An Intelligent Workforce Performance & Productivity Analytics Platform
Transform your industrial operations with cutting-edge computer vision and data analytics. Built with Django and advanced machine learning to deliver actionable insights from your factory floor.
Syzaar+ transforms raw visual data from industrial environments into actionable business intelligence. Our platform combines computer vision, machine learning, and intuitive web interfaces to help manufacturing facilities optimize workforce productivity, reduce operational costs, and maintain quality standards.
- Real-time Monitoring: Track workforce activity across multiple zones simultaneously
- Data-Driven Decisions: Convert visual observations into quantifiable metrics
- Seamless Integration: Works with existing IP camera infrastructure
- Scalable Architecture: Built on Django for enterprise-level deployment
Feature | Description | Status |
---|---|---|
📍 Precision Zone Management | Define, edit, and manage specific work zones with an intuitive drag-and-drop interface. Isolate analysis to areas that matter most. | ✅ Done |
🧠 AI-Powered Activity Recognition | Leverage advanced algorithms to automatically detect active vs. idle states, flagging anomalies and prolonged inactivity in real-time. | ⏳ Planned |
📹 Seamless Multi-Camera Integration | Natively support and auto-discover up to 10 simultaneous IP camera streams, providing a comprehensive view of your operations. | ✅ Done |
🤖 Dedicated AI Models per Zone | Assign specialized, fine-tuned AI models to each zone, ensuring maximum accuracy for diverse and specific tasks. | ⏳ Planned |
📊 Granular Data & Reporting | Capture frame-by-frame performance data and generate comprehensive reports in standard formats like Excel for deep analysis. | ✅ Done |
🖥️ Intuitive & Dynamic UI | A modern, responsive user interface with live visual labeling, providing at-a-glance insights without technical complexity. | ✅ Done |
Category | Technologies |
---|---|
Backend | 🐍 Python, Django |
Frontend | 📄 HTML5, 🎨 CSS3, 💡 JavaScript |
Database | 🗄️ SQLite 3 (Default), 🐘 PostgreSQL (Production) |
AI/ML | 👁️ OpenCV, 🧠 TensorFlow/PyTorch (Planned) |
Syzaar+/
│
├── Config/ # Main project configuration
│ ├── settings.py
│ └── urls.py
│
├── Detection_App/ # Core application
│ ├── admin.py
│ ├── forms.py
│ ├── models.py
│ ├── urls.py
│ └── views.py
│
├── static/ # Static assets
│ ├── css/ # Stylesheets
│ ├── js/ # JavaScript files
│ └── images/ # Image assets
│
├── templates/ # HTML templates
│ ├── base.html
│ ├── landing.html
│ ├── login.html
│ ├── overview.html
│ ├── camera_management.html
│ ├── zone_configuration.html
│ └── reports.html
│
├── db.sqlite3
└── manage.py
- Python 3.12 or higher
- Git
-
Clone the Repository
git clone https://github.com/Amin-moniry-pr/syzaar-plus.git cd syzaar-plus
-
Create and Activate Virtual Environment
Windows:
python -m venv venv .\venv\Scripts\activate
macOS/Linux:
python3 -m venv venv source venv/bin/activate
-
Install Dependencies
pip install -r requirements.txt
-
Apply Database Migrations
python manage.py makemigrations python manage.py migrate
-
Create Superuser
python manage.py createsuperuser
-
Run Development Server
python manage.py runserver
The application will be available at http://127.0.0.1:8000/
- Access the Application: Navigate to
http://127.0.0.1:8000/
- Login: Use your superuser credentials
- Admin Panel: Access at
http://127.0.0.1:8000/admin/
for camera and zone management - Dashboard: Explore different sections to manage operational data
Create a requirements.txt
file with:
Django>=5.0.0
opencv-python>=4.8.0
Pillow>=10.0.0
numpy>=1.24.0
- Implement AI-powered activity recognition
- Add dedicated AI models per zone
- Enhance real-time analytics
- Implement advanced reporting features
- Add mobile app support
- Integrate with external systems
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature
) - Commit your Changes (
git commit -m 'Add some AmazingFeature'
) - Push to the Branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
- GitHub: (https://github.com/Amin-moniry-pr/)
- Issues: Please report bugs and feature requests through GitHub Issues
- Email: Contact the development team for enterprise support
If you find this project helpful, please consider giving it a ⭐ on GitHub!