Code for binary segmentation of various cloths
Installation
pip install -U cloths_segmentation
Example inference
Jupyter notebook with the example:
WebApp
https://clothssegmentation.herokuapp.com/
Data Preparation
Download the dataset from https://www.kaggle.com/c/imaterialist-fashion-2019-FGVC6
Process the data using script
The script will create process the data and store images to folder images and binary masks to folder labels.
Training
Define the config.
Example at cloths_segmentation/configs
You can enable / disable datasets that are used for training and validation.
Define the environmental variable IMAGE_PATH that points to the folder with images.
Example:
export IMAGE_PATH=<path to the the folder with images>Define the environmental variable LABEL_PATH that points to the folder with masks.
Example:
export MASK_PATH=<path to the folder with masks>Training
python -m cloths_segmentation.train -c <path to config>
Inference
python -m torch.distributed.launch --nproc_per_node=<num_gpu> cloths_segmentation/inference.py \
-i <path to images> \
-c <path to config> \
-w <path to weights> \
-o <output-path> \
--fp16
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