Auto Colorization of Gray Scale Image using CNN

Overview

This project implements automatic colorization of grayscale images using Convolutional Neural Networks (CNN). The repository includes both basic auto-colorization and an advanced Ethnicity Aware Autocolorization system that considers ethnic characteristics for more accurate and culturally sensitive colorization.

Complete Walkaround is covered in this blog: Auto-Colorization of Grayscale Images using CNN

Tools Used

• Python 3
• Keras
• Numpy
• Tensorflow

Features

• Standard Auto-Colorization: Basic CNN-based colorization for general grayscale images
• Ethnicity Aware Auto-Colorization: Advanced pipeline that detects and considers ethnic characteristics for improved colorization accuracy
• Pre-trained models for immediate use
• Comprehensive testing and evaluation

Repository Structure

• Dataset: Training and testing datasets
• Screenshots: Result demonstrations
• result: Output colorized images
• Ethnicity Aware Autocolorization: Advanced ethnic-aware implementation with specialized notebooks and models
• Auto_color.ipynb: Main colorization notebook
• model.h5: Pre-trained model
• model.json: Model architecture

Dataset

Dataset is included in the folder named Dataset.

Ethnicity Aware Autocolorization

The Ethnicity Aware Autocolorization folder contains an advanced implementation that:

• Detects ethnic characteristics in facial images
• Applies culturally appropriate colorization
• Includes specialized models and testing notebooks
• Features comprehensive evaluation using LPIPS metrics
• Contains multiple test datasets for different ethnic groups

Key files in this folder:

• Colorization Final.ipynb: Main colorization pipeline
• Ethnic Detection Final.ipynb: Ethnicity detection system
• Final Testing Both Pipeline.ipynb: Combined testing pipeline
• Colorize.h5 and ColorizeTuned.h5: Pre-trained models

Screenshot of Result

Left Column includes the input images and the right column includes the automatically colorized images using CNN.

Getting Started

1. Clone the repository
2. Install required dependencies: pip install tensorflow keras numpy
3. Run Auto_color.ipynb for basic colorization
4. Explore the Ethnicity Aware Autocolorization folder for advanced features

Usage

For basic colorization:

jupyter notebook Auto_color.ipynb

For ethnicity-aware colorization:

cd "Ethnicity Aware Autocolorization"
jupyter notebook "Final Testing Both Pipeline.ipynb"