u2net-human-seg

U^2-Net - human segmentation

Input

(Image from https://github.com/xuebinqin/U-2-Net/blob/master/test_data/test_human_images/5-mental-skills-of-successful-athletes-image.jpg)

• Ailia input shape: (1, 3, 320, 320)

Output

Usage

Automatically downloads the onnx and prototxt files on the first run. It is necessary to be connected to the Internet while downloading.

For the sample image,

$ python3 u2net-human-seg.py

If you want to specify the input image, put the image path after the --input option.
You can use --savepath option to change the name of the output file to save.

$ python3 u2net-human-seg.py --input IMAGE_PATH --savepath SAVE_IMAGE_PATH

By adding the --video option, you can input the video.
If you pass 0 as an argument to VIDEO_PATH, you can use the webcam input instead of the video file.

$ python3 u2net-human-seg.py --video VIDEO_PATH

Add the --composite option if you want to combine the input image with the calculated alpha value.

$ python3 u2net-human-seg.py --input IMAGE_PATH --savepath SAVE_IMAGE_PATH --composite

Reference

• U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection

Framework

PyTorch

Model Format

ONNX opset = 11

Netron

u2net-human-seg.onnx.prototxt