scorevision: push artifact

miner.py

@@ -27,27 +27,21 @@ class TVFrameResult(BaseModel):
     keypoints: list[tuple[int, int]] | None = None
 
 
-# Element: manak0/Detect-fire — objects order: 0=fire, 1=smoke, 2=fire extinguisher.
-# Model trained with identical class order; ids pass through unmapped.
-# Tuned by replicating the element's own scorer
-# (0.6*mAP50 + 0.4*(1-FP_per_image/10)) across a threshold sweep on held-out
-# data. For the 3-class v2 model 0.10 maximised composite (0.782); below that
-# false positives grow faster than recall, above it mAP drops off sharply.
-CONF_THRESHOLD = 0.10
+# Element: manak0/Detect-road-signs — objects: ["road sign"] (single class, id 0).
+# Trained on LVIS street_sign + signboard + stop_sign, all mapped to class 0.
+# CONF_THRESHOLD is set by the sweep that replicates the element's own scorer
+# (0.6*mAP50 + 0.4*(1 - FP_per_image/10)).
+CONF_THRESHOLD = 0.40
 IMGSZ = 1280  # matches element preproc resize_long
 
 
 class Miner:
     def __init__(self, path_hf_repo: Path) -> None:
-        self.model = YOLO(str(path_hf_repo / "fire-detection.pt"))
-        try:
-            self.half = self.model.device is not None and "cuda" in str(self.model.device)
-        except Exception:
-            self.half = False
-        print("✅ Fire/Smoke/Extinguisher model loaded")
+        self.model = YOLO(str(path_hf_repo / "road-sign-detection.pt"))
+        print("✅ Road-sign model loaded")
 
     def __repr__(self) -> str:
-        return f"Detect-fire miner: {type(self.model).__name__} @ imgsz={IMGSZ}, conf={CONF_THRESHOLD}"
+        return f"Detect-road-signs miner: {type(self.model).__name__} @ imgsz={IMGSZ}, conf={CONF_THRESHOLD}"
 
     def predict_batch(
         self,
@@ -70,12 +64,8 @@ class Miner:
                     x1, y1, x2, y2, conf, cls_id = box.tolist()
                     boxes.append(
                         BoundingBox(
-                            x1=int(x1),
-                            y1=int(y1),
-                            x2=int(x2),
-                            y2=int(y2),
-                            cls_id=int(cls_id),
-                            conf=float(conf),
+                            x1=int(x1), y1=int(y1), x2=int(x2), y2=int(y2),
+                            cls_id=int(cls_id), conf=float(conf),
                         )
                     )
             out.append(TVFrameResult(frame_id=offset + i, boxes=boxes))