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miner.py

@@ -37,7 +37,7 @@ class Miner:
         #   balaclava=0, hoodie=1, glove=2, bat=3, spray paint=4, graffiti=5
         self.class_names = ['balaclava', 'hoodie', 'glove', 'bat', 'spray paint', 'graffiti']
         # ONNX class index order from training export (Ultralytics names 0..5 in dataset.yaml).
-        model_class_order = ['balaclava', 'hoodie', 'glove', 'bat', 'spray paint', 'graffiti']
+        model_class_order = ['balaclava', 'bat', 'glove', 'graffiti', 'hoodie', 'spray paint']
         self._train_cls_to_canonical = np.array(
             [self.class_names.index(n) for n in model_class_order],
             dtype=np.int32
@@ -94,19 +94,19 @@ class Miner:
         self.conf_thres = 0.25
 
         # Above this on orig view, accept directly. Below it, require TTA agreement.
-        self.conf_high = 0.35
+        self.conf_high = 0.45
 
         # Standard NMS IoU; balaclavas / hoodies on the same person can
         # overlap heavily but they're different classes so the per-class
         # NMS handles that — 0.50 stays a safe default.
-        self.iou_thres = 0.35
+        self.iou_thres = 0.5
 
         # Balaclavas / hoodies barely shift between orig and h-flipped views,
         # but graffiti and bats can have asymmetric extents so a moderate
         # IoU gate keeps the consensus rule from getting too strict.
-        self.tta_match_iou = 0.15
+        self.tta_match_iou = 0.25
 
-        self.max_det = 150
+        self.max_det = 50
         self.use_tta = True
 
         # Box sanity filters tuned for crime:
@@ -116,11 +116,11 @@ class Miner:
         #   graffiti can be very wide; allow up to 8.0
         # - a single graffiti tag can fill most of a wall, so allow up to
         #   ~95% image-area for one box
-        self.min_box_area = 10 * 10
-        self.min_w = 6
-        self.min_h = 6
+        self.min_box_area = 64 * 64
+        self.min_w = 16
+        self.min_h = 16
         self.max_aspect_ratio = 8.0
-        self.max_box_area_ratio = 0.95
+        self.max_box_area_ratio = 0.9
 
         print(f"✅ ONNX model loaded from: {model_path}")
         print(f"✅ ONNX providers: {self.session.get_providers()}")
@@ -536,7 +536,6 @@ class Miner:
         - any box with conf >= conf_high
         - low/medium-conf boxes only if confirmed across TTA views
         Then run final hard NMS.
-
         All thresholds default to the instance attributes when not supplied,
         so the non-sweep path can call this without args. The sweep path
         passes explicit values to avoid mutating shared state across

weights.onnx

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:97d6a4c1a6ec630ce8cf98d507b4838a3616592fa431e55533aaea19876c64b9
-size 19409709
+oid sha256:f672a170aa69723924770fbd6013c44ddc8139ef1d609c29a280a59aa7b57090
+size 19409603