https://github.com/ai-forever/movqgan

MoVQGAN - model for the image encoding and reconstruction

https://github.com/ai-forever/movqgan

Science Score: 10.0%

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    Links to: arxiv.org
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Keywords

gan generative-adversarial-network image-compression image-encoding image-reconstruction
Last synced: 6 months ago · JSON representation

Repository

MoVQGAN - model for the image encoding and reconstruction

Basic Info
  • Host: GitHub
  • Owner: ai-forever
  • Language: Jupyter Notebook
  • Default Branch: main
  • Homepage:
  • Size: 27.5 MB
Statistics
  • Stars: 233
  • Watchers: 4
  • Forks: 16
  • Open Issues: 10
  • Releases: 0
Topics
gan generative-adversarial-network image-compression image-encoding image-reconstruction
Created almost 3 years ago · Last pushed over 2 years ago
Metadata Files
Readme

README.md

SBER-MoVQGAN

Framework: PyTorch Huggingface space Open In Colab

Habr post

SBER-MoVQGAN (Modulated Vector Quantized GAN) is a new SOTA model in the image reconstruction problem. This model is based on code from the VQGAN repository and modifications from the original MoVQGAN paper. The architecture of SBER-MoVQGAN is shown below in the figure.

SBER-MoVQGAN was successfully implemented in Kandinsky 2.1, and became one of the architecture blocks that allowed to significantly improve the quality of image generation from text.

Models

The following table shows a comparison of the models on the Imagenet dataset in terms of FID, SSIM, and PSNR metrics. A more detailed description of the experiments and a comparison with other models can be found in the Habr post.

|Model|Latent size|Num Z|Train steps|FID|SSIM|PSNR|L1| |:----|:----|:----|:----|:----|:----|:----|:----| |ViT-VQGAN*|32x32|8192|500000|1,28|-|-|-| |RQ-VAE*|8x8x16|16384|10 epochs|1,83|-|-|-| |Mo-VQGAN*|16x16x4|1024|40 epochs|1,12|0,673|22,42|-| | VQ CompVis| 32x32| 16384 | 971043| 1,34| 0,65| 23,847| 0,053| | KL CompVis| 32x32| - | 246803| 0,968| 0,692| 25,112| 0,047| | SBER-VQGAN (from pretrain)| 32x32| 8192| 1 epoch| 1,439| 0,682| 24,314| 0,05| | SBER-MoVQGAN 67M | 32x32 | 16384 | 2M | 0,965| 0,725| 26,449| 0,042 | SBER-MoVQGAN 102M|32x32|16384|2360k|0,776|0,737 | 26,889| 0,04| |SBER-MoVQGAN 270M|32x32|16384|1330k| 0,686💥| 0,741💥| 27,037💥| 0,039💥|

How to use

Install

pip install "git+https://github.com/ai-forever/MoVQGAN.git"

Train

python main.py --config configs/movqgan_270M.yaml

Inference

Check jupyter notebook with example in ./notebooks folder or Open In Colab

Examples

This section provides examples of image reconstruction for all versions of SBER-MoVQGAN on hard-to-recover domains such as faces, text, and other complex scenes.

Authors

Owner

  • Name: AI Forever
  • Login: ai-forever
  • Kind: organization
  • Location: Armenia

Creating ML for the future. AI projects you already know. We are non-profit organization with members from all over the world.

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