https://github.com/selcia25/image-processing-toolkit
📸Image Processing Toolkit is a Python script that provides a set of common image processing operations using the OpenCV library.
https://github.com/selcia25/image-processing-toolkit
blending-images color-inversion contour-detection dilation edge-detection erosion gaussian-blur histogram-equalization image-processing opencv python
Last synced: 2 months ago
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📸Image Processing Toolkit is a Python script that provides a set of common image processing operations using the OpenCV library.
- Host: GitHub
- URL: https://github.com/selcia25/image-processing-toolkit
- Owner: selcia25
- Created: 2024-01-04T17:27:32.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-02-06T13:50:50.000Z (about 1 year ago)
- Last Synced: 2025-01-02T08:14:33.284Z (4 months ago)
- Topics: blending-images, color-inversion, contour-detection, dilation, edge-detection, erosion, gaussian-blur, histogram-equalization, image-processing, opencv, python
- Language: Jupyter Notebook
- Homepage:
- Size: 1.04 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Image Processing Toolkit
## Overview
Image Processing Toolkit is a Python script that provides a set of common image processing operations using the OpenCV library. This toolkit allows you to perform tasks such as thresholding, edge detection, contour visualization, image inversion, histogram equalization, morphological operations, blending, denoising, and blurring.
## Features
- **Thresholding:** Convert images to binary based on a threshold.
- **Edge Detection:** Detect edges in images using the Canny edge detector.
- **Contours:** Find and visualize contours in images.
- **Inversion:** Create inverted versions of images.
- **Histogram Equalization:** Enhance the contrast of grayscale images.
- **Morphological Operations:** Erode and dilate images for noise reduction and feature enhancement.
- **Blending:** Blend two images together with adjustable weights.
- **Denoising:** Remove noise from colored images using non-local means denoising.
- **Blurring:** Apply Gaussian blur to grayscale images.
## Usage
1. Open the Jupyter Notebook (`reconstruction.ipynb`).
2. Run each cell to see the output and visualize the results.
## Contributing
Feel free to contribute to the project by opening issues or submitting pull requests. Your feedback and suggestions are highly appreciated.