Hi, thank you for your work!
I am attempting to train the BIDNet and would greatly appreciate your assistance with the following questions:
The SN6 SAR imagery consists of 4-channel, 32-bit data. How did you convert this to 8-bit?
Am I correct in understanding that to train the teacher model, I should use train.py with RGB_res18_train_teacher.yaml, and for training the student model, I should use train_dist.py with SAR_res18_train_distill.yaml?
What exactly is the dist_cfg variable in SAR_res18_train_distill.yaml, and how can I generate the data for it?
you can take a normalization operator for conversion
yes
it refers to the distillation layer and the path of the pre-results generated by the RGB network. You can first infer the RGN images with the teacher model. Then train the student model with the RGB edge map and so on.
Hi, thank you for your work! I am attempting to train the BIDNet and would greatly appreciate your assistance with the following questions:
train.py
withRGB_res18_train_teacher.yaml
, and for training the student model, I should usetrain_dist.py
withSAR_res18_train_distill.yaml
?dist_cfg
variable inSAR_res18_train_distill.yaml
, and how can I generate the data for it?Thank you for your answer.