Comments (4)
Hi @qicathetine
The results during the validation and test phases should be the same. Try to test the provided pre-trained models to make sure that your test code is correct, or please provide more details about your issue if you need further help.
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Hi@aiff22, I think the idea you provided to me is correct that the results during the validation and test phases should be consistent. Therefore, I think there is a problem with my test code. So, I would like to ask you a question. How was the image tested in the network during the test phase? Whether it is the entire picture or the divided image blocks just like the way of the training phase. Finally get the final results of combining them. Thank you!
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Hi @qicathetine
The entire image is passed to a neural network during the test phase. Please have a look at our test code provided within this repository that contains all necessary steps for producing the final visual results: https://github.com/aiff22/DPED/blob/master/test_model.py
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Hi@aiff22
Thank your reply, I got where the problem is.
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Related Issues (20)
- Quite slow on my mac machine for given models. HOT 1
- I want to test this pretrained model on single image how can I do it HOT 2
- Unable to download the pre-trained VGG -19 Model HOT 1
- I want to change the network to single channel HOT 1
- Why "enhanced = tf.nn.tanh(conv2d(c11, W12) + b12) * 0.58 + 0.5"? HOT 1
- Do you have the file of '.meta'? HOT 1
- Resume learning HOT 1
- too slow when training (not using GPU)
- issue about preprocessing code
- collecting data HOT 1
- 感觉不如opencv一行代码提升效果明显 HOT 1
- Comparison with APE that is source-ignorant? HOT 1
- Download links no longer works
- discrim_predicitions
- A brilliant idea!
- Data set Download links no works HOT 3
- Not Good Result after training HOT 1
- can you upload how to generate Dataset scriptes? HOT 1
- Need RAW-RGB alignment code for custom dataset creation and training
- Cannot download DPED pre-trained model
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