🎈 SimHIT: A Simple Framework for HIT Pattern Recognition Experiment 🎈

Train and Eval 🚀

• Clone

git clone git@github.com:whlzy/SimHIT.git
cd PR_EXP

• You should modify the path of config/exp_mlp/test_hardswish.yml or config/exp_mlp/test_relu.yml to your local dataset path.

cd config/exp_mlp
cat test_relu.yml
...
...

• You can choose gpu or cpu in the config/exp_mlp/test_hardswish.yml or config/exp_mlp/test_relu.yml.

• You can run the script.

cd ../..
sh scripts/train_hardswish.sh
sh scripts/train_relu.sh

• You can change the net config in the config/exp_mlp/test_hardswish.yml or config/exp_mlp/test_relu.yml.

• You can add some new experiments with just adding new script in scripts and new yaml file in config.

• You can add new dataset in src/data, but maybe need to change some codes.

• You can rewrite a new training code like train_mlp.py using src/runner.py. src/runner.py is a class which assembles partial training process and config process. You just need to use the src/runner.py and rewrite set_data, set_model, train_one_epoch and test_one_epoch like train_mlp.py. Like the train_mlp.py, you can freely modify the network and modify the training process in train_one_epoch.

DataParallel(DP) and DistributedDataParallel(DDP) training

Note: If you want to use DP:

1. you need add "dp: True" to "basic" in your config.yml file.

Note: If you want to use DDP:

1. you need add "ddp: your port" to "basic" in your config.yml file.
2. please remember to add "if rank == 0:".
3. please remember to modify the sampler in torch.utils.data.DataLoader.
4. you need a slurm environment.

Note: If you don't need dp or ddp, you can just delete the "dp: True" and "ddp: your port".

EXP Log 📖

EXP log is in the exp/*/test_hardswish.

The output.log is logged by mmcv logging in the exp/*/test_hardswish/output.log.

The config you used is written in the exp/*/test_hardswish/config.yaml.

The tensorboard log is in the exp/*/test_hardswish/logdir.

The best checkpoint is in the exp/*/test_hardswish/checkpoint/best/model_best.pth.

PR_Experiment ⚡

• train mlp.

sh scripts/train_hardswish.sh
sh scripts/train_relu.sh

• train alexnet.

sh scripts/train_AlexNet.sh

• train resnet18.

sh scripts/train_resnet18.sh

Environment Note 🔔

You need install following packages:

thop
yaml
tqdm
pytorch >= 1.6
skimage <= 0.16.2

License ⭐

This project is released under the Apache 2.0 license.

Acknowledgement🪐

Our code is partially borrowed from MMCV and IMDN. Thanks Yiting Zhang and Junjing Huang for their help.

Citation 📣

If you find this project useful in your research, please consider to cite.

@misc{SimHIT,
    title={SimHIT: A Simple Framework for HIT Pattern Recognition Experiment},
    author={Zeyu Lu},
    howpublished = {\url{https://github.com/whlzy/SimHIT}},
    year={2022}
}