RegNet-pytorch
A pytorch implement of RegNet (Designing Netowrk design spaces). Original paper link: https://arxiv.org/pdf/2003.13678.pdf
The performance of this repository hasn't been tested because of lacking resource on the computation, which may update in the future.
How to Use
1.Dataset
Prepare a train.txt(or a val.txt) file for training(testing) your custom dataset.
train.txt is organized as:
your/data/path/img_0.jpg 0(label of img_0.jpg)
your/data/path/img_1.jpg 1
......
The separator between img_path and its_label is '\t'
2.training
1. Create a 'training.yml' file like 'AnyNet_cpu.yml' in 'Data' folder
2. Open train.py and find:
'if __name__=='__main__':'
Change the the path for 'load_cfg' to your '.yml' file
3. Run the train.py
3.test
1. Prepare the '.yml' file at first
2. Open test.py and find:
'if __name__=='__main__':'
Change the path for 'load_cfg' to your '.yml' file
3. Run the test.py