Welcome to the Miscellaneous Image Processing Toolkit! This repository contains a collection of miscellaneous methods and experiments related to image processing. Please note that this is a side project and not actively maintained. The purpose of this toolkit is to experiment with various image processing techniques and share insights with the community. Feel free to explore the provided Jupyter Notebook (test.ipynb) to see the implemented methods.
This repository contains a Jupyter Notebook (test.ipynb) that showcases the following image processing techniques:
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Convolution Function: A method for applying convolution to an image using a given kernel.
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Image Loading: A method to load images from a specified directory and convert them into NumPy arrays.
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Sobel Edge Detection: Implementation of the Sobel edge detection algorithm along with non-maximal suppression (NMS) for enhancing detected edges.
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Canny Edge Detection: Utilizing the Canny edge detection algorithm to identify edges in an image.
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Morphological Operations: Applying morphological closing and image filling to enhance edge detection results.
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Cluster Labeling: Labeling connected components in a binary image and removing small clusters.
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Background Removal: Demonstrating how the pipeline can be used to remove backgrounds from product images.
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Cropping and Resizing: Identifying non-white regions and cropping/resizing the image accordingly.
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Color Adjustment: Attempting to adjust colors based on a specified threshold.
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Saving Results: Saving the processed images to disk.
To use the provided methods and experiments, simply open the Jupyter Notebook test.ipynb. Execute each cell to see the results of different image processing techniques.
Please note that this project is not actively maintained, and some code segments might be incomplete or experimental. Feel free to explore, experiment, and adapt the methods for your own use.
Contributions are welcome! If you'd like to contribute to the project, here's how you can do it:
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Fork the Repository: Click the "Fork" button in the upper right corner of this repository to create your own copy.
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Make Changes: Make the desired changes or additions to the codebase.
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Submit a Pull Request: Once your changes are ready, submit a pull request to the main repository. Provide a clear description of your changes and why they are valuable.
This project was created as a personal exploration of image processing techniques and may contain experimental or incomplete code. Use the methods provided at your own discretion.
This project is provided under the MIT License. See the LICENSE file for more details.
Note: The content and code provided in this repository are for educational and experimental purposes only. The project may not be actively maintained or updated.