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Image Segmentation Control

This Python application uses tkinter for the GUI and pypylon to interface with Basler cameras. It processes live video feed from the camera and performs various image segmentation tasks including line detection, blob detection, color segmentation, edge detection, contour detection, and shape detection. The application also allows users to save the processed image data to a CSV file.

Features

  • Live Video Feed: Start and stop live video feed from a Basler camera.
  • Display Options: Choose between different image segmentation techniques (lines, blobs, color, edges, contours, shapes, or both lines and blobs).
  • Graphical Display: Real-time plots of line and blob detection counts.
  • Save Data: Save the processed image data (timestamp, line count, blob count) to a CSV file.

Requirements

  • Python 3.x
  • tkinter
  • pypylon
  • opencv-python
  • numpy
  • matplotlib
  • Pillow

Installation

  1. Clone the repository:

    git clone https://github.com/yourusername/image-segmentation-control.git
cd image-segmentation-control

  2. Install dependencies:

    pip install tkinter pypylon opencv-python numpy matplotlib Pillow

Usage

  1. Connect your Basler camera.

  2. Run the application:

    python image_segmentation_control.py

  3. Control the application through the GUI:

    • Click "Start Video Feed" to begin the live video feed.
    • Select the desired image segmentation technique from the display options.
    • Click "Stop Video Feed" to stop the live video feed.
    • Click "Save Data" to open a file dialog and choose where to save the CSV file with the processed image data.

GUI Elements

  • Video Feed Label: Displays the live video feed from the camera.
  • Start/Stop Video Buttons: Control the live video feed.
  • Display Options: Radio buttons to choose the type of image segmentation.
  • Save Data Button: Opens a file dialog to save the CSV file.
  • Real-time Plots: Displays plots of line and blob detection counts.

Code Overview

  • initialize_gui(): Sets up the GUI elements.
  • setup_camera(): Configures the Basler camera.
  • start_video_feed() / stop_video_feed(): Starts and stops the live video feed.
  • update_camera_feed(): Continuously retrieves images from the camera.
  • process_image(): Processes each frame from the camera according to the selected display option.
  • save_data(): Saves the collected image data to a CSV file.
  • detect_lines() / detect_blobs() / color_segmentation() / edge_detection() / contour_detection() / shape_detection(): Image segmentation methods.

Contributing

Contributions are welcome! Please fork this repository and submit pull requests for any enhancements or bug fixes.

License

This project is licensed under the MIT License.

Acknowledgments

  • pypylon - Python bindings for the pylon Camera Software Suite.
  • OpenCV - Open Source Computer Vision Library.
  • tkinter - Python's de-facto standard GUI package.
  • matplotlib - Comprehensive library for creating static, animated, and interactive visualizations in Python.
  • Pillow - Python Imaging Library (PIL) fork.

Feel free to update this README with additional information as needed.