This Python project combines image pixelation and stitching techniques to create a final stitched image based on a target pixelated image. The size of the stitched grid is determined by the dimensions of the pixelated target image. The project uses OpenCV for image processing and manipulation.
Before running this project, make sure you have the following dependencies installed:
- Python (3.6 or higher)
- OpenCV (cv2)
- NumPy
You can install OpenCV and NumPy using pip:
pip install opencv-python numpy
Project Structure
The project includes the following files and directories:
main.py: The main Python script that performs pixelation, image stitching, and display.
images/: A directory containing random images for stitching.
images/target_image.jpg: The target image you want to pixelate and use as a reference for stitching.
Usage
Place the target image you want to use in the images/ directory, and name it target_image.jpg.
Run the main.py script using the following command:
bash
Copy code
python main.py
The script will pixelate the target image and determine the grid size based on the pixelated image dimensions.
Random images from the images/ directory will be resized to match the grid size and stitched together.
The final stitched image will be displayed in a window along with the pixelated target image.
The stitched image will be saved as "OutputImage.jpg" in the project directory.
Press any key to close the image windows.
Customization
Adjust the pixel_size variable in the main.py script to control the level of pixelation applied to the target image.
Modify the content of the images/ directory to include your own random images for stitching.
Customize the screen width and height in the script for displaying the final stitched image.
License
This project is licensed under the MIT License. See the LICENSE file for details.
Acknowledgments
This project serves as a demonstration of image processing techniques using OpenCV and can be a foundation for more advanced image manipulation projects.