FocusCC: Python-Based Computer Vision for Cloud Chamber Events

Author: Nicolò Bagnasco
Contact: nicolo.bagnasco@edu.unito.it

---

Overview

FocusCC is a Python-based application designed for detecting and analyzing events in a cloud chamber using computer vision techniques. It processes a live video feed, applies edge detection, and identifies particle tracks in real time. The software also supports saving detected events, managing multiple webcams, and customizing various detection parameters.

---

Features

Main Features:

• Live Video Feed: Displays both raw and processed video feeds in real time.
• Event Detection: Detects particle tracks based on edge detection and threshold parameters.
• Webcam Selection: Choose from multiple connected webcams via a dropdown menu.
• Cooldown Feature: Avoid redundant detections by setting a cooldown time between events.
• Customizable Parameters:
  • Event detection threshold
  • Low and high thresholds for Canny edge detection
• Event Logging: Logs all system messages and detected events in a console-like interface.
• Save Events: Toggle between saving detected events as image files or viewing them live.

---

System Requirements

• Python 3.8 or newer
• Supported Operating Systems:
  • macOS
  • Linux
  • Windows (partial webcam detection support)
• Required Python libraries:
  • opencv-python
  • numpy
  • Pillow
  • tkinter (pre-installed with Python)

---

Installation

Steps to Install:

1. Clone the Repository:

   git clone https://github.com/bagnasconicolo/Focuscc
   cd FocusCC

2. Install Dependencies:

   pip install -r requirements.txt

3. Run the Application:

   python Focuscc.py

---

Usage

GUI Overview

1. Live Feed:

   • Displays the original and processed video feeds side by side.
   • Detected events are highlighted in the processed feed.

2. Controls:

   • Start Webcam: Activates the video feed for the selected camera.
   • Stop Webcam: Deactivates the video feed.
   • Save Events: Toggles saving detected events as .jpg files.

3. Webcam Selector:

   • Use the dropdown menu to select from available webcams.

4. Event Log:

   • Displays system messages and detected events in a console-like interface.

5. Filename Prefix:

   • Customize the prefix for saved event files.

6. Cooldown:

   • Avoid redundant detections by enabling a cooldown period (in seconds) between events.

---

Workflow

1. Start the Webcam:

   • Select a camera from the dropdown menu.
   • Click Start Webcam to begin the live feed.

2. Adjust Parameters:

   • Use sliders to customize the detection threshold and Canny edge detection parameters.

3. Monitor Events:

   • Detected events will be logged in the Event Log and highlighted in the processed feed.

4. Save Events:

   • Enable Save Events to save images of detected events.

5. Stop or Exit:

   • Use Stop Webcam to deactivate the feed or Exit to close the application.

---

Customization

Parameters:

• Event Threshold: Adjusts sensitivity for detecting events.
• Canny Edge Detection:
  • Low Threshold: Lower bound for detecting edges.
  • High Threshold: Upper bound for detecting edges.
• Filename Prefix: Set a custom prefix for saved event images.
• Cooldown: Set a time delay (in seconds) between consecutive detections.

File Customization:

• Icon: Replace ccicon.png with your desired icon file in the project directory.

---

Troubleshooting

Common Issues:

1. Webcam Not Detected:

   • Ensure the webcam is connected and properly recognized by your operating system.
   • On Linux, ensure v4l2-ctl is installed.
   • On macOS, ensure camera permissions are enabled.

2. No Events Detected:

   • Lower the Event Threshold slider.
   • Adjust Canny Edge Detection parameters for better sensitivity.

3. Application Crash:

   • Ensure all required libraries are installed.
   • Verify that the correct camera index is selected.

4. Icon Not Displaying:

   • Ensure the icon file ccicon.png is in the correct directory and properly named.

---

Future Improvements

• Support for advanced particle track visualization.
• Automated analysis of saved event data.
• Cross-platform webcam detection enhancements for Windows.
• Extended cooldown customization (e.g., per event type).

---

License

This software is open-source and distributed under the MIT License.

---

Contact

For support, feedback or contributions, contact Nicolò Bagnasco:
📧 nicolo.bagnasco@edu.unito.it