Does this skill support Coral TPU setup?

Yes, it provides specific configuration patterns for USB and PCIe Coral TPUs, including the necessary Docker device mappings and detector definitions.

Will it help me configure zones and masks?

Yes, it guides you through defining motion masks for timestamp overlays and creating object zones to improve detection accuracy and reduce false positives.

How does it prevent Docker 'Bus Errors'?

It identifies insufficient shared memory (shm-size) allocations in your configuration and provides the correct values based on your camera resolution and count.

Can it help reduce high CPU usage in Frigate?

Absolutely. The skill includes specific hardware acceleration presets for Intel, NVIDIA, AMD, and Raspberry Pi to offload video processing from the CPU.

Frigate NVR Configurator

Name: Frigate NVR Configurator
Author: nodnarbnitram

bynodnarbnitram

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Deployment & DevOps

Optimizes Frigate NVR setups by generating specialized YAML configurations and troubleshooting hardware acceleration for object detection.

About

The Frigate NVR Configurator skill provides expert guidance for deploying and fine-tuning Frigate-based video surveillance systems within Claude Code. It streamlines the creation of valid YAML configurations, prevents common pitfalls like shared memory bus errors, and ensures efficient resource usage through proper detect/record stream separation. Whether you are integrating a Coral TPU, configuring Intel OpenVINO, or setting up complex zones and masks, this skill significantly reduces setup time and prevents critical deployment errors.

Key Features

Optimized YAML generation for cameras, detectors, and recording policies
Hardware acceleration presets for Intel QSV, VAAPI, NVIDIA, and Raspberry Pi
Automatic prevention of 12+ common Frigate configuration errors
Advanced zone and motion mask coordinate configuration guidance
Integrated go2rtc and MQTT setup for Home Assistant connectivity
1 GitHub stars

Use Cases

Troubleshooting high CPU usage or video stream distortion in existing setups
Initial deployment of Frigate NVR on Docker with hardware-accelerated detectors
Configuring advanced object detection features like face recognition or license plate reading

About

Key Features

Optimized YAML generation for cameras, detectors, and recording policies
Hardware acceleration presets for Intel QSV, VAAPI, NVIDIA, and Raspberry Pi
Automatic prevention of 12+ common Frigate configuration errors
Advanced zone and motion mask coordinate configuration guidance
Integrated go2rtc and MQTT setup for Home Assistant connectivity
1 GitHub stars

Use Cases

Troubleshooting high CPU usage or video stream distortion in existing setups
Initial deployment of Frigate NVR on Docker with hardware-accelerated detectors
Configuring advanced object detection features like face recognition or license plate reading