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Vigilance System Dependencies

This document explains the dependencies required for the Vigilance System and how to install them.

Core Dependencies

The Vigilance System relies on several Python packages to function properly. These are categorized by their purpose:

Core Dependencies

  • numpy: For numerical operations and array handling
  • opencv-python: For image processing and computer vision
  • opencv-contrib-python: For advanced OpenCV features like video stabilization
  • pillow: For image handling

Deep Learning

  • torch: PyTorch for deep learning
  • torchvision: Computer vision utilities for PyTorch
  • ultralytics: For YOLOv5 object detection models

Video Streaming

  • av: PyAV for video decoding
  • rtsp: RTSP client for streaming

Web Dashboard

  • flask: Web framework for the dashboard
  • flask-socketio: Real-time communication for the dashboard
  • bidict: Required by flask-socketio
  • python-engineio: Required by flask-socketio
  • python-socketio: Required by flask-socketio

Notification Services (Optional)

  • twilio: For SMS notifications
  • boto3: For AWS SNS notifications

Utilities

  • pyyaml: For YAML configuration files
  • python-dotenv: For environment variable management
  • loguru: For enhanced logging
  • requests: For HTTP requests

Testing

  • pytest: For unit testing
  • pytest-cov: For test coverage reports

Installation

Using the Setup Scripts

The easiest way to install all dependencies is to use the provided setup scripts:

Windows

setup.bat

Linux/Mac

chmod +x setup.sh
./setup.sh

These scripts will:

  1. Create a virtual environment
  2. Install all dependencies from requirements.txt
  3. Install the package in development mode with all extras

Manual Installation

If you prefer to install dependencies manually:

  1. Create and activate a virtual environment:

    python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

  2. Install core dependencies:

    pip install --upgrade pip
pip install -r requirements.txt

  3. Install the package with all extras:

    pip install -e .[notifications,dev]

Installing Specific Extras

If you only need certain features, you can install specific extras:

# For notification features only
pip install -e .[notifications]

# For development and testing only
pip install -e .[dev]

System Dependencies

Some Python packages require system-level dependencies:

OpenCV Dependencies (Linux)

sudo apt-get update
sudo apt-get install -y libsm6 libxext6 libxrender-dev libgl1-mesa-glx

PyTorch with CUDA (Optional, for GPU acceleration)

If you want to use GPU acceleration, make sure you have:

  1. A CUDA-compatible GPU
  2. CUDA Toolkit installed (version compatible with your PyTorch version)
  3. cuDNN installed

Troubleshooting

Common Issues

  1. ImportError: No module named 'cv2'

    • Solution: pip install opencv-python opencv-contrib-python

  2. ImportError: DLL load failed while importing _C

    • Solution: Make sure you have the Visual C++ Redistributable installed (Windows)

  3. No CUDA GPUs are available

    • Solution: Check that your GPU is CUDA-compatible and that you have the correct CUDA version installed

  4. Error loading YOLOv5 model

    • Solution: pip install ultralytics

Checking Installed Packages

To check which packages are installed in your environment:

pip list

To check if a specific package is installed:

pip show package_name

Updating Dependencies

To update all dependencies to their latest versions:

pip install --upgrade -r requirements.txt

To update a specific package:

pip install --upgrade package_name