Binder is a free service where the webcam will not work, and performance on the video will not be good. For best performance, it is recommended to install the notebooks locally.
This notebook contains a 3D multi-person pose estimation demo.The model used in this demo is based on Lightweight OpenPose and Single-Shot Multi-Person 3D Pose Estimation From Monocular RGB. It detects 2D coordinates of up to 18 types of key points: ears, eyes, nose, neck, shoulders, elbows, wrists, hips, knees, and ankles, as well as their 3D coordinates, which may then be used to construct the 3D display of human poses. OpenVINO™ is used to accelerate the inference on multiple devices, such as CPU, GPU. Also, this 3D display method may be extended to display the inference results of other 3D models without much effort.
This notebook uses the "human-pose-estimation-3d-0001" model from OpenVINO Open Model Zoo to estimate 3D human pose and represent it on a 2D screen. Details of the model can be found here. The input source may be video files or webcam feed. It uses the Three.js Python API to display 3D results in a web browser. To display the 3D inference results properly on Windows and Ubuntu, it is recommended to use Chrome web browser. For macOS, Safari is recommended.
If you have not installed all required dependencies, follow the Installation Guide.
Make sure your Jupyter extension is working properly. To avoid errors that may arise from the version of the dependency package, it is recommended to use the JupyterLab instead of the Jupyter notebook to display image results.
- pip install --upgrade pip && pip install -r requirements.txt
- jupyter labextension install --no-build @jupyter-widgets/jupyterlab-manager
- jupyter labextension install --no-build jupyter-datawidgets/extension
- jupyter labextension install jupyter-threejs
- jupyter labextension list
You should see:
JupyterLab v...
...
jupyterlab-datawidgets v... enabled OK
@jupyter-widgets/jupyterlab-manager v... enabled OK
jupyter-threejs v... enabled OK