The Image-Colorizer project leverages deep learning techniques to add realistic colors to grayscale images. This tool utilizes advanced neural networks to predict and apply appropriate colors to images automatically. The result enhances the visual appeal of black-and-white photos with vibrant, lifelike colorization.
- Automatic colorization of grayscale images.
- Supports diverse image styles and content.
- Powered by state-of-the-art deep learning algorithms for accurate and realistic results.
data/: Contains sample grayscale images and optional datasets for testing.models/: Pre-trained deep learning models used for image colorization.scripts/: Python scripts for preprocessing, training, and inference.outputs/: Folder to store colorized images generated by the model.README.md: Documentation for the project.
- Python: Core programming language for the project.
- TensorFlow: Deep learning framework for training and deploying the colorization model.
- OpenCV: Image processing library for handling image inputs and outputs.
This project is open-source and available under the MIT License.