A newer version of the Gradio SDK is available:
6.9.0
metadata
title: Color Restorization Model
emoji: 🖼️
colorFrom: indigo
colorTo: yellow
sdk: gradio
sdk_version: 3.9
app_file: app.py
pinned: true
license: unlicense
🌈 Color Restorization Model (CPU Optimized)
Bring your old black & white photos back to life—upload, adjust, and download in vivid color.
This version has been optimized for CPU inference, removing GPU dependencies and improving performance on standard hardware.
Features
- Adaptive Resolution Processing: Large images are processed intelligently to preserve sharpness while ensuring fast colorization.
- Quality Presets: Choose between Fast, Balanced, and High quality to suit your hardware.
- Real-time Progress: Visual progress bar.
- Pure CPU Stack: Optimized for Intel/AMD CPUs with AVX2 support (via PyTorch).
CPU Compatibility Matrix
| Processor Generation | Recommended Preset | 1080p Processing Time (Est.) |
|---|---|---|
| Intel Core i3 / Older | Fast (256px) | 2-5s |
| Intel Core i5 (8th Gen+) | Balanced (512px) | 1-3s |
| Intel Core i7 / Ryzen 7 | High (1080px) | 3-8s |
| M1/M2 Mac | Balanced | <1s |
Performance Tuning
- Memory Constrained (<8GB RAM): Stick to "Fast" or "Balanced".
- High-Res Archival: Use "Original" resolution only if you have >16GB RAM and patience.
- Batch Processing: The core logic is thread-safe and can be extended for batch processing.
Technical Details
The application uses the DDColor architecture via ModelScope. Optimizations include:
- L-Channel Preservation: We apply colorization at a lower resolution and merge it with the original high-resolution Luminance channel using LAB color space.
- In-Memory Pipeline: Removed disk I/O bottlenecks.
- Dynamic Quantization: Automatically applied to the model on supported CPUs.
Installation
pip install -r requirements.txt
python app.py
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference