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ROS ov2.0 #195
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| # This file can be used with the --list option of the model converter. | ||
| mobilenet-ssd | ||
| deeplabv3 | ||
| mask_rcnn_inception_resnet_v2_atrous_coco | ||
| vehicle-license-plate-detection-barrier-0123 |
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| # This file can be used with the --list option of the model downloader. | ||
| face-detection-adas-0001 | ||
| age-gender-recognition-retail-0013 | ||
| emotions-recognition-retail-0003 | ||
| landmarks-regression-retail-0009 | ||
| license-plate-recognition-barrier-0001 | ||
| person-detection-retail-0013 | ||
| person-attributes-recognition-crossroad-0230 | ||
| person-reidentification-retail-0277 | ||
| vehicle-attributes-recognition-barrier-0039 | ||
| vehicle-license-plate-detection-barrier-0106 | ||
| head-pose-estimation-adas-0001 | ||
| human-pose-estimation-0001 | ||
| semantic-segmentation-adas-0001 | ||
| mobilenet-ssd | ||
| deeplabv3 | ||
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| # ROS_NOETIC_OpenVINO_Toolkit | ||
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| **NOTE:** | ||
| Below steps have been tested on **Ubuntu 20.04**. | ||
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| ## 1. Environment Setup | ||
| * Install ROS Noetic ([guide](http://wiki.ros.org/noetic/Installation/Ubuntu)). | ||
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| * Install Intel® OpenVINO™ Toolkit Version: 2022.1 ([guide](https://docs.openvino.ai/2022.1/openvino_docs_install_guides_installing_openvino_linux.html)). | ||
| * Install from an achive file ([guide](https://www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/download.html)). | ||
| Tips: Both runtime and development tool are needed, `pip` is recommended for installing the development tool ([guide](https://docs.openvino.ai/latest/openvino_docs_install_guides_install_dev_tools.html)). | ||
| * Install from source code ([guide](https://github.com/openvinotoolkit/openvino/wiki/BuildingForLinux)). | ||
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| * Install Intel® RealSense ™ SDK ([guide](https://github.com/IntelRealSense/librealsense/blob/master/doc/distribution_linux.md)). | ||
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| * Install Dependency | ||
| * Install gflags | ||
| ``` | ||
| sudo apt-get install -y libgflags-dev | ||
| ``` | ||
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| ## 2. Build and Installation | ||
| * Install ROS_OpenVINO_Toolkit packages | ||
| ``` | ||
| mkdir -p ~/catkin_ws/src | ||
| cd ~/catkin_ws/src | ||
| git clone https://github.com/intel/ros_openvino_toolkit -b noetic | ||
| git clone https://github.com/intel/object_msgs | ||
| git clone https://github.com/IntelRealSense/realsense-ros.git | ||
| cd realsense-ros | ||
| git checkout `git tag | sort -V | grep -P "^2.\d+\.\d+" | tail -1` | ||
| ``` | ||
| * Install dependencies | ||
| ``` | ||
| sudo apt-get install ros-noetic-ddynamic-reconfigure | ||
| ``` | ||
| * Build package | ||
| ``` | ||
| source /opt/ros/noetic/setup.bash | ||
| source <OpenVINO_INSTALL_DIR>/setupvars.sh | ||
| cd ~/catkin_ws | ||
| catkin_make_isolated | ||
| source ./devel_isolated/setup.bash | ||
| ``` | ||
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| ## 3. Running the Demo | ||
| ### Install OpenVINO 2022.1 by source code | ||
| * See all available models | ||
| ``` | ||
| cd <OpenVINO_SOURCECODE_DIR>/openvino/thirdparty/open_model_zoo/tools/model_tools | ||
| sudo python3 downloader.py --print_all | ||
| ``` | ||
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| * Download the optimized Intermediate Representation (IR) of model (execute once): | ||
| ``` | ||
| cd <OpenVINO_SOURCECODE_DIR>/openvino/thirdparty/open_model_zoo/tools/model_tools | ||
| sudo python3 downloader.py --name face-detection-adas-0001 --output_dir /opt/openvino_toolkit/models/face_detection/output | ||
| sudo python3 downloader.py --name age-gender-recognition-retail-0013 --output_dir /opt/openvino_toolkit/models/age-gender-recognition/output | ||
