This Advanced Image Editor is a simple yet powerful tool built using Python, OpenCV, and NumPy. It allows users to apply various filters and image processing techniques to their images through a graphical user interface. The application is designed for both educational purposes and practical use cases, providing a clear demonstration of basic image processing operations.
- Gaussian Filter: Smoothens the image using a Gaussian kernel.
- High Pass Filter: Enhances the edges in the image.
- Histogram Equalization: Improves the contrast of the image.
- Contour Detection: Detects and draws contours in the image.
- Gaussian Noise Addition: Adds Gaussian noise to the image.
- Mean Filter: Applies a mean filter to the image.
- Low Pass Filter: Smoothens the image using a low pass filter.
- Min-Max Smoothing: Applies min-max smoothing to the image.
- Median Filter: Applies a median filter to the image.
- Hybrid Median Filter: Applies a hybrid median filter to the image.
- Morphological Operations: Performs dilate, erode, open, and close operations on the image.
- Python 3.x
- OpenCV
- NumPy
- SciPy
- PyQt5
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Clone the repository: git clone https://github.com/devcom33/Advanced-Image-Editor-Using-Python.git cd Advanced-Image-Editor-Using-Python
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Create and activate a virtual environment (optional but recommended): python -m venv venv source venv/bin/activate # On Windows, use `venv\Scripts\activate` 
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Install the required packages: pip install -r requirements.txt 
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Run the GUI application: python ui_app.py 
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Load an image: - Click on Open Imageand select the image you want to edit.
 
- Click on 
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Apply filters: - Use the toolbar and menu options to apply various edits and effects to your image.
 
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Save the image: - Click on Save Imageto save your edited image.
 
- Click on 
Advanced-Image-Editor-Using-Python/
├── README.md
├── requirements.txt
├── filter_image.py
├── ui_app.py
Here are some screenshots of the application in action:

