scorevision: push artifact

miner.py

@@ -98,7 +98,11 @@ class Miner:
 
         # Tuning matched to alfred's deployed model — bias toward precision to dodge
         # the false_positive pillar penalty (validator weights FP heavily on this element).
-        self.conf_thres = 0.40
+        # v13 sweet spot on starter (true GT): uniform conf=0.50.
+        # Tuning per-class on 7 images overfits — leave-one-out CV showed it
+        # collapsed to 0.314 on held-out shards. Uniform 0.50 is robust.
+        self.conf_thres = 0.50
+        self.conf_thres_per_class = np.array([0.50] * 6, dtype=np.float32)
         self.iou_thres = 0.4
         self.cross_iou_thresh = 0.7
         self.max_det = 100
@@ -359,7 +363,11 @@ class Miner:
         cls_ids = self.cls_remap[cls_ids]
 
         if apply_conf_thresh:
-            keep = scores >= self.conf_thres
+            # Per-class threshold: each box compared against its own class's threshold
+            cls_thresh = np.full(len(scores), self.conf_thres, dtype=np.float32)
+            valid_cls = (cls_ids >= 0) & (cls_ids < len(self.conf_thres_per_class))
+            cls_thresh[valid_cls] = self.conf_thres_per_class[cls_ids[valid_cls]]
+            keep = scores >= cls_thresh
             boxes = boxes[keep]
             scores = scores[keep]
             cls_ids = cls_ids[keep]