.
.
.
99%|#############################7| 198/200 [00:05<00:00, 33.51batch/s, loss=185.71356]
Traceback (most recent call last):
File "train.py", line 154, in <module>
main()
File "train.py", line 148, in main
t.fit([lt, lv], config)
File "c:\code\videosuperresolution\VSR\Backend\TF\Framework\Trainer.py", line 352, in fit
self.fn_train_each_epoch()
File "c:\code\videosuperresolution\VSR\Backend\TF\Framework\Trainer.py", line 270, in fn_train_each_epoch
for items in r:
File "C:\Users\ccho\AppData\Local\conda\conda\envs\enntri\lib\site-packages\tqdm\std.py", line 1127, in __iter__
for obj in iterable:
File "c:\code\videosuperresolution\VSR\DataLoader\Loader.py", line 148, in __next__
pack['hr'] = np.concatenate(pack['hr'])
File "<__array_function__ internals>", line 6, in concatenate
ValueError: all the input array dimensions for the concatenation axis must match exactly, but along dimension 2, the array at index 0 has size 63 and the array at index 3 has size 18
Neural network: SRCNN and ESPCN
Dataset: Waterloo
To reproduce my error:
python train.py srcnn --dataset waterloo --pretrain="../Results/srcnn_uda/save" --epochs=1000 -cuda or
python train.py espcn --dataset waterloo --pretrain="../Results/espcn/save" --epochs=1000 --cuda
Setting: scale 9 and batch 4.
I searched Issues in the repository, but it looks like no one had this problem.
I am facing error during training. The function is
np.concatenate
.It looks like my images in the dataset need to be the same size...
File:
VSR\DataLoader\Loader.py
Code line:
pack['hr'] = np.concatenate(pack['hr'])
Here is error Message:
Neural network: SRCNN and ESPCN
Dataset: Waterloo
To reproduce my error:
python train.py srcnn --dataset waterloo --pretrain="../Results/srcnn_uda/save" --epochs=1000 -cuda
orpython train.py espcn --dataset waterloo --pretrain="../Results/espcn/save" --epochs=1000 --cuda
Setting: scale 9 and batch 4.
I searched Issues in the repository, but it looks like no one had this problem.
Do I miss anything?
Thanks.