# Person detector from MediaPipe Pose This model detects upper body and full body keypoints of a person, and is downloaded from https://github.com/PINTO0309/PINTO_model_zoo/blob/main/053_BlazePose/20_densify_pose_detection/download.sh or converted from TFLite to ONNX using following tools: - TFLite model to ONNX with MediaPipe custom `densify` op: https://github.com/PINTO0309/tflite2tensorflow - simplified by [onnx-simplifier](https://github.com/daquexian/onnx-simplifier) SSD Anchors are generated from [GenMediaPipePalmDectionSSDAnchors](https://github.com/VimalMollyn/GenMediaPipePalmDectionSSDAnchors) **Note**: - `person_detection_mediapipe_2023mar_int8bq.onnx` represents the block-quantized version in int8 precision and is generated using [block_quantize.py](../../tools/quantize/block_quantize.py) with `block_size=64`. ## Demo ### Python Run the following commands to try the demo: ```bash # detect on camera input python demo.py # detect on an image python demo.py -i /path/to/image -v # get help regarding various parameters python demo.py --help ``` ### C++ Install latest OpenCV and CMake >= 3.24.0 to get started with: ```shell # A typical and default installation path of OpenCV is /usr/local cmake -B build -D OPENCV_INSTALLATION_PATH=/path/to/opencv/installation . cmake --build build # detect on camera input ./build/opencv_zoo_person_detection_mediapipe # detect on an image ./build/opencv_zoo_person_detection_mediapipe -m=/path/to/model -i=/path/to/image -v # get help messages ./build/opencv_zoo_person_detection_mediapipe -h ``` ### Example outputs ![webcam demo](./example_outputs/mppersondet_demo.webp) ## License All files in this directory are licensed under [Apache 2.0 License](LICENSE). ## Reference - MediaPipe Pose: https://developers.google.com/mediapipe/solutions/vision/pose_landmarker - MediaPipe pose model and model card: https://github.com/google/mediapipe/blob/master/docs/solutions/models.md#pose - BlazePose TFJS: https://github.com/tensorflow/tfjs-models/tree/master/pose-detection/src/blazepose_tfjs