Getting Started

June 20, 2022 ยท View on GitHub

This document provides a brief intro of the usage of builtin command-line tools in derain-toolbox.

For a tutorial that involves actual coding with the API, see our Colab Notebook which covers how to run inference with an existing model, and how to train a builtin model on a custom dataset.

Training

Two scripts in "train.py" and "dist_train.sh" are made to train all the configs provided in this repo. You may want to use it as a reference to write your own training script.

To train a model, first setup the corresponding datasets following dataset preparation, then run:

# single-gpu training
python train.py ${CONFIG_FILE} [optional arguments]

# multi-gpu training
./dist_train.sh ${CONFIG_FILE} ${GPU_NUM} [optional arguments]

Optional arguments are:

  • --work-dir ${WORK_DIR}: Override the working directory specified in the config file.
  • --resume-from ${CHECKPOINT_FILE}: Resume from a previous checkpoint file.
  • --no-validate: By default, the codebase will perform evaluation every k iterations during the training. To disable this behavior, use --no-validate
  • --cfg-options: If specified, the key-value pair optional cfg will be merged into config file.

Testing

The evaluate a model's performance, use:

# single-gpu testing
python test.py ${CONFIG_FILE} ${CHECKPOINT_FILE} [optional arguments]

# multi-gpu testing
./dist_test.sh ${CONFIG_FILE} ${CHECKPOINT_FILE} ${GPU_NUM} [optional arguments]

Optional arguments are:

  • --out: Specify the filename of the output results in pickle format. If not given, the results will not be saved to a file.
  • --save-path: Specify the path to store edited images. If not given, the images will not be saved.
  • --seed: Random seed during testing. This argument is used for fixed results in some tasks such as inpainting.
  • --deterministic: Related to --seed, this argument decides whether to set deterministic options for CUDNN backend. If specified, it will set torch.backends.cudnn.deterministic to True and torch.backends.cudnn.benchmark to False.
  • --cfg-options: If specified, the key-value pair optional cfg will be merged into config file.