Comments (1)
csxmli2016
commented on June 22, 2024
Just out of curiosity, is it possible to skip the face detection stage when running DFDNet? Would it crash or just keep working? I love experimenting and I'm curious how the result would look like since I'm looking for a tool that would help me enhance hair in photos where subjects have long hairs. So far I tested a lot of solutions such as DFDNet, Remini, and other apps and scripts of this type and they only enhance hairs around faces, leaving the rest of the hair looking like the subject put a load of glue on their head
Hi, DFDNet is proposed to handle face regions. So it is a must to detect face. As for hair, I think you can extract them, and use irregular region fair discriminator or style constrains to enhance them.
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Related Issues (20)
- Training HOT 2
- Can the cropped area of the face be larger? Long-haired ones are not fully displayed HOT 1
- Cuda alocating too much on 4gb card, come on, gpen does it fine. 1024 models ?
- Pasting upscaled face back to original image is offset/wrong size
- Can someone set it up for huggingface or replicate websites to run ?
- Got it working, but won't work the second time
- CUDA running out of memory (3gb card) on the face restoration step
- all faces enhance along with background
- the face channel or some step went wrong? HOT 1
- No output
- onnx export
- Biased Custom Training
- somebody can help me HOT 1
- Multiple gpus?
- VGGFace loss details.
- Discriminator architecture
- Weird results on side face input
- weird results, what's wrong.
- weird results, what's wrong? HOT 2
- Which file to edit in order to use cpu when using it as mve plugin?
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