torch-fidelity
High-fidelity performance metrics for generative models in PyTorch (by toshas)
pytorch-fid
Compute FID scores with PyTorch. (by mseitzer)
torch-fidelity | pytorch-fid | |
---|---|---|
3 | 5 | |
872 | 3,080 | |
- | - | |
8.1 | 5.9 | |
3 months ago | about 2 months ago | |
Python | Python | |
GNU General Public License v3.0 or later | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
torch-fidelity
Posts with mentions or reviews of torch-fidelity.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-10.
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[D] A better way to compute the Fréchet Inception Distance (FID)
The Fréchet Inception Distance (FID) is a widespread metric to assess the quality of the distribution of a image generative model (GAN, Stable Diffusion, etc.). The metric is not trivial to implement as one needs to compute the trace of the square root of a matrix. In all PyTorch repositories I have seen that implement the FID (https://github.com/mseitzer/pytorch-fid, https://github.com/GaParmar/clean-fid, https://github.com/toshas/torch-fidelity, ...), the authors rely on SciPy's sqrtm to compute the square root of the matrix, which is unstable and slow.
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[D] Are there any good FID and KID metrics implementations existing that are compatible with pytorch?
Try torch-fidelity : https://github.com/toshas/torch-fidelity
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How to compute Inception score for 3d GAN
You can, but two ingredients are required: a rich pretrained feature extractor for your data to replace InceptionV3 pretrained on ImageNet, and https://github.com/toshas/torch-fidelity, which can be used with custom feature extractors (also supports FID and KID).
pytorch-fid
Posts with mentions or reviews of pytorch-fid.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-10.
-
[D] A better way to compute the Fréchet Inception Distance (FID)
The Fréchet Inception Distance (FID) is a widespread metric to assess the quality of the distribution of a image generative model (GAN, Stable Diffusion, etc.). The metric is not trivial to implement as one needs to compute the trace of the square root of a matrix. In all PyTorch repositories I have seen that implement the FID (https://github.com/mseitzer/pytorch-fid, https://github.com/GaParmar/clean-fid, https://github.com/toshas/torch-fidelity, ...), the authors rely on SciPy's sqrtm to compute the square root of the matrix, which is unstable and slow.
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[D] Are there any good FID and KID metrics implementations existing that are compatible with pytorch?
https://github.com/GaParmar/clean-fid/ is my goto. https://github.com/mseitzer/pytorch-fid isn't bad either.
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[P] Frechet Inception Distance
https://github.com/mseitzer/pytorch-fid for example this here. The code is quite clean and clear
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SSIM (Structural Similarity Index Metric )
Didn't get your problem statement but you can also consider FFID score to measure the similarity between two images. Check out: https://github.com/mseitzer/pytorch-fid
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[R] Maximum likelihood estimation can fail due to "Manifold Overfitting"
Author here, thanks for the comment! The example in 3.1 is not meant as a realistic example, it is meant as an intuitive explanation of how the manifold overfitting issue can arise. As for FID scores, we intend on releasing our code soon, but we used the standard PyTorch implementation (https://github.com/mseitzer/pytorch-fid).
What are some alternatives?
When comparing torch-fidelity and pytorch-fid you can also consider the following projects:
evaluate - 🤗 Evaluate: A library for easily evaluating machine learning models and datasets.
clean-fid - PyTorch - FID calculation with proper image resizing and quantization steps [CVPR 2022]
rexmex - A general purpose recommender metrics library for fair evaluation.
TryOnGAN - TryOnGAN: Unofficial Implementation
mugl
avalanche - Avalanche: an End-to-End Library for Continual Learning based on PyTorch.
stylegan2-ada-pytorch - StyleGAN2-ADA - Official PyTorch implementation
trajectopy-core - Trajectopy - Trajectory Evaluation in Python
ALAE - [CVPR2020] Adversarial Latent Autoencoders
trajectopy - Trajectopy - Trajectory Evaluation in Python
DE-GAN - Document Image Enhancement with GANs - TPAMI journal
torch-fidelity vs evaluate
pytorch-fid vs clean-fid
torch-fidelity vs rexmex
pytorch-fid vs TryOnGAN
torch-fidelity vs clean-fid
pytorch-fid vs mugl
torch-fidelity vs avalanche
pytorch-fid vs stylegan2-ada-pytorch
torch-fidelity vs trajectopy-core
pytorch-fid vs ALAE
torch-fidelity vs trajectopy
pytorch-fid vs DE-GAN