Problem

The plate detector runs at YOLO size=640, so the whole frame is resized to 640px wide before detection. On wide-angle or high-resolution (e.g. 4K) cameras a license plate is a small part of the scene and, after that resize, can shrink to ~10px — too small to detect — even though it is perfectly legible in the source image. The module then returns "No plates found" on cameras that clearly show plates.

Example: a ~60px-wide plate in a 3840×2160 frame becomes ~10px after the 640 resize. (Commonly hit when Blue Iris / Frigate / Agent-DVR send full-resolution frames, but this is a general high-resolution-scene issue, not vendor-specific.)

Fix

Two-pass detection in ALPR.py:

1. Detect plates on the full frame — unchanged fast path.
2. If that finds nothing, run general object detection for vehicles, crop each car / truck / bus / motorcycle (with padding plus an extra lower/front-of-vehicle crop), and run the plate detector on those crops. Plate boxes are translated back to full-frame coordinates, de-duplicated by IoU, and then OCR'd exactly as before.

Because a crop is a small region of the original image, the plate keeps its pixels through the 640 resize and detects normally. Well-presented full-frame plates still take the original fast path — the fallback only runs on a miss.

Tuning (constants near the top of ALPR.py)

• vehicle_confidence (0.25) — minimum confidence to treat a detection as a vehicle
• max_vehicle_crops (8) — cap on vehicles cropped per frame (bounds worst-case latency)
• vehicle_labels — object classes to crop

Cost

A miss adds one object-detection pass plus up to max_vehicle_crops × 2 plate passes, so a fallback read is slower than a direct hit (~1s vs ~150ms on our hardware). Direct hits are unaffected.

Testing

• python3 -m py_compile ALPR.py, git diff --check
• Validated live against real 4K frames that previously returned nothing: they now read — localization succeeds on the crop, OCR path unchanged.