NVR with AI Detection
NVR with AI Detection osFoundry community catalog में एक app है। Network video recorder के साथ local AI object detection — record from RTSP/RTMP IP cameras, run object detection (person/vehicle/pet), generate motion-triggered clips, publish events के माध्यम से MQTT to Home Assistant. Powered by Frigate. यह upstream image के चारों ओर एक thin wrapper के रूप में आता है के साथ a persistent volume for recordings + config.
विवरण
- Workspace: osfoundry
- Category: COMMUNICATION
- मूल्य: Free
- Access: Community
Features
- Network video recorder with local AI object detection — record from RTSP/RTMP IP cameras
- Run object detection (person/vehicle/pet)
- Generate motion-triggered clips
- Publish events via MQTT to Home Assistant
Documentation
Documentation को upstream project द्वारा अंग्रेज़ी में मेंटेन किया जाता है।
# NVR with AI Detection
Network video recorder + local AI object detection, powered by Frigate.
## Features
- Record from any RTSP / RTMP / ONVIF camera
- Object detection: person / car / dog / cat / bird / package / face
- Motion-triggered + continuous recording
- Event clips with thumbnails
- MQTT events for Home Assistant integration
- Mobile + web review UI
## ⚠️ Hardware acceleration matters
Frigate's object detection model is intended to run on:
- **Coral USB / PCIe TPU** (best efficiency)
- **NVIDIA GPU with TensorRT** (best raw throughput)
- **Intel iGPU with OpenVINO**
- **CPU fallback** (works but limits FPS — single 720p stream max on a small vCPU)
This cloud container ships with **CPU-only detection** as the default — fine for testing or a single camera at low resolution. For real multi-camera deployments, run Frigate on local hardware with a detector and forward its UI through the osFoundry desktop client.
## Packaging
Thin wrapper around the official `ghcr.io/blakeblackshear/frigate` image. Config at `/config/config.yml`; recordings + clips on `/media/frigate` (200 GB default).
osFoundry में NVR with AI Detection का उपयोग कैसे करें
एक क्लिक में NVR with AI Detection को अपने workspace में install करें, फिर अपने stack के लिए prompts, tools, या configuration को customise करने के लिए इसे osStudio में fork करें। आपके workspace का कोई भी सदस्य वहीं से आगे बढ़ा सकता है जहाँ आपने छोड़ा था।
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