Comments (4)
I have the same issue. Now I save and load [0,1] range raw data instead of images for the evaluation, and numbers make sense to me.
from pytorch-fid.
This should not be the case because generated images are often quantized to uint8 before computing the FID score.
(because real images are not real values).
The different in FID might be cause due to JPEG compression.
The table 4 and figure 2 in this paper might be relevant to this issue.
( https://arxiv.org/pdf/2104.11222.pdf )
from pytorch-fid.
I have the same issue. Now I save and load [0,1] range raw data instead of images for the evaluation, and numbers make sense to me.
As saving it to be image format is not okay, how to save it to be [0, 1] range raw data, something like .npz?
from pytorch-fid.
Thank you for the solution.
Here is the reference architecture of the InceptionV3 model
from pytorch-fid.
Related Issues (20)
- Imaginary component 3.1913775165377e+114 HOT 4
- How to calculate fid score with label HOT 1
- Can I implement the code with video data? HOT 1
- ValueError: Imaginary component 4.082076360939105e+125 HOT 12
- Batch-size Error HOT 5
- FID is a negative value HOT 2
- ValueError: batch_size should be a positive integer value, but got batch_size=0 HOT 8
- Invalid path error HELP PLS
- CUDNN_STATUS_NOT_SUPPORTED
- transforms: ToTensor(), Normalization HOT 1
- python: symbol lookup error: /home/xxx/miniconda3/envs/torch/lib/python3.7/site-packages/mk│ l/../../../libmkl_intel_thread.so.1: undefined symbol: __kmpc_global_thread_num HOT 1
- RuntimeError: unexpected EOF, expected 877244 more bytes. The file might be corrupted. HOT 3
- Query: WGAN-GP FID SCORE (PyTorch) HOT 1
- No module named pytorch_fid
- RuntimeError: cuDNN error: CUDNN_STATUS_NOT_INITIALIZED HOT 1
- batch_size error HOT 7
- A better way to compute the FID
- Faster computation for FID
- Dataset sizes
- Error while loading weights from url HOT 1
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from pytorch-fid.