inference result with model trained with train.py is not good and model size is almost twise bigger then pretrained model
kiitosu opened this issue · 3 comments
I tried to train PSPNet101 with cityscapes dataset.
I did below.
・download dataset
・edit cityscapes_trail_list.txt gtFine_labelTrainIds.png to gtFine_labeIds.png
・edit train.py DATA_DIRECTORY to suit my image data
・change batch size 2 to 1
・python train.py
After 15hours I finished the training .
Inference with inference.py is so poor.
Traind data I created is
File size of model.ckpt-60000.data-00000-of-00001 is about 502M byte.
File size of model.ckpt-60000.meta is about 2.7M byte.
Pretraind data is
File size of model.ckpt-0.data-00000-of-00001 size is 254M .
File size of model.ckpt-0.meta size is 254M .
I think the problem is the model trained is not proper because of the model.ckpt-60000.data-00000-of-00001 size is twice bigger than pretrained file model.ckpt-0.data-00000-of-00001.
Or the problem is model.ckpt-60000.meta size is too small compared wit pretrained file model.ckpt-0.meta size is 254M.
How could I solve this problem?
My problem is same with you. Have you solve the issue?
I'm sorry. No I haven't.