| sudo python3 downloader.py --name emotions-recognition-retail-0003 --output_dir /opt/openvino_toolkit/models/emotions-recognition/output | ||
| sudo python3 downloader.py --name head-pose-estimation-adas-0001 --output_dir /opt/openvino_toolkit/models/head-pose-estimation/output | ||
| sudo python3 downloader.py --name person-detection-retail-0013 --output_dir /opt/openvino_toolkit/models/person-detection/output | ||
| sudo python3 downloader.py --name person-reidentification-retail-0277 --output_dir /opt/openvino_toolkit/models/person-reidentification/output | ||
| sudo python3 downloader.py --name landmarks-regression-retail-0009 --output_dir /opt/openvino_toolkit/models/landmarks-regression/output | ||
| sudo python3 downloader.py --name face-reidentification-retail-0095 --output_dir /opt/openvino_toolkit/models/face-reidentification-retail/output | ||
| sudo python3 downloader.py --name vehicle-attributes-recognition-barrier-0039 --output_dir /opt/openvino_toolkit/models/vehicle-attributes-recognition/output | ||
| sudo python3 downloader.py --name license-plate-recognition-barrier-0001 --output_dir /opt/openvino_toolkit/models/license-plate-recognition/output | ||
| ``` | ||
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| * If the model (tensorflow, caffe, MXNet, ONNX, Kaldi)need to be converted to intermediate representation (For example the model for object detection) | ||
| * mobilenet-ssd (replaced ssd_mobilenet_v2_coco to mobilenet-ssd for object detection in ov2022) | ||
| ``` | ||
| cd <OpenVINO_SOURCECODE_DIR>/openvino/thirdparty/open_model_zoo/tools/model_tools | ||
| sudo python3 downloader.py --name mobilenet-ssd --output_dir /opt/openvino_toolkit/models/object_detection/mobilenet_ssd/output | ||
| sudo python3 converter.py --name mobilenet-ssd -d /opt/openvino_toolkit/models/object_detection/mobilenet_ssd/output/ -o /opt/openvino_toolkit/models/object_detection/mobilenet_ssd/output/convert | ||
| ``` | ||
| * vehicle-license-plate-detection-barrier-0123 | ||
| ``` | ||
| cd <OpenVINO_SOURCECODE_DIR>/openvino/thirdparty/open_model_zoo/tools/model_tools | ||
| sudo python3 downloader.py --name vehicle-license-plate-detection-barrier-0123 --output_dir /opt/openvino_toolkit/models/vehicle-license-plate-detection-barrier/output | ||
| sudo python3 converter.py --name vehicle-license-plate-detection-barrier-0123 -d /opt/openvino_toolkit/models/vehicle-license-plate-detection-barrier/output -o /opt/openvino_toolkit/models/vehicle-license-plate-detection-barrier/output/convert | ||
| ``` | ||
| * deeplabv3 | ||
| ``` | ||
| cd <OpenVINO_SOURCECODE_DIR>/openvino/thirdparty/open_model_zoo/tools/model_tools | ||
| sudo python3 downloader.py --name deeplabv3 --output_dir /opt/openvino_toolkit/models/deeplabv3/output | ||
| sudo python3 converter.py --name deeplabv3 -d /opt/openvino_toolkit/models/deeplabv3/output -o /opt/openvino_toolkit/models/deeplabv3/output/convert | ||
| ``` | ||
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| * Copy label files (execute once) | ||
| * Before launch, copy label files to the same model path, make sure the model path and label path match the ros_openvino_toolkit/vino_launch/param/xxxx.yaml. | ||
| ``` | ||
| sudo cp ~/catkin_ws/src/ros_openvino_toolkit/data/labels/emotions-recognition/FP32/emotions-recognition-retail-0003.labels /opt/openvino_toolkit/models/emotions-recognition/output/intel/emotions-recognition-retail-0003/FP32/ | ||
| sudo cp ~/catkin_ws/src/ros_openvino_toolkit/data/labels/emotions-recognition/FP32/emotions-recognition-retail-0003.labels /opt/openvino_toolkit/models/emotions-recognition/output/intel/emotions-recognition-retail-0003/FP16/ | ||
| sudo cp ~/catkin_ws/src/ros_openvino_toolkit/data/labels/face_detection/face-detection-adas-0001.labels /opt/openvino_toolkit/models/face_detection/output/intel/face-detection-adas-0001/FP32/ | ||
| sudo cp ~/catkin_ws/src/ros_openvino_toolkit/data/labels/face_detection/face-detection-adas-0001.labels /opt/openvino_toolkit/models/face_detection/output/intel/face-detection-adas-0001/FP16/ | ||
