tar -zxvf deeplabv3_mnv2_pascal_train_aug_2018_01_29.tar.gz $ cp deeplabv3_mnv2_pascal_train_aug/frozen_inference_graph.pb model $ sudo python3 /opt/intel/computer_vision_sdk/deployment_tools/model_optimizer/mo_tf.py \ --input_model pbmodels/PascalVOC/frozen_inference_graph.pb \ --input 0:MobilenetV2/Conv/Conv2D \ --output ArgMax \ --input_shape [1,513,513,3] \ --output_dir lrmodels/PascalVOC/FP32 ``` #### 6-2. MS-COCO cityscapes ```bash $ wget http://download.tensorflow.org/models/deeplabv3_mnv2_cityscapes_train_2018_02_05.tar.gz $ tar -zxvf deeplabv3_mnv2_cityscapes_train_2018_02_05.tar.gz ``` ### 7. Execution (The default is "USB Camera mode") ```bash $ cd ~ $ git clone https://github.com/PINTO0309/OpenVINO-DeeplabV3.git $ cd OpenVINO-DeeplabV3 $ python3 openvino_deeplabv3_test.py ``` # How to install Bazel (version 0.17.2, x86_64 only) ### 1. Bazel introduction command ```bash $ cd ~ $ curl -sc /tmp/cookie "https://drive.google.com/uc?export=download&id=1dvR3pdM6vtkTWqeR-DpgVUoDV0EYWil5" > /dev/null $ CODE="$(awk '/_warning_/ {print $NF}' /tmp/cookie)" $ curl -Lb /tmp/cookie "https://drive.google.com/uc?export=download&confirm=${CODE}&id=1dvR3pdM6vtkTWqeR-DpgVUoDV0EYWil5" -o bazel $ sudo cp ./bazel /usr/local/bin $ rm ./bazel ``` ### 2. Supplementary information **https://github.com/PINTO0309/Bazel_bin.git** # How to check the graph structure of a ".pb" file [Part.1] Simple structur