Forked from U-Net in PyTorch, this implantation is used for mixture signal separation and classification
Note : Use Python 3
To predict and classify a batch of mixture signals
python predict.py --model MODEL.pth
You can specify which model file to use with --model MODEL.pth
.
To visualize the separated component signals, please run visualization.ipynb
> python train.py -h
usage: train.py [-h] [-e E] [-b [B]] [-l [LR]] [-f LOAD]
Train the UNet on
optional arguments:
-h, --help show this help message and exit
-e E, --epochs E Number of epochs (default: 5)
-b [B], --batch-size [B]
Batch size (default: 1)
-l [LR], --learning-rate [LR]
Learning rate (default: 0.1)
-f LOAD, --load LOAD Load model from a .pth file (default: False)
Original paper by Olaf Ronneberger, Philipp Fischer, Thomas Brox: https://arxiv.org/abs/1505.04597