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Refactor processors and add LPR postprocessing (#16722)

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* recordings data pub/sub

* function to process recording stream frames

* model runner

* lpr model runner

* refactor to mixin class and use model runner

* separate out realtime and post processors

* move model and mixin folders

* basic postprocessor

* clean up

* docs

* postprocessing logic

* clean up

* return none if recordings are disabled

* run postprocessor handle_requests too

* tweak expansion

* add put endpoint

* postprocessor tweaks with endpoint
This commit is contained in:
Josh Hawkins
2025-02-21 07:51:37 -06:00
committed by GitHub
parent e773d63c16
commit 60b34bcfca
16 changed files with 568 additions and 104 deletions
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8
docs/docs/configuration/license_plate_recognition.md
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@@ -41,6 +41,8 @@ lpr:
Ensure that your camera is configured to detect objects of type `car`, and that a car is actually being detected by Frigate. Otherwise, LPR will not run.
Like the other real-time processors in Frigate, license plate recognition runs on the camera stream defined by the `detect` role in your config. To ensure optimal performance, select a suitable resolution for this stream in your camera's firmware that fits your specific scene and requirements.
## Advanced Configuration
Fine-tune the LPR feature using these optional parameters:
@@ -52,7 +54,7 @@ Fine-tune the LPR feature using these optional parameters:
- Note: If you are using a Frigate+ model and you set the `threshold` in your objects config for `license_plate` higher than this value, recognition will never run. It's best to ensure these values match, or this `detection_threshold` is lower than your object config `threshold`.
- **`min_area`**: Defines the minimum size (in pixels) a license plate must be before recognition runs.
- Default: `1000` pixels.
- Depending on the resolution of your cameras, you can increase this value to ignore small or distant plates.
- Depending on the resolution of your camera's `detect` stream, you can increase this value to ignore small or distant plates.
### Recognition
@@ -114,7 +116,7 @@ lpr:
Ensure that:
- Your camera has a clear, well-lit view of the plate.
- The plate is large enough in the image (try adjusting `min_area`).
- The plate is large enough in the image (try adjusting `min_area`) or increasing the resolution of your camera's stream.
- A `car` is detected first, as LPR only runs on recognized vehicles.
If you are using a Frigate+ model or a custom model that detects license plates, ensure that `license_plate` is added to your list of objects to track.
@@ -143,7 +145,7 @@ Use `match_distance` to allow small character mismatches. Alternatively, define
- View MQTT messages for `frigate/events` to verify detected plates.
- Adjust `detection_threshold` and `recognition_threshold` settings.
- If you are using a Frigate+ model or a model that detects license plates, watch the debug view (Settings --> Debug) to ensure that `license_plate` is being detected with a `car`.
- Enable debug logs for LPR by adding `frigate.data_processing.real_time.license_plate_processor: debug` to your `logger` configuration. These logs are _very_ verbose, so only enable this when necessary.
- 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 enable this when necessary.
### Will LPR slow down my system?