MIRNet and MIRNet-TFJS

These are ecosystem siblings, specifically a TensorFlow implementation (A) and its corresponding TensorFlow.js models (B), allowing the same low-light image enhancement technique to be applied in different environments, such as server-side Python and client-side web browsers, respectively.

MIRNet
47
Emerging
MIRNet-TFJS
43
Emerging
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 21/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 17/25
Stars: 118
Forks: 36
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 356
Forks: 40
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About MIRNet

soumik12345/MIRNet

Tensorflow implementation of MIRNet for Low-light image enhancement

This helps photographers, videographers, and content creators improve the visual quality of their images and videos captured in poor lighting conditions. You input a dark or underexposed image, and it outputs a brighter, clearer, and more vibrant version, revealing details that were previously hidden. It's for anyone who needs to rescue underexposed visuals without reshooting.

photography video-editing image-enhancement digital-restoration content-creation

About MIRNet-TFJS

Rishit-dagli/MIRNet-TFJS

TensorFlow JS models for MIRNet for low-light💡 image enhancement

This project helps photographers, content creators, or anyone with a collection of dimly lit images to instantly brighten and clarify them. You simply provide a low-light photograph, and it outputs a significantly enhanced, clearer version. It's designed for individuals who need to improve the visual quality of their images without complex editing software.

Photography Image Enhancement Digital Imaging Content Creation Photo Editing

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