Gray2Color: Colorization of Grayscale Images

This repository showcases a neural network model designed to convert grayscale images into color images.

Utilizing advanced deep learning techniques, the model learns to add realistic colors to grayscale images, effectively enhancing them with vivid hues.

The project demonstrates the application of neural networks in image processing, providing a powerful tool for automatic colorization.

Features

• Neural Network-Based Colorization: Transforms grayscale images into color using state-of-the-art neural network architectures.
• High-Quality Colorization: Generates realistic and visually appealing color images from monochromatic inputs.
• Easy-to-Use: Simple integration and usage with clear instructions provided.

Getting Started

git clone https://github.com/gralliry/Gray2Color.git
cd Gray2Color

pip install -r requirements.txt

Usage

Train

python train.py -d your_dataset_path -lr 0.001 -e 3000 -bs 16

Evaluate

python evaluate.py -d your_sample_dir