About the implementation

[wl082013]

HI, Yunsheng, nice work.
I was kind of confused when I was reading the paper.
I understood the 'bi-directional' as simultaneous forward and backward pass', however when I check the code, I found it is not simultaneous training.

If I am correct, the training step might be:
(1) train CycleGAN to get translated images
(2) train BDL.py to get segmentation model with the translated images and source images,
(3) train SSL.py to get pseudo-labels and refine the segmentation model.
(4) retrain CycleGAN with an additional perceptual loss.

Then what's the next step? Step (1) tries to get better-translated images with the model of step (4)?
And then repeat (2)-(3). Does that mean this needs to be done multiple times based on the number of steps we want to try?
I am kind of confused about it since I thought 'bi-directional' was for simultaneous training of Im2Im translation and segmentation.

Moreover, the CycleGAN folder is not complete. Some libraries are missing :
from util.image_pool import ImagePool
from .base_model import BaseModel
from fcn8s_LSD import FCN8s_LSD #lys
For the last one, fcn8s_LSD is the model from step (4)?

thanks for your help.

[liyunsheng13]

step (1) -> (4) can be iterated. You can just ignore from fcn8s_LSD import FCN8s_LSD, it is only for VGG net.