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MaybeShewill-CV / attentive-gan-derainnet

Unofficial tensorflow implemention of "Attentive Generative Adversarial Network for Raindrop Removal from A Single Image (CVPR 2018) " model https://maybeshewill-cv.github.io/attentive-gan-derainnet/
MIT License
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How to achieve a better result of deraining? #5

Closed zhaojianghe16 closed 5 years ago

zhaojianghe16 commented 5 years ago

Dear Friend, I ran the test_model.py with the test_1.jpg, test_2.png and test_3.png (directory: \attentive-gan-derainnet-master\data\test_data). However, it seemed the model could not get rid of the raindrops as well as the photo pairs(with raindrops, and after deraining) illustrated in the readme. May I ask what is your future plan? Or could you give me some instructions for continuing to train the model? I am very curious about your answer. Thank you so much!

MaybeShewill-CV commented 5 years ago

@zhaojianghe16 You may not pull the newest code. The test data now is test_1.png, test_2.png and test_3.png. You may test them.

MaybeShewill-CV commented 5 years ago

@zhaojianghe16 You can also test the model on the origin dataset supplied by the origin author

zhaojianghe16 commented 5 years ago

Hi. Thank you for your quick response. Did you mean "You may now pull the newest code." instead of "not"? I am not sure what you meant. Thanks.

MaybeShewill-CV commented 5 years ago

@zhaojianghe16 Yep you can update the repo and test the model on the data/test_data/*.png. If there is something wrong you can put the result here:)