SpectraX — Unified Surveillance System

SpectraX is a streamlined surveillance system for turning any phone, tablet, or IP camera into a secure RTSP/HLS streaming source with object detection capabilities. It's built for people who need a simple, powerful, and private way to set up a surveillance system or a quick streaming solution.

⚠️ Note: SpectraX uses a self-signed certificate for RTSPS by default, which can trigger security warnings in some clients. For production use, replace it with a certificate from a trusted CA.

Table of Contents

• What It Does
• Key Features
• Quick Start
• Basic Usage
• Configuration
• Connecting Your Cameras
• Documentation
• Contributing
• License

What It Does

SpectraX wraps MediaMTX, a powerful RTSP/HLS server, with intelligent object detection, tracking, and recording capabilities. The vision pipeline is built on Ultralytics YOLOv8 for detection and Roboflow's supervision library for annotations and ByteTrack tracking. Turn any device with a camera into a smart surveillance system with advanced analytics in minutes.

Key Features

🎥 Streaming

• Multiple Protocols: RTSP (low latency), RTSPS (encrypted), and HLS (browser-compatible)
• Mobile-Ready: Works with Larix Broadcaster and other RTSP apps
• Multi-Camera Support: Monitor multiple streams simultaneously
• Automatic Credentials: Secure, randomly generated passwords stored in system keychain

🤖 AI Object Detection

• YOLO Integration: Real-time object detection using YOLOv8 models
• Customizable Models: Choose from nano (fast) to large (accurate) models
• Smart Filtering: Detect specific objects (person, car, dog, etc.)
• Visual Overlays: Bounding boxes and labels rendered with Roboflow supervision annotators
• Adjustable Confidence: Fine-tune detection sensitivity

🎯 Object Tracking (NEW!)

• Persistent IDs: Track individual objects across frames with unique IDs
• ByteTrack Integration: State-of-the-art multi-object tracking via Roboflow supervision
• Visual Feedback: See tracker IDs in labels (e.g., "person #42 0.95")
• Database Storage: Query recordings by specific tracker ID
• Analytics: Track which objects appear most frequently
• Configurable: Adjust tracking parameters for your use case

📹 Event-Based Recording

• Intelligent Recording: Automatically record when objects are detected
• Pre/Post Buffers: Capture 10 seconds before and after detections
• Selective Recording: Only record specific object types
• SQLite Database: Searchable metadata for all recordings
• Storage Management: Automatic cleanup when storage limits reached

🌐 Web Dashboard

• Live Viewing: Real-time video with AI detection overlays
• Recordings Browser: View and manage all recorded clips
• Multi-Camera Grid: Monitor all cameras in one interface
• REST API: Access recordings and statistics programmatically
• Responsive Design: Works on desktop and mobile browsers

🔐 Security

• RTSPS Encryption: TLS-encrypted RTSP streams
• Credential Management: Secure storage using OS keyring
• Network Isolation: Bind to localhost or specific interfaces
• Self-Signed Certificates: Included for immediate use

Quick Start

Prerequisites

System Requirements:

• macOS, Linux, or Windows
• Python 3.8 or higher
• 4GB RAM minimum (8GB recommended for multiple cameras)
• Tested on macOS Sequoia 15.4.1

Required Software:

1. MediaMTX - RTSP/HLS streaming server

   # macOS
   brew install mediamtx
   
   # Linux
   # Download from https://github.com/bluenviron/mediamtx/releases
   
   # Windows
   # Download from https://github.com/bluenviron/mediamtx/releases

2. Python 3.8+

   python3 --version  # Check your version

Recommended Clients:

• Mobile Publishing: Larix Broadcaster (iOS/Android)
• Desktop Viewing: OBS Studio or VLC Media Player

Installation

1. Clone and Setup

# Clone the repository
git clone https://github.com/SpectraCoreX/SpectraX.git
cd SpectraX

# Create virtual environment
python3 -m venv venv
source venv/bin/activate  # macOS/Linux
# or: .\venv\Scripts\activate  # Windows

# Install dependencies
cd video-feed
pip install -r requirements.txt
cd ..

2. Download YOLO Models (optional - will auto-download on first use)

cd video-feed/models
wget https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8n.pt
wget https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8l.pt
cd ../..

3. Configure Your System

Edit video-feed/config/surveillance.yml to set your camera paths and preferences (see Configuration Guide for details).

Start the System

# Start with configuration file (recommended)
./scripts/surveillance.sh config

# Quick start with defaults (1 camera at video/camera-1)
./scripts/surveillance.sh quick

# Open standalone web dashboard
./scripts/surveillance.sh dashboard

The system will display connection URLs for your cameras and the web interface.

Basic Usage

Web Dashboard

Access the web interface at the URL shown when starting the system (e.g., http://192.168.x.x:8080):

• Live Video: Real-time streams with AI detection overlays
• Multi-Camera Grid: View all cameras simultaneously
• Recordings Browser: Search and play recorded clips
• Statistics: FPS, detection counts, and system status

Command Line

# Start with configuration file (recommended)
./scripts/surveillance.sh config

# Quick start with defaults
./scripts/surveillance.sh quick

# Start streaming server only (no detection)
python -m videofeed.surveillance run --path video/front-door

# Start detection only (existing stream)
python -m videofeed.surveillance detect --rtsp-url "rtsps://viewer:pass@host:8322/video/cam"

# Query recordings by tracker ID
python scripts/query_recordings.py tracker 42

# Reset stored credentials
python -m videofeed.surveillance reset

REST API

Access recordings and system data programmatically:

# Get system status
curl http://localhost:8080/status

# List all recordings
curl http://localhost:8080/api/recordings

# Get recording statistics
curl http://localhost:8080/api/recordings/stats

See API Documentation for complete endpoint reference.

Configuration

All settings are managed in video-feed/config/surveillance.yml.

Quick example:

cameras:
  - video/front-door
  - video/backyard

detection:
  enabled: true
  model: "yolov8n.pt"
  confidence: 0.4
  filters:
    classes: ["person", "car", "dog"]

recording:
  enabled: true
  max_storage_gb: 10.0

For complete configuration options, see the Configuration Guide.

Connecting Your Cameras

When the system starts, it displays connection URLs:

📱 For Mobile Cameras (Publishing):

1. Install Larix Broadcaster on your phone
2. Use the RTSPS URL shown in the terminal
3. Enter the publisher username and password
4. Start streaming!

🖥️ For Viewing:

• Web Dashboard: Open the URL shown (e.g., http://192.168.x.x:8080)
• OBS/VLC: Use the viewer RTSPS URL with credentials
• Browser HLS: Use the HLS URL for browser-based viewing

Documentation

For Users

• Configuration Guide - Complete configuration reference
• Tracking Guide - Object tracking features and usage
• Recording Setup - Event-based recording configuration

For Developers

• API Documentation - REST API reference for building clients
• Architecture Guide - Codebase structure and development guide

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Make your changes with tests
4. Submit a pull request

See the Architecture Guide for codebase details.

License

See LICENSE file for details.

Acknowledgments

• MediaMTX - Excellent RTSP/HLS server
• Ultralytics YOLOv8 - State-of-the-art object detection
• Roboflow Supervision - Computer vision utilities, annotators, and ByteTrack integration
• ByteTrack - Multi-object tracking algorithm
• FastAPI - Modern web framework