Original Repository: here
Example usage in train.sh
and predict.sh
prerequisite: conda https://docs.anaconda.com/free/anaconda/install/linux/
use environment.yml
conda env create -f environment.yml
manually
conda create --name pt110 python=3.9 numpy
conda activate pt110
pip install torch==1.10.1+cu111 torchvision==0.11.2+cu111 torchaudio==0.10.1 -f https://download.pytorch.org/whl/cu111/torch_stable.html
pip install matplotlib
pip install h5py
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt -f https://download.pytorch.org/whl/cu111/torch_stable.html
h5dump-shared -n data/g4-rec-r9.h5
./scripts/h5plot.py data/g4-rec-r9.h5 /100/frame_loose_lf0
./scripts/h5plot.py data/g4-rec-r9.h5 /100/frame_mp3_roi0
./scripts/h5plot.py data/g4-rec-r9.h5 /100/frame_mp2_roi0
./scripts/h5plot.py data/g4-tru-r9.h5 /103/frame_ductor0
./scripts/h5plot.py data/g4-rec-r9.h5 /103/frame_gauss0
./train3.sh
python plot_epoch.py 1
./to-ts.py -m test0/CP49.pth