HomeTechOps

Cameras

Frigate hardware planner

See how many cameras a detector (Coral, Hailo, Intel, Nvidia) can handle at your detection fps.

Use this to right-size a Frigate detector: it applies Frigate's own cameras ≈ (1000 ÷ inference_ms) ÷ detect_fps capacity model and flags when you're over capacity.

Low priority

Hailo-8L can handle this — up to ~13 cameras at 5 fps

At ~11 ms inference, Hailo-8L sustains about 68 detections/sec (75% derated). 6 cameras × 5 fps = 30 detections/sec, so this is within capacity.

Detector capacity
68 det/s

~11 ms inference, derated 75%

Your load
30 det/s

6 × 5 fps

Max cameras
13

at 5 fps each

Verdict
Within capacity

First checks

  • Detector: Hailo-8L (~11 ms inference).
  • Load: 6 cameras × 5 fps detection = 30 detections/sec.
  • Inference numbers are model-specific (ssd-mobilenet / yolov6n class) — measure your own in Frigate's stats for accuracy.

Step-by-step troubleshooting

  1. 1

    Confirm your detector and inference time

    Check Frigate's stats for the actual inference speed (ms) of your detector + model.

    Expected: A measured inference time instead of a table estimate.

    Next: Enter it in the override field and re-run.

  2. 2

    Plan decode separately from detection

    Ensure the host has hardware video decode (iGPU/GPU) for all camera streams.

    Expected: Decode and detection both have headroom.

    Next: If detection is over capacity, lower fps or upgrade the detector.

What your answers suggest

  • Capacity = (1000 ÷ 11 ms) × 0.75 ≈ 68 detections/sec.
  • Max cameras ≈ capacity ÷ detect fps = 68 ÷ 5 ≈ 13.

Likely cause area

  • Detection capacity and video DECODE are separate — 4K decode needs an iGPU/GPU (QuickSync/VAAPI/Nvidia), independent of the detector.
  • Run detection on a ~5 fps substream; detecting on the full main stream wastes capacity.

Safe actions

  • You have detector headroom — keep detection on the substream at ~5 fps.
  • Make sure the host can also DECODE all the camera streams (separate from detection).

When to stop

  • Don't run near the theoretical ceiling — real frame-skipping starts before 100% (this figure is already derated to 75%).

Assumptions

  • Inference times are representative 2026 figures and are model- and resolution-specific.
  • Derated to 75% of the theoretical 1000/inference ceiling because real frame-skip starts earlier.
  • Video decode load is separate and not included in this detection estimate.

What should I check first?

  • Pick your detector and check its inference time in Frigate's stats (ms) if you already run it.
  • Set a realistic detection fps per camera (Frigate default is 5; 10 for fast objects).
  • Confirm the host can also DECODE all camera streams — that's separate from detection.

What is likely wrong?

  • Choosing a Coral for a new build — Frigate's docs now list it as no longer recommended.
  • Detecting on the high-res main stream instead of a ~5 fps substream.
  • Forgetting that 4K video decode needs an iGPU/GPU independent of the detector.

What is safe to try?

  • Detect on the substream at ~5 fps to stretch detector capacity.
  • For new builds, prefer a Hailo-8L or an Intel iGPU/Arc over Coral.
  • Lower detection fps or split cameras across two detectors if you're over capacity.

When should I stop?

  • Stop before running near the theoretical ceiling — real frame-skipping starts before 100%.
  • Stop assuming detection capacity covers decode; size 4K decode (QuickSync/VAAPI/Nvidia) separately.

Source-backed checks

HomeTechOps turns official docs and conservative safety rules into a shorter runbook. These links are the source trail for the page direction.