| sudo cp ~/catkin_ws/src/ros_openvino_toolkit/data/labels/object_detection/vehicle-license-plate-detection-barrier-0106.labels /opt/openvino_toolkit/models/vehicle-license-plate-detection/output/convert/intel/vehicle-license-plate-detection-barrier-0106/FP32 | ||
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There was a problem hiding this comment. There is used FP16/vehicle-license-plate-detection-barrier-0106.labels at the pipeline_vehicle_detection.yaml. but there are FP32 |
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| sudo cp ~/catkin_ws/src/ros_openvino_toolkit/data/labels/object_detection/mobilenet-ssd.labels /opt/openvino_toolkit/models/object_detection/mobilenet_ssd/output/convert/public/mobilenet-ssd/FP16 | ||
| sudo cp ~/catkin_ws/src/ros_openvino_toolkit/data/labels/object_segmentation/frozen_inference_graph.labels /opt/openvino_toolkit/models/deeplabv3/output/convert/public/deeplabv3/FP16 | ||
| sudo mv /opt/openvino_toolkit/models/deeplabv3/output/convert/public/deeplabv3/FP16/frozen_inference_graph.labels /opt/openvino_toolkit/models/deeplabv3/output/convert/public/deeplabv3/FP16/deeplabv3.labels | ||
| ``` | ||
| ### Install OpenVINO 2022.1 by PIP | ||
| * OMZ tools are provided for downloading and converting OMZ models in ov2022 ([guide](https://pypi.org/project/openvino-dev/)). | ||
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| * See all available models | ||
| ``` | ||
| omz_downloader --print_all | ||
| ``` | ||
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| * Download the optimized Intermediate Representation (IR) of model (execute once), for example: | ||
| ``` | ||
| omz_downloader --name face-detection-adas-0001 --output_dir /opt/openvino_toolkit/models/face_detection/output | ||
| omz_downloader --name age-gender-recognition-retail-0013 --output_dir /opt/openvino_toolkit/models/age-gender-recognition/output | ||
| omz_downloader --name emotions-recognition-retail-0003 --output_dir /opt/openvino_toolkit/models/emotions-recognition/output | ||
| omz_downloader --name head-pose-estimation-adas-0001 --output_dir /opt/openvino_toolkit/models/head-pose-estimation/output | ||
| omz_downloader --name person-detection-retail-0013 --output_dir /opt/openvino_toolkit/models/person-detection/output | ||
| omz_downloader --name person-reidentification-retail-0277 --output_dir /opt/openvino_toolkit/models/person-reidentification/output | ||
| omz_downloader --name landmarks-regression-retail-0009 --output_dir /opt/openvino_toolkit/models/landmarks-regression/output | ||
| omz_downloader --name semantic-segmentation-adas-0001 --output_dir /opt/openvino_toolkit/models/semantic-segmentation/output | ||
| omz_downloader --name vehicle-attributes-recognition-barrier-0039 --output_dir /opt/openvino_toolkit/models/vehicle-attributes-recognition/output | ||
| omz_downloader --name license-plate-recognition-barrier-0001 --output_dir /opt/openvino_toolkit/models/license-plate-recognition/output | ||
| ``` | ||
| * Copy label files (execute once) | ||
| ``` | ||
| sudo cp ~/catkin_ws/src/ros_openvino_toolkit/data/labels/emotions-recognition/FP32/emotions-recognition-retail-0003.labels /opt/openvino_toolkit/models/emotions-recognition/output/intel/emotions-recognition-retail-0003/FP32/ | ||
| sudo cp ~/catkin_ws/src/ros_openvino_toolkit/data/labels/emotions-recognition/FP32/emotions-recognition-retail-0003.labels /opt/openvino_toolkit/models/emotions-recognition/output/intel/emotions-recognition-retail-0003/FP16/ | ||
| sudo cp ~/catkin_ws/src/ros_openvino_toolkit/data/labels/face_detection/face-detection-adas-0001.labels /opt/openvino_toolkit/models/face_detection/output/intel/face-detection-adas-0001/FP32/ | ||
| sudo cp ~/catkin_ws/src/ros_openvino_toolkit/data/labels/face_detection/face-detection-adas-0001.labels /opt/openvino_toolkit/models/face_detection/output/intel/face-detection-adas-0001/FP16/ | ||
| sudo cp ~/catkin_ws/src/ros_openvino_toolkit/data/labels/object_detection/vehicle-license-plate-detection-barrier-0106.labels /opt/openvino_toolkit/models/vehicle-license-plate-detection/output/convert/intel/vehicle-license-plate-detection-barrier-0106/FP32 | ||
