3 Stage training
Train in parallel gt, sl, occ
- implement saving and loading of individual unet decoder branches
- When using SSIM for loss: 1 - SSIM_value (to avoid negative loss, because we want to maximise SSIM)
- implement losses
- GT:
- MSE(gt_original,
gt_prediction)
- SL:
- MAE(light_generated,
light_prediction)
- MAE(shadow_generated,
shadow_prediction)
- OCC:
- 1 - SSIM(gt_original * shadow_generated + light_generated XOR
occ_predicted, input_image)
- prepare configs
3 Stage training
Train in parallel gt, sl, occ
gt_prediction)light_prediction)shadow_prediction)occ_predicted, input_image)