Anime2Sketch
clean-fid
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| Anime2Sketch | clean-fid | |
|---|---|---|
| 7 | 3 | |
| 1,811 | 726 | |
| - | - | |
| 0.0 | 5.2 | |
| about 2 months ago | 20 days ago | |
| Python | Python | |
| MIT License | MIT License |
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Anime2Sketch
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?
pytorch-fid - Compute FID scores with PyTorch.
U-2-Net - The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."
UGATIT - Official Tensorflow implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation (ICLR 2020)
GANime - A deep learning program that automatically generates colorized anime characters based on sketch drawings.
SDEdit - PyTorch implementation for SDEdit: Image Synthesis and Editing with Stochastic Differential Equations
anime-face-detector - Anime Face Detector using mmdet and mmpose
pytorch-pretrained-BigGAN - 🦋A PyTorch implementation of BigGAN with pretrained weights and conversion scripts.
StyleSwin - [CVPR 2022] StyleSwin: Transformer-based GAN for High-resolution Image Generation
generative-evaluation-prdc - Code base for the precision, recall, density, and coverage metrics for generative models. ICML 2020.
PromptGallery-stable-diffusion-webui - A prompt cookbook worked as stable-diffusion-webui extenstions.
torch-fidelity - High-fidelity performance metrics for generative models in PyTorch
vision-aided-gan - Ensembling Off-the-shelf Models for GAN Training (CVPR 2022 Oral)