Rat Path Tracker - Advanced Motion Analysis System

A professional GUI application for tracking and analyzing rat movement paths in video footage using computer vision.

Features

• 🎥 Video Input: Support for webcam and video files (MP4, AVI, MOV, MKV)
• 🎯 Interactive Selection: Click and drag to select the target
• ▶️ Real-time Tracking: CSRT tracker for accurate motion tracking
• 📊 Live Statistics: Distance, average speed, and path points
• 💾 Export Options: Save path data as CSV and images as PNG
• 🎨 Modern UI: Clean, professional interface with dark theme
• 📈 Automatic Summary: End-of-video dialog with save options

Installation

Prerequisites

• Python 3.8 or higher
• Windows/Linux/macOS

Setup

1. Create a virtual environment (recommended):

python -m venv venv

2. Activate the virtual environment:

   • Windows: venv\Scripts\activate
   • Linux/Mac: source venv/bin/activate

3. Install dependencies:

pip install -r requirements.txt

Usage

Run the application:

python fresh.py

Workflow

1. Load Video Source

   • Click "🎥 Use Webcam" for live camera feed
   • Click "📁 Load Video File" to open a video file

2. Select Target

   • Click "🎯 Select Target"
   • Click and drag on the video to draw a box around the rat
   • Release to confirm selection

3. Start Tracking

   • Click "▶️ Start" to begin tracking
   • The path will be drawn in cyan color
   • Live statistics update in the top bar

4. Control Tracking

   • Click "⏹️ Stop" to pause tracking
   • Click "🗑️ Clear Path" to reset the recorded path

5. Save Results

   • When video ends, a summary dialog appears automatically
   • Click "Save Path (CSV)" to export coordinates
   • Click "Save Image (PNG)" to save the final frame with path overlay

Keyboard Shortcuts

• ESC: Cancel current selection

Output Formats

CSV Format

Contains path coordinates:

index,x,y
0,320,240
1,322,242
...

PNG Image

Final video frame with complete path overlay and position markers.

Technical Details

• Tracker: OpenCV CSRT (Discriminative Correlation Filter with Channel and Spatial Reliability)
• Path Rendering: Solid cyan lines with position markers
• Thread-safe: Video processing runs in separate thread
• Auto-scaling: Window adapts to 90% of screen size

Requirements

• opencv-python >= 4.8.0
• numpy >= 1.24.0
• Pillow >= 10.0.0

Troubleshooting

Issue: Buttons appear cut off

• The app auto-scales to 90% of your screen
• Minimum recommended resolution: 1280x720

Issue: Tracking lost

• Try re-selecting the target with a larger bounding box
• Ensure good lighting and contrast
• Avoid rapid movements or occlusions

Issue: Webcam not detected

• Check camera permissions in system settings
• Try closing other applications using the camera
• Verify camera is properly connected

License

MIT License - Free to use and modify

Author

Created with ❤️ for motion tracking research