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LPR improvements (#16559)

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* use a small yolov9 model for detection

* use yolov9 for users without frigate+ and update retention algorithm

* new lpr config fields

* levenshtein distance package

* tweaks

* docs
This commit is contained in:
Josh Hawkins
2025-02-13 16:08:56 -07:00
committed by GitHub
parent f7199f205f
commit 729f5c0833
5 changed files with 297 additions and 49 deletions
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docs/docs/configuration/license_plate_recognition.md
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@@ -24,14 +24,20 @@ lpr:
## Advanced Configuration
Several options are available to fine-tune the LPR feature. For example, you can adjust the `min_area` setting, which defines the minimum size in pixels a license plate must be before LPR runs. The default is 500 pixels.
Several options are available to fine-tune the LPR feature. For example, you can adjust the `min_area` setting, which defines the minimum size in pixels a license plate must be before LPR runs. The default is 1000 pixels.
The `min_plate_length` field specifies the minimum number of characters a license plate must have to be added to the object as a sub label.
If you want to allow a number of number of missing/incorrect characters to still cause a detected plate to match a known plate, set the `match_distance` field. For example, setting `match_distance` to 1 would cause a detected plate of ABCDE to match ABCBE or ABCD.
Additionally, you can define `known_plates` as strings or regular expressions, allowing Frigate to label tracked vehicles with custom sub_labels when a recognized plate is detected. This information is then accessible in the UI, filters, and notifications.
```yaml
lpr:
enabled: true
min_area: 500
min_area: 1500
min_plate_length: 4
match_distance: 1
known_plates:
Wife's Car:
- "ABC-1234"