Frigate NVR Configuration Expert

Comprehensive Frigate NVR configuration assistance with optimized YAML generation, detector setup, and troubleshooting.

BEFORE YOU START

This skill prevents 12+ common errors and saves ~60% tokens on Frigate configuration.

Metric Without Skill With Skill

Setup Time 2-4 hours 30-45 min

Common Errors 12+ 0

Token Usage ~15,000 ~6,000

Known Issues This Skill Prevents

• Bus errors from insufficient shared memory allocation

• Green/distorted video from incorrect resolution configuration

• Database locked errors when using network storage for SQLite

• Missing audio in recordings due to default audio stripping

• MQTT connection failures from using localhost in Docker

• Coral TPU not detected due to missing device passthrough

• High CPU usage from missing hardware acceleration

• False positives from missing motion masks on timestamps

• No alerts triggered due to misconfigured required_zones

• Recording corruption from h265 streams without transcoding

• go2rtc WebRTC failures from missing STUN configuration

• Object detection misses from wrong detect stream resolution

Quick Start

Step 1: Create Minimal Configuration

mqtt: enabled: false

cameras: front_door: ffmpeg: inputs: - path: rtsp://user:pass@192.168.1.100:554/stream1 roles: - detect detect: width: 1280 height: 720 fps: 5

Why this matters: Start with the absolute minimum to verify camera connectivity before adding complexity. Frigate requires explicit detect stream role assignment.

Step 2: Add Hardware-Accelerated Detector

detectors: coral: type: edgetpu device: usb

OR for Intel with OpenVINO:

detectors: ov: type: openvino device: GPU

Why this matters: CPU detection is not recommended for production. Even a single USB Coral TPU dramatically reduces CPU usage and improves detection latency.

Step 3: Enable Recording with Retention

record: enabled: true retain: days: 1 mode: motion alerts: retain: days: 14 detections: retain: days: 7

cameras: front_door: ffmpeg: inputs: - path: rtsp://user:pass@192.168.1.100:554/stream1 roles: - detect - path: rtsp://user:pass@192.168.1.100:554/stream2 roles: - record

Why this matters: Use separate streams for detect (low-res) and record (high-res) to optimize performance. Retention modes prevent storage from filling up.

Critical Rules

Always Do

• Use width and height that match your camera's ACTUAL resolution (verify with VLC)

• Set detect fps between 5-10 (higher wastes resources, lower misses events)

• Use separate streams for detect (sub-stream) and record (main stream)

• Allocate adequate shm-size in Docker (64MB minimum per camera)

• Create motion masks for timestamp overlays and areas with constant motion

• Use environment variables for credentials: {FRIGATE_RTSP_PASSWORD}

• Test RTSP URLs in VLC first before adding to Frigate config

Never Do

• Never use localhost or 127.0.0.1 for MQTT inside Docker containers

• Never set detect resolution higher than 1280x720 (wastes detector capacity)

• Never enable recording without specifying retention policy

• Never mount /media/frigate on network storage without relocating database

• Never mix multiple detector types for object detection (e.g., Coral + OpenVINO)

• Never use UDP RTSP transport without explicit configuration (TCP is default)

Common Mistakes

Wrong:

cameras: cam1: ffmpeg: inputs: - path: rtsp://192.168.1.100/stream roles: - detect - record detect: width: 1920 height: 1080 fps: 30

Correct:

cameras: cam1: ffmpeg: inputs: - path: rtsp://192.168.1.100/substream roles: - detect - path: rtsp://192.168.1.100/mainstream roles: - record detect: width: 1280 height: 720 fps: 5

Why: Using 1080p@30fps for detection wastes resources. Detection works best at 720p or lower at 5fps. Always use the camera's sub-stream for detection and main stream for recording.