| sudo cp ~/catkin_ws/src/ros_openvino_toolkit/data/labels/object_detection/mobilenet-ssd.labels /opt/openvino_toolkit/models/object_detection/mobilenet_ssd/output/convert/public/mobilenet-ssd/FP16 | ||
| sudo cp ~/catkin_ws/src/ros_openvino_toolkit/data/labels/object_segmentation/frozen_inference_graph.labels /opt/openvino_toolkit/models/deeplabv3/output/convert/public/deeplabv3/FP16 | ||
| sudo mv /opt/openvino_toolkit/models/deeplabv3/output/convert/public/deeplabv3/FP16/frozen_inference_graph.labels /opt/openvino_toolkit/models/deeplabv3/output/convert/public/deeplabv3/FP16/deeplabv3.labels | ||
| ``` | ||
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| * If the model (tensorflow, caffe, MXNet, ONNX, Kaldi) need to be converted to intermediate representation (such as the model for object detection): | ||
| * mobilenet-ssd (replaced ssd_mobilenet_v2_coco to mobilenet-ssd for object detection in ov2022) | ||
| ``` | ||
| omz_downloader --name mobilenet-ssd --output_dir /opt/openvino_toolkit/models/object_detection/mobilenet_ssd/output | ||
| omz_converter --name mobilenet-ssd -d /opt/openvino_toolkit/models/object_detection/mobilenet_ssd/output -o /opt/openvino_toolkit/models/object_detection/mobilenet_ssd/output/convert | ||
| ``` | ||
| * vehicle-license-plate-detection-barrier-0123 | ||
| ``` | ||
| omz_downloader --name vehicle-license-plate-detection-barrier-0123 --output_dir /opt/openvino_toolkit/models/vehicle-license-plate-detection-barrier/output | ||
| omz_converter --name vehicle-license-plate-detection-barrier-0123 -d /opt/openvino_toolkit/models/vehicle-license-plate-detection-barrier/output -o /opt/openvino_toolkit/models/vehicle-license-plate-detection-barrier/output/convert | ||
| ``` | ||
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| * deeplabv3 | ||
| ``` | ||
| omz_downloader --name deeplabv3 --output_dir /opt/openvino_toolkit/models/deeplabv3/output | ||
| omz_converter --name deeplabv3 -d /opt/openvino_toolkit/models/deeplabv3/output -o /opt/openvino_toolkit/models/deeplabv3/output/convert | ||
| ``` | ||
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| * Please check the parameter configuration in ros_openvino_toolkit/sample/param/xxxx.yaml before lauching, make sure parameters such as model_path, label_path and input_path are set correctly. | ||
| * run face detection sample code input from StandardCamera. | ||
| ``` | ||
| roslaunch vino_launch pipeline_people.launch | ||
| ``` | ||
| * run person reidentification sample code input from StandardCamera. | ||
| ``` | ||
| roslaunch vino_launch pipeline_face_reidentification.launch | ||
| ``` | ||
| * run person reidentification sample code input from StandardCamera | ||
| ``` | ||
| roslaunch vino_launch pipeline_reidentification.launch | ||
| ``` | ||
| * run face detection sample code input from Image. | ||
| ``` | ||
| roslaunch vino_launch pipeline_image.launch | ||
| ``` | ||
| * run object sample | ||
| ``` | ||
| roslaunch vino_launch pipeline_object.launch | ||
| ``` | ||
| * run object topic sample | ||
| ``` | ||
| roslaunch vino_launch pipeline_object_topic.launch | ||
| ``` | ||
| * run object segmentation sample code input from RealSenseCamera. | ||
| ``` | ||
| roslaunch vino_launch pipeline_segmentation.launch | ||
| ``` | ||
| * run vehicle detection sample code input from StandardCamera. | ||
| ``` | ||
| roslaunch vino_launch pipeline_vehicle_detection.launch | ||
| ``` | ||
| * run video sample | ||
| ``` | ||
| roslaunch vino_launch pipeline_video.launch | ||
| ``` | ||
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| # More Information | ||
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| ###### *Any security issue should be reported using process at https://01.org/security* | ||
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no found the xml: face-reidentification-retail-0095.xml
if it is need.
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and the xml vehicle-license-plate-detection-barrier-0123.xml
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Fixed.