| # Huggingface cloth segmentation using U2NET | |
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| [](https://opensource.org/licenses/MIT) | |
| [](https://colab.research.google.com/drive/1LGgLiHiWcmpQalgazLgq4uQuVUm9ZM4M?usp=sharing) | |
| This repo contains inference code and gradio demo script using pre-trained U2NET model for Cloths Parsing from human portrait.</br> | |
| 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. | |
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| # Gradio Demo | |
| - Run `python app.py` | |
| - Navigate to local or public url provided by app on successfull execution. | |
| ### OR | |
| - Inference in colab from here [](https://colab.research.google.com/drive/1LGgLiHiWcmpQalgazLgq4uQuVUm9ZM4M?usp=sharing) | |
| # Huggingface Demo | |
| - Check gradio demo on Huggingface space from here [huggingface-cloth-segmentation](https://huggingface.co/spaces/wildoctopus/cloth-segmentation). | |
| # Output samples | |
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| This model works well with any background and almost all poses. | |
| # Acknowledgements | |
| - U2net model is from original [u2net repo](https://github.com/xuebinqin/U-2-Net). Thanks to Xuebin Qin for amazing repo. | |
| - Most of the code is taken and modified from [levindabhi/cloth-segmentation](https://github.com/levindabhi/cloth-segmentation) | |