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call out avx2 requirement (#22305)

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Josh Hawkins
2026-03-07 06:18:17 -07:00
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parent ab3cef813c
commit d1f3a807d3
7 changed files with 7 additions and 16 deletions
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docs/docs/configuration/license_plate_recognition.md
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@@ -30,7 +30,7 @@ In the default mode, Frigate's LPR needs to first detect a `car` or `motorcycle`
## Minimum System Requirements
License plate recognition works by running AI models locally on your system. The YOLOv9 plate detector model and the OCR models ([PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR)) are relatively lightweight and can run on your CPU or GPU, depending on your configuration. At least 4GB of RAM and a CPU with AVX instructions is required.
License plate recognition works by running AI models locally on your system. The YOLOv9 plate detector model and the OCR models ([PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR)) are relatively lightweight and can run on your CPU or GPU, depending on your configuration. At least 4GB of RAM and a CPU with AVX + AVX2 instructions is required.
## Configuration
@@ -375,7 +375,6 @@ Use `match_distance` to allow small character mismatches. Alternatively, define
Start with ["Why isn't my license plate being detected and recognized?"](#why-isnt-my-license-plate-being-detected-and-recognized). If you are still having issues, work through these steps.
1. Start with a simplified LPR config.
- Remove or comment out everything in your LPR config, including `min_area`, `min_plate_length`, `format`, `known_plates`, or `enhancement` values so that the only values left are `enabled` and `debug_save_plates`. This will run LPR with Frigate's default values.
```yaml
@@ -386,7 +385,6 @@ Start with ["Why isn't my license plate being detected and recognized?"](#why-is
```
2. Enable debug logs to see exactly what Frigate is doing.
- Enable debug logs for LPR by adding `frigate.data_processing.common.license_plate: debug` to your `logger` configuration. These logs are _very_ verbose, so only keep this enabled when necessary. Restart Frigate after this change.
```yaml
@@ -399,18 +397,15 @@ Start with ["Why isn't my license plate being detected and recognized?"](#why-is
3. Ensure your plates are being _detected_.
If you are using a Frigate+ or `license_plate` detecting model:
- Watch the debug view (Settings --> Debug) to ensure that `license_plate` is being detected.
- View MQTT messages for `frigate/events` to verify detected plates.
- You may need to adjust your `min_score` and/or `threshold` for the `license_plate` object if your plates are not being detected.
If you are **not** using a Frigate+ or `license_plate` detecting model:
- Watch the debug logs for messages from the YOLOv9 plate detector.
- You may need to adjust your `detection_threshold` if your plates are not being detected.
4. Ensure the characters on detected plates are being _recognized_.
- Enable `debug_save_plates` to save images of detected text on plates to the clips directory (`/media/frigate/clips/lpr`). Ensure these images are readable and the text is clear.
- Watch the debug view to see plates recognized in real-time. For non-dedicated LPR cameras, the `car` or `motorcycle` label will change to the recognized plate when LPR is enabled and working.
- Adjust `recognition_threshold` settings per the suggestions [above](#advanced-configuration).