metadata

title: Cloth Segmentation
emoji: 🏃
colorFrom: yellow
colorTo: purple
sdk: gradio
sdk_version: 3.36.0
app_file: app.py
pinned: false
license: mit

Huggingface cloth segmentation using U2NET

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.

Inference

clone the repo git clone https://github.com/wildoctopus/huggingface-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.

Gradio Demo

Run `python app.py'
Navigate to local or public url provided by app on successfull execution.

OR

Inference in colab from here

Huggingface Demo

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

Output samples

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

Acknowledgements

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