hands_segmentation_pytorch

Hands Segmentation - A Plug and Play Model

Input

• Image or Video

Output

• Predicted mask

Estimated mask of the hands(without option --overlay), or a mask overlayed over the original image(with option --overlay). The image above was made with the overlay option enabled.

The result will be saved to ./output.png by default but it can be specified with the -s option

Usage

An Internet connection is required when running the script for the first time, as the model files will be downloaded automatically.

The predicted mask of the hands in the input media will be generated by running the script.

Example 1: Inference on prepared demo image.

$ python3 hands_segmentation_pytorch.py

Example 2: Specify input path, save path.

$ python3 hands_segmentation_pytorch.py -i input.png -s output.png

-i, -s options can be used to specify the input path and the save path.

Example 3: Specify the size of the image, and visualize the overlayed mask.

$ python3 hands_segmentation_pytorch.py --width 512 --height 512 --overlay

Use options --width and height to specify the image size on which the model will be running inference. The result will always be resized to the original size of the image. You can visualize the result with a mask overlayed over the original image using the option --overlay.

Example 4: Inference on Video.

$ python3 hands_segmentation_pytorch.py -v 0

argument after the -v option can be the device ID of the webcam, or the path to the input video.

Reference

• hands-segmentation-pytorch

Framework

Pytorch

Model Format

ONNX opset=11

Netron

• hands_segmentation_pytorch.onnx.prototxt