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A few minor issues #3
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@WhiteSigility Thanks for all your works! First of all, I am very glad about there is someone really tried my code. About the inference results, we aligned the training dataset with the landmarks extracted from 3DDFA_v2. If you used other landmark extractors, it will affect the inference quality.
Can you tell me more details about this error? |
Sure - here's the error in detail:
In this case, one target image was 954x954 px and the other was 579x929 px. I should also mention that I'm evaluating your code in Anaconda, haven't installed Docker or set up for training. I'm using Python v3.7. It's certainly possible this issue is unique to my setup! |
@WhiteSigility The input image size should be a right rectangle. You should pre-process with 3DDFA_v2's landmarks, just like FFHQ did. |
I have the same issue with @WhiteSigility. Things I have tried:
I wonder if any specific image size requirement for the inferencing task? |
I got "ModuleNotFoundError: No module named 'lpips'" error when running the inference.py, and even if I git cloned the lpips repo in /hififace/model, it didn't work. would you please tell how to solve this problem? |
First, thanks for taking the time to implement this faceswapping model - seems like it has a lot of potential!
That said, I noticed a few issues while setting it up on my machine:
While I am able to produce images with hififace_inference, I must say that the resulting faces look quite strange and lack the visual fidelity shown in the examples. Is this because my images have not been properly aligned? And if so, is there a way to automate the alignment script and prepend it to the inference execution?
On a similar note, the inference seems to crash when target images have different dimensions. Is this a known limitation?
Thank you again for your hard work!
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