Nikolai10/PerCo
PyTorch implementation of PerCo (Towards Image Compression with Perfect Realism at Ultra-Low Bitrates, ICLR 2024)
This project helps anyone working with digital images to drastically reduce file sizes while maintaining a high degree of visual quality. You input an image and get back a much smaller image file that still looks realistic, even at ultra-low bitrates. This is ideal for content creators, web developers, or anyone needing efficient image storage and transmission.
103 stars. No commits in the last 6 months.
Use this if you need to compress images to extremely small file sizes, particularly for web delivery or storage, while prioritizing the perceptual quality and realism over perfect pixel-for-pixel accuracy.
Not ideal if your application requires mathematically perfect image fidelity or if you need to compress images without any risk of introducing subtle creative changes.
Stars
103
Forks
6
Language
Python
License
Apache-2.0
Category
Last pushed
Jan 13, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/Nikolai10/PerCo"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
UCSC-VLAA/story-iter
[ICLR 2026] A Training-free Iterative Framework for Long Story Visualization
PaddlePaddle/PaddleMIX
Paddle Multimodal Integration and eXploration, supporting mainstream multi-modal tasks,...
keivalya/mini-vla
a minimal, beginner-friendly VLA to show how robot policies can fuse images, text, and states to...
adobe-research/custom-diffusion
Custom Diffusion: Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023)
byliutao/1Prompt1Story
🔥ICLR 2025 (Spotlight) One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation...