AmrShaaban99/super-resolution
This project shows Image Super Resolution using Deep Learning . Seven models are implemented SRCNN, FSRCNN,ESPCN, RDN, RFDN, Autoencoder and ESRGAN.
This project helps you enhance the resolution of low-quality images, turning blurry or pixelated photos into clearer, more detailed versions. You input a low-resolution image, and it outputs a high-resolution version. This tool is designed for anyone needing to improve image quality, such as photographers, graphic designers, or medical imaging specialists.
No commits in the last 6 months.
Use this if you need to upscale existing images without losing significant detail, making them suitable for printing, presentations, or detailed analysis.
Not ideal if you require real-time image enhancement for video streams or if your primary need is for specialized image restoration beyond simple upscaling.
Stars
32
Forks
8
Language
Jupyter Notebook
License
—
Category
Last pushed
May 21, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/AmrShaaban99/super-resolution"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
HasnainRaz/Fast-SRGAN
A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps
NatLabRockies/sup3r
The Super-Resolution for Renewable Resource Data (sup3r) software uses generative adversarial...
the-database/traiNNer-redux
Deep learning training framework for image super resolution and restoration.
eugenesiow/super-image
Image super resolution models for PyTorch.
movehand/raisr
A Python implementation of RAISR