Raise configured YOLO max detections

2026-07-09 10:14:07 +02:00
parent 9bef905da8
commit 25f098bde0
16 changed files with 82 additions and 1 deletions
@@ -110,9 +110,11 @@ This file now starts with the current implementation status. Older preparation/b
 - [x] Benchmark an external remote-sensing YOLOv8l building candidate as an explicit local model asset.
 - [x] Train and gate the `uniquehardneg160e50` YOLOv8s candidate through 7 positive AOIs and 9 hard-negative/background samples.
 - [x] Train and gate an AOI-scale `aoi512e80` YOLOv8s candidate to test the 160px training-scale hypothesis.
+- [x] Raise configured-YOLO `max_det` through `YOLO_MAX_DETECTIONS` so dense AOIs are not capped at 300 detections before QA/QC.
 - [ ] Find or train a materially stronger aerial/Kempen building model candidate; `geointel-building-yolov8n-expanded160e50-pt` is the best current dense-AOI candidate but still too weak and too noisy for a V1 default.
 - [ ] Train a higher-capacity local aerial-building detector with stronger positive recall while preserving the hard-negative false-positive gate.
 - [ ] Add more diverse positive AOIs and revisit geometry-to-box label strategy before the next default-model training attempt.
+- [ ] Rerun live dense-AOI calibration after redeploy with `YOLO_MAX_DETECTIONS=1000` to measure uncapped recall and false-positive pressure.

 ## Sprint 8 status