This repo contains inference code and gradio demo script using pre-trained U2NET model for Cloths Parsing from human portrait. Here clothes are parsed into 3 category: Upper body(red), Lower body(green) and Full body(yellow). The provided script also generates alpha images for each class.

clone the repo git clone git@github.com:asadrizvi64/Cloth-segmentation.git.

Install dependencies pip install -r requirements.txt

Run python process.py --image 'input/03615_00.jpg' . Script will automatically download the pretrained model.

Outputs will be saved in output folder.

output/alpha/.. contains alpha images corresponding to each class.

output/cloth_seg contains final segmentation.

Run python app.py

Navigate to local or public url provided by app on successfull execution.

Inference in colab from here

Check gradio demo on Huggingface space from here huggingface-cloth-segmentation.

This model works well with any background and almost all poses.

U2net model is from original u2net repo. Thanks to Xuebin Qin for amazing repo.

Most of the code is taken and modified from levindabhi/cloth-segmentation