Detectra is a professional AI-powered desktop application designed to detect and document the disappearance of objects in CCTV and video footage. Version 2.1.0 introduces a comprehensive UI/UX overhaul, featuring a sleek modern design, automated setup, and enhanced stability.
The system allows users to select an object within a video and intelligently track it across frames using high-performance computer vision. If the object disappears from the scene, Detectra automatically captures high-resolution evidence snapshots for forensic analysis.
- Professional Branding: Custom icons, high-DPI scaling support, and a polished dark-themed interface.
- Splash Screen: Smooth initial loading experience with real-time status updates.
- Responsive Canvas: Dynamic video scaling and interactive bounding-box selection.
- YOLOv8 & ByteTrack: State-of-the-art object detection and persistent tracking for reliable monitoring.
- Live Preview: Real-time visual feedback of the tracking process.
- Variable Speed: Adjustable processing speeds (1x to 10x) to handle long-duration CCTV footage efficiently.
- Automatic Snapshots: Captures "Before" and "After" frames the moment an object is no longer detected.
- OCR Timestamp Extraction: Automatically extracts on-screen timestamps from CCTV feeds (Alpha).
- Export Management: Organized results export with timestamped folders.
- Zero-Install EXE: Packaged as a single-file portable Windows executable.
- Automated Setup: On first launch, Detectra automatically downloads and configures the required AI models.
- OS: Windows 10 or 11 (64-bit)
- RAM: 8 GB (16 GB Recommended)
- Dependencies: The standalone version requires an active internet connection on the first launch only to download models.
- Download
Detectra_v2.1.0.exefrom the Releases page. - Run the file directly. No installation is required.
- Clone the repo:
git clone https://github.com/NEIL-DANIEL-A/Detectra.git - Create virtual environment:
python -m venv venv - Activate:
venv\Scripts\activate - Install requirements:
pip install -r requirements.txt - Run:
python main.py
| File | Description |
|---|---|
main.py |
Application entry point, UI management, and Splash Screen. |
tracker.py |
Core AI logic for YOLOv8 detection and object tracking. |
setup.py |
Automated first-run downloader for AI models and weights. |
icon.ico |
High-resolution application branding. |
- Python 3.10+ & Tkinter — Core application framework
- Ultralytics YOLOv8 — State-of-the-art object detection
- OpenCV & PIL — Advanced image and video processing
- EasyOCR — Optical Character Recognition for timestamps
- PyInstaller — Secure executable distribution
Current version: v2.1.0
- Complete UI redesign with Catppuccin inspired color palette.
- Added Windows Taskbar integration and AppUserModelID fix.
- Integrated Automated Model Setup (no more manual downloads).
- Implemented Splash Screen with loading progress tracking.
- Fixed DPI scaling issues for high-resolution displays.
This project is developed for educational and research purposes.