kherin / colorwizard

ColorWizard is a Python-based project that aims to automate the coloring process of physical coloring books.

ColorWizard 🎨

⚠️ IMPORTANT: The current project is in development and experimental.

ColorWizard is a Python-based project that aims to automate the coloring process of physical coloring books. It uses computer vision techniques to scan and detect the regions in a coloring book page, and then automatically applies colors to those regions, creating a digitally colored version of the page.

Features

• Region Segmentation: The project employs image processing algorithms to segment the coloring book page into distinct regions, each representing a separate area to be colored.

Installation

1. Clone the repository:

   git clone https://github.com/kherin/ColorWizard.git

2. Navigate to the project directory:

cd ColorWizard

3. Install the required dependencies:

pip install -r requirements.txt

Usage

Run the ColorWizard server:

python server.py

Open your web browser and navigate to the provided URL (e.g., http://localhost:5000).

Process_video.py 📄

The process_video.py file contains the core functionality for processing the coloring book pages. It imports the necessary libraries and defines functions to perform the following tasks:

Image Preprocessing: This function prepares the uploaded image for further processing by resizing, converting to grayscale, and applying various filters and transformations. Region Segmentation: This function uses computer vision algorithms to segment the coloring book page into distinct regions, each representing a separate area to be colored.

The process_video.py file is imported and utilized by the server application (server.py) to handle the image processing and coloring tasks.

video_capture.html 📄

The video_capture.html file is an HTML template that provides the user interface for the ColorWizard web application.

Contributing

Contributions to ColorWizard are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request on the project's GitHub repository.

Acknowledgments

The project utilizes the following open-source libraries and frameworks: OpenCV for image processing and computer vision tasks. NumPy for numerical computations. Flask for the web application framework.