High quality model for cloths segmentation.
Project description
cloths_segmentation
Code for binary segmentation of cloths
Data Preparation
Download the dataset from https://www.kaggle.com/c/imaterialist-fashion-2019-FGVC6
Process the data using script https://github.com/ternaus/iglovikov_helper_functions/tree/master/iglovikov_helper_functions/data_processing/prepare_cloths_segmentation
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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