clean-fid
generative-evaluation-prdc
| clean-fid | generative-evaluation-prdc | |
|---|---|---|
| 3 | 2 | |
| 863 | 234 | |
| - | 5.1% | |
| 2.6 | 0.0 | |
| 2 months ago | over 1 year ago | |
| Python | Python | |
| MIT License | MIT License |
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clean-fid
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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?
https://github.com/GaParmar/clean-fid/ is my goto. https://github.com/mseitzer/pytorch-fid isn't bad either.
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[D] Comparing the efficiency of different GAN models
The best repo for FID (as far as I know) is this one: https://github.com/GaParmar/clean-fid
generative-evaluation-prdc
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[D] Comparing the efficiency of different GAN models
Also you can easily add in some extra precision/recall mterics into that repo's evaluation script from this repo: https://github.com/clovaai/generative-evaluation-prdc
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[R] What are some up-to-date references to the evaluation of model fit across various types of generative models (GANs, flows, VAEs, diffusion, etc.)?
Code for https://arxiv.org/abs/2002.09797 found: https://github.com/clovaai/generative-evaluation-prdc
What are some alternatives?
pytorch-fid - Compute FID scores with PyTorch.
precision-recall-distributions - Assessing Generative Models via Precision and Recall (official repository)
SDEdit - PyTorch implementation for SDEdit: Image Synthesis and Editing with Stochastic Differential Equations
FedScale - FedScale is a scalable and extensible open-source federated learning (FL) platform.
torch-fidelity - High-fidelity performance metrics for generative models in PyTorch
image-similarity-measures - :chart_with_upwards_trend: Implementation of eight evaluation metrics to access the similarity between two images. The eight metrics are as follows: RMSE, PSNR, SSIM, ISSM, FSIM, SRE, SAM, and UIQ.
Anime2Sketch - A sketch extractor for anime/illustration.
ALAE - [CVPR2020] Adversarial Latent Autoencoders
gangealing - Official PyTorch Implementation of "GAN-Supervised Dense Visual Alignment" (CVPR 2022 Oral, Best Paper Finalist)
rexmex - A general purpose recommender metrics library for fair evaluation.
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch
SDV - Synthetic data generation for tabular data