https://github.com/nav3005/image-colorizer
Streamlit app for Colorization of B/W images through hallucinations
https://github.com/nav3005/image-colorizer
Last synced: over 1 year ago
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Streamlit app for Colorization of B/W images through hallucinations
- Host: GitHub
- URL: https://github.com/nav3005/image-colorizer
- Owner: Nav3005
- License: mit
- Created: 2025-03-18T16:30:19.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-18T16:40:32.000Z (over 1 year ago)
- Last Synced: 2025-03-18T16:41:52.638Z (over 1 year ago)
- Language: Python
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Image Colorizer
This Streamlit application uses deep learning to automatically colorize black and white images. The app employs a pre-trained model based on the Zhang et al. colorization architecture to add realistic colors to grayscale photographs.
## Features
- Upload black and white images in JPG, JPEG, or PNG format
- Real-time colorization using deep learning
- Download capability for colorized images
- User-friendly web interface
## Prerequisites
- Python 3.8 or higher
- Required Python packages (listed in requirements.txt)
- Model files (download instructions below)
## Installation
1. Clone this repository:
```bash
git clone https://github.com/Nav3005/Image-Colorizer.git
cd Image-Colorizer
```
2. Install the required packages:
```bash
pip install -r requirements.txt
```
3. Download the model files:
- Create a `Model` directory in the project root
- Download the following files and place them in the `Model` directory:
- [colorization_deploy_v2.prototxt](https://raw.githubusercontent.com/richzhang/colorization/master/colorization/models/colorization_deploy_v2.prototxt)
- [colorization_release_v2.caffemodel](https://www.dropbox.com/s/dx0qvhhp5hbcx7z/colorization_release_v2.caffemodel?dl=1)
- [pts_in_hull.npy](https://raw.githubusercontent.com/richzhang/colorization/master/colorization/resources/pts_in_hull.npy)
## Usage
1. Run the Streamlit app:
```bash
streamlit run app.py
```
2. Open your web browser and navigate to the provided local URL (typically http://localhost:8501)
3. Upload a black and white image using the file uploader
4. Wait for the colorization process to complete
5. Download the colorized image using the "Download Colorized Image" button
## Model Information
The colorization model used in this application is based on the research paper "Colorful Image Colorization" by Zhang et al. It uses a deep neural network trained on a large dataset of color images to predict the most likely colors for a given grayscale input.
## Limitations
- The model works best with natural photographs
- Results may vary depending on the quality and content of the input image
- Processing time depends on the image size and your computer's specifications
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Acknowledgments
- Original colorization model by [Richard Zhang](https://github.com/richzhang/colorization)
- Built with Streamlit