Viseron
Self-hosted, local-only NVR with AI computer vision for object detection, motion detection, and face recognition.
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Self-hosted, local-only NVR with AI computer vision for object detection, motion detection, and face recognition.
Core Features
- Object detection with multiple model support
- Motion detection and zone masking
- Face recognition
- Built-in web configuration interface
- Fully local processing, no cloud dependency
What It Can't Do
- •For real-time object detection, a GPU-capable host is recommended; otherwise, frame rate may be low. 2. Default memory usage is around 1-2GB; ensure sufficient RAM. 3. The component system requires reading documentation; beginners may face a learning curve. 4. The community is relatively small; hardware compatibility may need manual testing.
Use Cases
- Home security monitoring
- Office or warehouse real-time alerts
- Intrusion detection in unattended areas
Detailed Introduction
Viseron is a self-hosted, privacy-focused NVR (Network Video Recorder) and AI computer vision software that runs entirely on your local network. It supports object detection, motion detection, face recognition, and other vision features through a modular component system. The software is deployed via Docker and configured through a built-in web interface, making it easy to set up and manage. Unlike cloud-dependent solutions, Viseron keeps all video processing and data local, ensuring full control and privacy. It is designed for home security, office monitoring, and any scenario where real-time vision analytics are needed without internet exposure.
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Getting Started
Download installer
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Install the software
Double-click the downloaded installer and follow the prompts
Step 1: Install Docker and pull the Viseron image (docker pull roflcoopter/viseron)
Step 2: Run the container with a mounted config directory: docker run -d --name viseron -p 8080:8080 -v /path/to/config:/config roflcoopter/viseron
Step 3: Open http://localhost:8080 in your browser and configure cameras and detection components via the web interface
- Step 1: Install Docker and pull the Viseron image (docker pull roflcoopter/viseron)
- Step 2: Run the container with a mounted config directory: docker run -d --name viseron -p 8080:8080 -v /path/to/config:/config roflcoopter/viseron
- Step 3: Open http://localhost:8080 in your browser and configure cameras and detection components via the web interface
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Open Source Transparency
View GitHub SourceUninstall Info
Stop and remove the Viseron container: docker stop viseron && docker rm viseron. Delete the mounted config directory if you want to remove all data.
No Extra Dependencies
Ready to use after download. No additional runtime required.
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