Comments (4)
drboog
commented on August 16, 2024
Hi, please check this link google drive.
PS: In evaluation, we follow TediGAN, which computes metrics with 6000 generated images whose text input are randomly sampled from testing set of MM-CelebA-HQ.
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justinpinkney
commented on August 16, 2024
Thank you, exactly what I was looking for!
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YeolJ00
commented on August 16, 2024
@drboog Hi, I tried inferencing with the checkpoints you provided and somehow I mostly get male images even in cases where the text description points to female (e.g., "She is wearing lipstick").
So the FID-30k (which should be lower than the 6k version) goes up to about 54 despite the high quality images.
Is this a known issue? or do I need another checkpoint?
Thanks in advance!
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YeolJ00
commented on August 16, 2024
Oops, it was a simple inference issue. My apologies
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Related Issues (20)
- Understanding Multi-Line Text input for training and testing model HOT 1
- Some questions about the experimental setting HOT 1
- Data set download HOT 1
- The questions about parameters img_img_c and img_img_d HOT 1
- Questions on the class Model and Gaussian noise in loss.py, and data preprocessing HOT 4
- evaluate issue HOT 2
- A Question on the Temperature in the Contrastive Loss HOT 3
- any plans for the Lafite2? HOT 1
- Question about FID-k HOT 3
- A Question on Injecting Text Condition into Each Generator Layer. HOT 2
- Pre-trained Model on CUB dataset HOT 2
- Tune hyperparameters HOT 1
- Pretrained checkpoints for MM-CelebA-HQ HOT 1
- Question about finetuning hyperparams for mscoco HOT 3
- About generated results HOT 2
- Custom Dataset training HOT 8
- training time
- resume pretrained model problem HOT 1
- data preprocess
- weights link is not working
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