Welcome to the Photo Colorization Model repository! This project aims to provide a powerful machine-learning solution for transforming black-and-white photos into vibrant, realistic color images. The model uses advanced deep learning techniques and comprises an encoder, decoder, fusion layer, and classification layer.
Our colorization model consists of the following components:
- Encoder: Extracts essential features from black and white images.
- Decoder: Generates high-resolution color images based on the encoded features.
- Fusion Layer: Combines encoded features with external references, enhancing colorization accuracy.
- Classification Layer: Understands and classifies different objects and scenes within the image, guiding the colorization process.
I would like to express our gratitude to the open-source community for their valuable contributions and to the developers of TensorFlow and other libraries utilized in this project. I would like to thank Emil Wallner for the amazing blog, which is the inspiration for this project. For the dataset, I would like to thank Aayush Sharma.
If you have any questions, suggestions, or feedback, please don't hesitate to reach out to me at Kaggle. We appreciate your interest in our project and look forward to hearing from you!
Happy colorizing!