- Python 3
- PIL (pillow)
- NumPy (numpy)
- Matplotlib (matplotlib)
- CV2 (opencv-python)
- torch
- CV2 (opencv-python)
*generated images with inverted colors and black contour
generate folding dataset:
python gen_pix2pix_dataset.py
move unfolding dataset into pix2pix folder
mv unfolding_1000_fc_3_af_0p2 pytorch-CycleGAN-and-pix2pix/datasets/unfolding_1000_fc_3_af_0p2/
start model training:
cd pytorch-CycleGAN-and-pix2pix
python train.py --dataroot ./datasets/unfolding_1000_fc_3_af_0p2 --name pix2pix_unfolding_1000_fc_3_af_0p2 --model pix2pix --direction BtoA
python train.py --dataroot ./datasets/unfolding_1000_fc_3_af_0p2 --name cycle_gan_unfolding_1000_fc_3_af_0p2 --model cycle_gan
eval on real img data:
python test_on_real_imgs.py --dataroot ./datasets/unfolding_1000_fc_3_af_0p2 --name pix2pix_unfolding_1000_fc_3_af_0p2 --model pix2pix
python test_on_real_imgs.py --dataroot ./datasets/unfolding_1000_fc_3_af_0p2 --name cycle_gan_unfolding_1000_fc_3_af_0p2 --model cycle_gan