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

1. Clone the repository:

   git clone https://github.com/devcom33/Advanced-Image-Editor-Using-Python.git
   cd Advanced-Image-Editor-Using-Python

2. Create and activate a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate    # On Windows, use `venv\Scripts\activate`

3. Install the required packages:

   pip install -r requirements.txt

1. Run the GUI application:

   python ui_app.py

2. Load an image:

   • Click on Open Image and select the image you want to edit.

3. Apply filters:

   • Use the toolbar and menu options to apply various edits and effects to your image.

4. Save the image:

   • Click on Save Image to save your edited image.

Advanced-Image-Editor-Using-Python/
├── README.md
├── requirements.txt
├── filter_image.py
├── ui_app.py

Here are some screenshots of the application in action: