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@@ -11,7 +11,7 @@
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Real-ESRGAN aims at developing **Practical Algorithms for General Image Restoration**.<br>
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We extend the powerful ESRGAN to a practical restoration application (namely, Real-ESRGAN), which is trained with pure synthetic data.
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-:triangular_flag_on_post: The training codes have been released. A detailed guide will be provided later (on July 25th). Note that the codes have a lot of refactoring from our developed codes. So there may be some bugs/performance drops. Welcome to report issues and I wil also retrain the models.
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+:triangular_flag_on_post: The training codes have been released. A detailed guide will be provided later (on July 25th). Note that the codes have a lot of refactoring. So there may be some bugs/performance drops. Welcome to report issues and I wil also retrain the models.
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### :book: Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data
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@@ -36,11 +36,11 @@ in my spare time.
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Here is a TODO list in the near future:
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-[ ] optimize for human faces
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-[ ] optimize for texts
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-[ ] optimize for animation images
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-[ ] support more scales
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-[ ] support controllable restoration strength
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+- [ ] optimize for human faces
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+- [ ] optimize for texts
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+- [ ] optimize for animation images
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+- [ ] support more scales
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+- [ ] support controllable restoration strength
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If you have any good ideas or demands, please open an issue/discussion to let me know. <br>
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If you have some images that Real-ESRGAN could not well restored, please also open an issue/discussion. I will record it (but I cannot guarantee to resolve it:stuck_out_tongue:). If necessary, I will open a page to specially record these real-world cases that need to be solved, but the current technology is difficult to handle well.
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Xintao