neka-nat image_completion_tf2 issues

neka-nat / image_completion_tf2

"Globally and Locally Consistent Image Completion" with Tensorflow2 Keras

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train.py

#21 yuting666888 opened 3 years ago
0
test.py

#20 Yaizzz opened 3 years ago
0
ValueError: Layer sequential expects 1 inputs, but it received 2 input tensors.

#19 Sophietje1p closed 3 years ago
0
Test.py

#18 mpsunmikim opened 3 years ago
2
I cant load G-discriminator

#17 predestined-will opened 3 years ago
7
Why d_container.trainable is set to False in the train.py?

#16 zhengzibing2011 closed 4 years ago
3
data preprocess

#15 LexieYang opened 4 years ago
2
question

#14 barrylee9527 closed 4 years ago
1
Set "d_container.trainable = True" after training all_model

#13 bis-carbon closed 5 years ago
4
error on Keras 2.2.2 merge

#12 ldenoue closed 5 years ago
4
does this code deal with random mask?

#11 micklexqg closed 5 years ago
2
Test different size of images

#10 zhangqingbo1 opened 6 years ago
0
A keras question about bulid network

#9 xieenze closed 5 years ago
2
predict the test pic

#8 Alex-toto opened 6 years ago
4
I didn't see obvious differents in the results with or without the local and global D.

#7 dongdong092 closed 5 years ago
1
Computer available memory is reduced from 14G to 100M until the program is killed

#6 zhangqingbo1 closed 6 years ago
3
The results seems not good.

#5 dongdong092 opened 6 years ago
15
Can't training the model on GPU

#4 generallc closed 6 years ago
3
which branch should I choose?

#3 xieenze closed 6 years ago
2
Using the joint loss gradient

#2 neka-nat closed 6 years ago
0
where did you use the joint loss?

#1 micklexqg closed 6 years ago
6