lpr docs tweaks

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Josh Hawkins 2026-01-16 06:57:44 -06:00
parent f428a64948
commit dcff06906c

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@ -68,8 +68,8 @@ Fine-tune the LPR feature using these optional parameters at the global level of
- Default: `1000` pixels. Note: this is intentionally set very low as it is an _area_ measurement (length x width). For reference, 1000 pixels represents a ~32x32 pixel square in your camera image.
- Depending on the resolution of your camera's `detect` stream, you can increase this value to ignore small or distant plates.
- **`device`**: Device to use to run license plate detection _and_ recognition models.
- Default: `CPU`
- This can be `CPU`, `GPU`, or the GPU's device number. For users without a model that detects license plates natively, using a GPU may increase performance of the YOLOv9 license plate detector model. See the [Hardware Accelerated Enrichments](/configuration/hardware_acceleration_enrichments.md) documentation. However, for users who run a model that detects `license_plate` natively, there is little to no performance gain reported with running LPR on GPU compared to the CPU.
- Default: `None`
- This is auto-selected by Frigate and can be `CPU`, `GPU`, or the GPU's device number. For users without a model that detects license plates natively, using a GPU may increase performance of the YOLOv9 license plate detector model. See the [Hardware Accelerated Enrichments](/configuration/hardware_acceleration_enrichments.md) documentation. However, for users who run a model that detects `license_plate` natively, there is little to no performance gain reported with running LPR on GPU compared to the CPU.
- **`model_size`**: The size of the model used to identify regions of text on plates.
- Default: `small`
- This can be `small` or `large`.
@ -432,6 +432,6 @@ If you are using a model that natively detects `license_plate`, add an _object m
If you are not using a model that natively detects `license_plate` or you are using dedicated LPR camera mode, only a _motion mask_ over your text is required.
### I see "Error running ... model" in my logs. How can I fix this?
### I see "Error running ... model" in my logs, or my inference time is very high. How can I fix this?
This usually happens when your GPU is unable to compile or use one of the LPR models. Set your `device` to `CPU` and try again. GPU acceleration only provides a slight performance increase, and the models are lightweight enough to run without issue on most CPUs.