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