Adds call_platerecognizer() to lpr.py which sends frames to the
PlateRecognizer cloud API (regions=fr) with a 1920px cap to stay
within API limits. In watcher.py, switches to a two-pass frame
scoring strategy: Laplacian sharpness on all frames first, then
YOLO only on the top-10 sharpest frames, then PlateRecognizer on
the top-3 by score. Falls back to local YOLO+Tesseract/PaddleOCR
if the API returns no result.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Delete event: POST /event/{id}/delete removes DB row + files
- Perspective correction: minAreaRect on white plate region → getPerspectiveTransform
gives a flat frontal view of the plate (e.g. 'GR B38 WR' instead of trapezoid)
- Tesseract now scales image 3x before OCR and skips EU blue strip (left 11%)
- Saves plate_ocr.jpg (perspective-corrected + enhanced crop actually fed to OCR)
- Event detail shows both raw detection crop and OCR crop side by side
- Manual plate edit form in event detail
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Tiled YOLO (3x2, 20% overlap): plate confidence 0.307 -> 0.838 on test frame
- Aspect ratio filter (2.0-6.5:1): rejects non-plate shapes
- Confidence threshold 0.03 -> 0.04: removes fence/noise false positives
- Exclude top 15% (sky) and bottom 8% (timestamp overlay) from detection zone
- Add Tesseract as primary OCR (better for Latin plates), PaddleOCR as fallback
- Enhance plate crop before OCR: CLAHE + sharpening + min 80px upscale
- Save plate_crop.jpg (4x upscaled) to event dir for manual review
- Show plate crop in event detail page
- Add manual plate edit form in event detail (POST /event/{id}/plate)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Couleur : crop autour de la plaque (zone carrosserie au-dessus) au lieu du frame entier ; fallback center 50% si pas de plaque
- lpr.read_plate() retourne maintenant (text, conf, bbox) pour exposer la position de la plaque
- Index : supprime filtre caméra et badge caméra (une seule caméra)
- Carte index : badge ▶ clip si clip disponible
- Page détail : section debug (nb frames, taille clip, id), gestion propre des anciens événements sans clip/frames
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Remplace la source Frigate par l'API GetAiState de la caméra Reolink
- Capture RTSP en temps réel (~20s) quand véhicule détecté, garde la meilleure frame
- LPR avec YOLOv9 (détection plaque) + PaddleOCR v4 (lecture texte) via ONNX
- Modèles partagés avec Frigate (volume local ./models/)
- Cooldown 60s entre événements pour éviter les doublons
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
