# PicoDet OpenVINO Demo This fold provides PicoDet inference code using [Intel's OpenVINO Toolkit](https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit.html). Most of the implements in this fold are same as *demo_ncnn*. **Recommand** to use the xxx.tar.gz file to install instead of github method, [link](https://registrationcenter-download.intel.com/akdlm/irc_nas/18096/l_openvino_toolkit_p_2021.4.689.tgz). ## Install OpenVINO Toolkit Go to [OpenVINO HomePage](https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit.html) Download a suitable version and install. Follow the official Get Started Guides: https://docs.openvinotoolkit.org/latest/get_started_guides.html ## Set the Environment Variables ### Windows: Run this command in cmd. (Every time before using OpenVINO) ```cmd \openvino_2021\bin\setupvars.bat ``` Or set the system environment variables once for all: Name |Value :--------------------:|:--------: INTEL_OPENVINO_DIR | \openvino_2021 INTEL_CVSDK_DIR | %INTEL_OPENVINO_DIR% InferenceEngine_DIR | %INTEL_OPENVINO_DIR%\deployment_tools\inference_engine\share HDDL_INSTALL_DIR | %INTEL_OPENVINO_DIR%\deployment_tools\inference_engine\external\hddl ngraph_DIR | %INTEL_OPENVINO_DIR%\deployment_tools\ngraph\cmake And add this to ```Path``` ``` %INTEL_OPENVINO_DIR%\deployment_tools\inference_engine\bin\intel64\Debug;%INTEL_OPENVINO_DIR%\deployment_tools\inference_engine\bin\intel64\Release;%HDDL_INSTALL_DIR%\bin;%INTEL_OPENVINO_DIR%\deployment_tools\inference_engine\external\tbb\bin;%INTEL_OPENVINO_DIR%\deployment_tools\ngraph\lib ``` ### Linux Run this command in shell. (Every time before using OpenVINO) ```shell source /opt/intel/openvino_2021/bin/setupvars.sh ``` Or edit .bashrc ```shell vi ~/.bashrc ``` Add this line to the end of the file ```shell source /opt/intel/openvino_2021/bin/setupvars.sh ``` ## Convert model Convert to OpenVINO ``` shell cd /openvino_2021/deployment_tools/model_optimizer ``` Install requirements for convert tool ```shell cd ./install_prerequisites sudo install_prerequisites_onnx.sh ``` Then convert model. Notice: mean_values and scale_values should be the same with your training settings in YAML config file. ```shell python3 mo_onnx.py --input_model --mean_values [103.53,116.28,123.675] --scale_values [57.375,57.12,58.395] ``` ## Build ### Windows ```cmd \openvino_2021\bin\setupvars.bat mkdir -p build cd build cmake .. msbuild picodet_demo.vcxproj /p:configuration=release /p:platform=x64 ``` ### Linux ```shell source /opt/intel/openvino_2021/bin/setupvars.sh mkdir build cd build cmake .. make ``` ## Run demo Download PicoDet openvino model [PicoDet openvino model download link](https://paddledet.bj.bcebos.com/deploy/third_engine/picodet_m_416_openvino.zip). move picodet openvino model files to the demo's weight folder. Then run these commands: ### Edit file ``` step1: main.cpp #define image_size 416 ... auto detector = PicoDet("../weight/picodet_m_416.xml"); ... step2: picodet_openvino.h #define image_size 416 ``` ### Webcam ```shell picodet_demo 0 0 ``` ### Inference images ```shell picodet_demo 1 IMAGE_FOLDER/*.jpg ``` ### Inference video ```shell picodet_demo 2 VIDEO_PATH ``` ### Benchmark ```shell picodet_demo 3 0 ```