Known Issues Prevention

Issue Root Cause Solution

Bus Error Insufficient shared memory Set shm-size: 256mb in docker-compose

Database Locked SQLite on network storage Use database.path: /config/frigate.db

Green/Distorted Video Wrong resolution in config Match camera's actual output resolution

No Audio in Recordings Default audio removal Use preset-record-generic-audio-aac

MQTT Connection Failed localhost in Docker Use host IP address instead

Coral Not Detected Missing device passthrough Add /dev/bus/usb to Docker devices

High CPU Usage Missing hwaccel Add appropriate preset (vaapi/qsv/nvidia)

Missing Alerts No required_zones Configure zones with review.alerts.required_zones

UDP Stream Failures TCP is default in Frigate Add preset-rtsp-udp to input args

Configuration Reference

config.yml Structure

MQTT Configuration (optional but recommended)

mqtt: enabled: true host: 192.168.1.50 port: 1883 user: "{FRIGATE_MQTT_USER}" password: "{FRIGATE_MQTT_PASSWORD}"

Detector Configuration

detectors: coral: type: edgetpu device: usb # or pci for M.2/PCIe

Global Object Settings

objects: track: - person - car - dog - cat filters: person: min_area: 5000 max_area: 100000 threshold: 0.7

Recording Settings

record: enabled: true retain: days: 1 mode: motion alerts: retain: days: 14 detections: retain: days: 7

Snapshot Settings

snapshots: enabled: true retain: default: 7

Camera Configuration

cameras: front_door: enabled: true ffmpeg: inputs: - path: "rtsp://{FRIGATE_RTSP_USER}:{FRIGATE_RTSP_PASSWORD}@192.168.1.100:554/stream1" input_args: preset-rtsp-restream roles: - detect - path: "rtsp://{FRIGATE_RTSP_USER}:{FRIGATE_RTSP_PASSWORD}@192.168.1.100:554/stream0" input_args: preset-rtsp-restream roles: - record output_args: record: preset-record-generic-audio-aac detect: width: 1280 height: 720 fps: 5 motion: mask: - 0,0,200,0,200,100,0,100 # Timestamp area zones: front_yard: coordinates: 100,500,400,500,400,720,100,720 objects: - person - car review: alerts: required_zones: - front_yard

Key settings:

• detect.fps : 5 is optimal for most cameras (reduces detector load)

• detect.width/height : Must match actual camera sub-stream resolution

• record.retain.mode : Use motion or active_objects to save storage

• motion.mask : Define polygons as comma-separated coordinates

• zones.coordinates : Bottom-center of bounding box determines zone presence

Hardware Acceleration Presets

Intel (6th Gen+)

For Intel gen8+ (prefer QSV)

ffmpeg: hwaccel_args: preset-intel-qsv-h264 # or preset-intel-qsv-h265

For Intel gen1-gen7 (use VAAPI)

ffmpeg: hwaccel_args: preset-vaapi

NVIDIA GPU

ffmpeg: hwaccel_args: preset-nvidia

Requires NVIDIA Container Toolkit:

docker-compose.yml

services: frigate: runtime: nvidia environment: - NVIDIA_VISIBLE_DEVICES=all

AMD GPU

ffmpeg: hwaccel_args: preset-vaapi

docker-compose.yml

environment:

• LIBVA_DRIVER_NAME=radeonsi

Raspberry Pi

Raspberry Pi 4/5

ffmpeg: hwaccel_args: preset-rpi-64-h264 # or preset-rpi-64-h265

Requires: gpu_mem=128 in /boot/config.txt and device mapping in Docker.

Object Detector Types

USB Coral TPU

detectors: coral: type: edgetpu device: usb # Single USB Coral # device: usb:0 # First of multiple USB Corals

Docker device mapping:

devices:

• /dev/bus/usb:/dev/bus/usb

M.2/PCIe Coral TPU

detectors: coral: type: edgetpu device: pci # device: pci:0 # First of multiple PCIe Corals

OpenVINO (Intel)

detectors: ov: type: openvino device: GPU # or CPU

model: path: /openvino-model/ssdlite_mobilenet_v2.xml width: 300 height: 300

ONNX (Multi-GPU)

detectors: onnx: type: onnx # Automatically uses: ROCm (AMD), OpenVINO (Intel), TensorRT (NVIDIA)

Advanced Features

Zone-Based Speed Estimation

zones: driveway: coordinates: 100,500,400,500,400,720,100,720 distances: - "100,500|400,500|20ft" # 20 feet between points speed: threshold: 15 # Minimum mph to register

