Manga Light Colorizer — ONNX Inference

Standalone inference script for the Manga Light Colorizer model.

Gallery

The following gallery uses the same source images as the manga-colorization-v2 project to facilitate direct comparison between models.

Comparison between input (left) and colorized output (right):

Quick Start

# Install dependencies
pip install -r requirements.txt

# Single image
python inference.py --input input/bw1.jpg

# All images in a folder
python inference.py --input input/

# Custom output folder
python inference.py --input input/ --output_dir output/

# Custom inference resolution
python inference.py --input input/ --infer-size 1024

Arguments

Model Information

• Architecture: FastViT-SA36 Encoder + DualSemanticSAM Guide + UNet V6 Decoder
• Training Resolution: 512×512 pixels
• Current Inference Resolution: 768×768 pixels (default)
• Output: Resized back to original input resolution

Important: Resolution Notice

The model was trained at 512×512 pixels. Inference currently runs at 768×768 pixels by default.

More the inference resolution differs from 512×512, the less faithful the colors will be.

For best results, use the training resolution:

# Best color accuracy, but lower resolution — matches training resolution
python inference.py --input input/ --infer-size 512

# Default (good quality)
python inference.py --input input/

# Higher resolution (may reduce color accuracy)
python inference.py --input input/ --infer-size 1024

Pipeline

Input (grayscale) → Resize to infer-size → SAM 2.1 (zeros) → Generator ONNX → Resize to original

Requirements

• Python 3.10+
• onnxruntime
• numpy
• opencv-python

See requirements.txt for full list.

License

Model Weights

Licensed under CC BY-NC-SA 4.0 (Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International).

You may:

• Share — copy and redistribute the material in any medium or format
• Adapt — remix, transform, and build upon the material

Under the following terms:

• Attribution — You must give appropriate credit
• NonCommercial — You may not use the material for commercial purposes
• ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license

See: https://creativecommons.org/licenses/by-nc-sa/4.0/

Inference Code

Licensed under GNU General Public License v3 (GPL-3.0).

You may use, modify, and distribute this code under the terms of the GPL-3.0 license.

See: https://www.gnu.org/licenses/gpl-3.0.html