SDEdit
clean-fid
| SDEdit | clean-fid | |
|---|---|---|
| 1 | 3 | |
| 848 | 863 | |
| 0.0% | - | |
| 0.0 | 2.6 | |
| about 1 year ago | 2 months ago | |
| Python | Python | |
| MIT License | MIT License |
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SDEdit
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
What are some alternatives?
DeepSIM - Official PyTorch implementation of the paper: "DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample" (ICCV 2021 Oral)
pytorch-fid - Compute FID scores with PyTorch.
data-efficient-gans - [NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
torch-fidelity - High-fidelity performance metrics for generative models in PyTorch
sketchedit - SketchEdit: Mask-Free Local Image Manipulation with Partial Sketches, CVPR2022
Anime2Sketch - A sketch extractor for anime/illustration.
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch
gangealing - Official PyTorch Implementation of "GAN-Supervised Dense Visual Alignment" (CVPR 2022 Oral, Best Paper Finalist)
Text2LIVE - Official Pytorch Implementation for "Text2LIVE: Text-Driven Layered Image and Video Editing" (ECCV 2022 Oral)
generative-evaluation-prdc - Code base for the precision, recall, density, and coverage metrics for generative models. ICML 2020.
OASIS - Official implementation of the paper "You Only Need Adversarial Supervision for Semantic Image Synthesis" (ICLR 2021)