Gradio deployment

https://gradio.app/g/potipot/deepfashion

howto

to train the model you'll have to download the ds from https://github.com/switchablenorms/DeepFashion2 and place it in the datasets/train and datasets/validation directory.

The label failes are already cached and should be loaded automatically - check detector.ipynb to make sure.

Check the startup.sh to see what kind of preprocessing is necessary.

1. Install nvidia apex:

git clone https://github.com/NVIDIA/apex
cd apex
pip install -v --disable-pip-version-check --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./

Make sure your /usr/local/cuda points to cuda-10.2

2. Create the env

conda env create -n deepfashion -f environment.yml

3. Train

python detector.py