Train assumptions

[michacohen]

Hi
I tried to train aug over pascal_voc data set unsuccessfully, h5 files has been generated (both original and subpixel) however it not predict anything

These are my assumptions/my understanding, any comments are welcome

1. backbone to chose between 'mobilenetv2' or 'xception'

2. better_model to chose between original or subpixel

3. weights = is the pretrain model to load as base, 'pascal_voc' or None

4. load_weights in case I want to load weight during create_seg_model - on training should be False

5. Data:
   under PEGImages\train need to have the jpg you want to train
   under SegmentationClassAug you should have the mask on png format ,2D with the number of class on each pixel (see attached as example)
   both PEGImages\train and SegmentationClassAug must have the same pairs for example 2007_000032.png and 2007_000032.jpg

Still h5 files are not good

Any Idea? Do I miss something?

6.

[Mps24-7uk]

@michacohen JPEGImages folder has 17125 images and SegmentationClassAug 12301 masks. So before the training, keep only those images having mask pairs. Download the SegmentationClassAug folder from https://www.dropbox.com/s/oeu149j8qtbs1x0/SegmentationClassAug.zip