Audio Detection

audio: enabled: true listen: - bark - fire_alarm - scream - speech

cameras: front_door: ffmpeg: inputs: - path: rtsp://camera/stream roles: - audio

GenAI Event Descriptions

genai: enabled: true provider: ollama base_url: http://192.168.1.100:11434 model: llava

Face Recognition (Frigate+)

face_recognition: enabled: true threshold: 0.6

cameras: front_door: detect: width: 1280 # Higher res improves face detection

License Plate Recognition

lpr: enabled: true

cameras: driveway: lpr: enabled: true

go2rtc Integration

go2rtc: streams: front_door: - rtsp://user:pass@192.168.1.100:554/stream1 - "ffmpeg:front_door#video=copy#audio=opus" webrtc: candidates: - 192.168.1.50:8555 - stun:8555

Docker Compose Template

services: frigate: container_name: frigate image: ghcr.io/blakeblackshear/frigate:stable restart: unless-stopped shm_size: "256mb" devices: - /dev/bus/usb:/dev/bus/usb # USB Coral - /dev/dri/renderD128:/dev/dri/renderD128 # Intel GPU volumes: - ./config:/config - ./storage:/media/frigate - type: tmpfs target: /tmp/cache tmpfs: size: 1000000000 ports: - "8971:8971" # Web UI - "8554:8554" # RTSP feeds - "8555:8555/tcp" # WebRTC - "8555:8555/udp" # WebRTC environment: FRIGATE_RTSP_USER: admin FRIGATE_RTSP_PASSWORD: ${RTSP_PASSWORD} FRIGATE_MQTT_USER: frigate FRIGATE_MQTT_PASSWORD: ${MQTT_PASSWORD}

Bundled Resources

Templates

Located in templates/ :

• docker-compose.yml

• Production-ready compose file

• config-minimal.yml

• Minimal starter config

• config-full.yml

• Full-featured config template

References

Located in references/ :

• detector-comparison.md

• Detector performance comparison

• ffmpeg-presets.md

• All available FFmpeg presets

• mqtt-topics.md

• MQTT topic reference

Scripts

Located in scripts/ :

• validate-config.sh
• Validate config syntax before applying

Dependencies

Required

Package Version Purpose

Docker 20.10+ Container runtime

docker-compose 2.0+ Service orchestration

Optional

Package Version Purpose

NVIDIA Container Toolkit Latest NVIDIA GPU support

Coral Edge TPU runtime Latest Coral TPU support

Official Documentation

• Frigate Documentation

• Configuration Reference

• Getting Started Guide

• Troubleshooting FAQs

Troubleshooting

Camera Shows Offline

Symptoms: Camera fps shows 0, web UI shows offline status

Solution:

Test RTSP URL directly

ffprobe -rtsp_transport tcp "rtsp://user:pass@ip:554/stream"

Check Docker logs

docker logs frigate 2>&1 | grep -i "camera_name"

High CPU Usage

Symptoms: CPU consistently above 80%, system becomes unresponsive

Solution:

• Enable hardware acceleration (see presets above)

• Reduce detect fps from 10 to 5

• Lower detect resolution to 720p or below

• Add Coral TPU for object detection

No Objects Detected

Symptoms: Motion detected but no object events created

Solution:

• Verify detector is configured and running: check /api/stats

• Check object filters aren't too restrictive (min_area, threshold)

• Ensure detect stream resolution is correct

• Verify objects list includes desired types

Recording Not Working

Symptoms: Events show but no recordings available

Solution:

Ensure record role is assigned

cameras: cam1: ffmpeg: inputs: - path: rtsp://camera/stream roles: - record # Must be explicitly set record: enabled: true # Must be true

Setup Checklist

Before deploying Frigate, verify:

• Docker and docker-compose installed

• RTSP URLs tested in VLC (note actual resolution)

• Camera credentials ready for environment variables

• Storage volume has adequate space (100GB+ recommended)

• Shared memory size configured (64MB per camera minimum)

• Hardware acceleration device mapped (if applicable)

• Coral TPU device mapped (if using)

• MQTT broker accessible (if integrating with Home Assistant)

• Port 8971 available for web UI

• Firewall allows required ports (8554, 8555 for streaming)