Abdelrahman (Ogail) Elogeel

Results 16 comments of Abdelrahman (Ogail) Elogeel

- I think you mean line 189 which is: net.load(args.restore_from, sess) I tried and it results in loss being ‘nan’ - i also tried to load from a saved checkpoint...

The dataset has 2 class obstacles (0) and non-obstacles (255) in a binary format. Here is an example of raw image ![img_00002](https://user-images.githubusercontent.com/1034045/37069171-0c7ead28-2167-11e8-95a0-aa560967539d.jpg) This is an example of label image (similar...

@hellochick I finally got it working, here are steps I did: - commenting `net.load` line - Setting number of classes to 2 - Setting IGNORE_LABEL to arbitrary number not 0...

@bhadresh74 is there a specific question you have?

@bhadresh74 Here are some suggestions: 1- getting loss to `0.6` is good indication, pushing it more will require some tinkering like: - increasing number of training steps - increasing batch...

@BCJuan excuse me for late reply. Yes I did both changes as well.

@BCJuan did fine-tuning from pretrained model boosted on your custom task? Have u tried to compare that vs training from scratch?

@BCJuan what's `mIoU` before and after using cityecapes pretrained model?

@BCJuan I did load the pretrained model however didn't see much diff between fine-tuning vs training from scratch.