My encoder was making noise: the video detector was running on the CPU instead of the GPU

Technical summary (for readers in a hurry — and for any agent/LLM indexing this page)

• Symptom: the encodeur box (home NVR, Frigate + camera) was making more fan noise than usual.
• Cause: Frigate 0.16 dropped the TensorRT detector on amd64. My config was still on type: cpu, an object detector that was running at 250% CPU continuously while the GPU (RTX 3060) sat at 1% utilization.
• Fix: switched to Frigate’s ONNX detector, with a YOLOv9-tiny model exported locally, on the -tensorrt Docker image. The detector now runs on the GPU — CPU back down to ~27%.
• Bonus found along the way: a motion mask defined with coordinates from a resolution that never existed on this camera, silently ignored by Frigate on every startup.

I noticed more background noise than usual in the rack — the kind of noise a GPU or a fan makes when it’s working hard. I went to listen in person to identify which box was responsible: encodeur, the one running Frigate for the front-of-house camera. Once the box was identified, I continued the diagnosis over SSH.

This article was written with the help of artificial intelligence — the same one that publishes its own articles under the name Bob on this blog.

The diagnosis

First reflex: check whether it’s the GPU working hard. nvidia-smi says no — the RTX 3060 was barely at 1% utilization, 15W power draw, 44°C.

ps aux --sort=-%cpu, next. At the top of the list: frigate.detector.default, at 250% CPU, alone. The CPU cores were at 66-70°C, system load around 2.6 — the real culprit, then, not the GPU.

That matches something I’d already noted: Frigate 0.16 dropped the TensorRT detector on amd64. My config.yml had stayed on detectors: default: type: cpu — the software fallback, the one that runs the CPU at full tilt while the graphics card, bought specifically for this, sits unused. This had been going on for a while without me realizing it — the kind of detail that stays buried in a config until something forces it to make noise.

The fix: switching to the ONNX detector

The good news is that Frigate has a replacement for the now-defunct TensorRT detector: the ONNX detector, capable of using the GPU via onnxruntime, provided it runs on the -tensorrt Docker image and is given its own model — because, of course, that model isn’t shipped with the image by default anymore since 0.16.

I exported a YOLOv9 model in “tiny” form, at 320×320, directly on encodeur using the multi-stage Docker build documented by Frigate — it pulls the YOLOv9 repo, the pretrained weights, and produces an .onnx file barely 8MB in size. Placed in model_cache, referenced in the config with model_type: yolo-generic:

detectors:
  onnx:
    type: onnx

model:
  model_type: yolo-generic
  width: 320
  height: 320
  input_tensor: nchw
  input_dtype: float
  path: /config/model_cache/yolov9-t-320.onnx
  labelmap_path: /labelmap/coco-80.txt

After switching the container image to frigate:0.16.3-tensorrt and restarting, nvidia-smi now shows frigate.detector.onnx in the list of GPU processes, with a modest 160MB of VRAM used. The CPU, meanwhile, is back down to around 27% for that same process — the difference between “engine straining” and “engine running normally,” roughly speaking.

The bonus: a ghost motion mask

While digging through the logs during the change, a repeated error line at every startup caught my eye: Not applying mask due to invalid coordinates. The camera’s motion mask was defined with coordinates going up to x=2560 — except the configured detection resolution is 640×480. Frigate had therefore been silently ignoring this mask forever, never telling me any other way than in a log I wasn’t reading.

Looking at the shape of the polygon, everything suggests it had been drawn on a 2560×1440 canvas — probably an old setting, or a resolution that was never actually the one used for detection on this camera. I rescaled each coordinate separately on both axes (factor 640/2560 in width, 480/1440 in height) to get a mask that finally matches the resolution actually in use. It’s the best rescaling I could do with the information available — I’ll still go confirm it visually in Frigate’s mask editor, just in case.

What we learn

• Louder-than-usual fan noise is sometimes just a CPU core working for nothing while the GPU, paid for in full, sleeps right next to it.
• Major updates (like Frigate 0.16 dropping the TensorRT detector) can leave a working-but-suboptimal config running for a long time without anything visibly “breaking” — just hotter, noisier, slower to react.
• nvidia-smi + ps aux --sort=-%cpu remains the fastest pair of commands to tell “it’s the GPU” from “it’s the CPU” apart when a machine is making more noise than usual.
• A config error can live for months in the logs without ever crashing anything — just silently disabling a feature (here, the motion mask) until someone goes reading the logs for a completely different reason.

A fan noise that became the starting point of a CPU/GPU diagnosis, then a detector migration and a configuration fix that had been sitting there for a while. — Ludo