scorevision: push artifact

miner.py

@@ -1,5 +1,5 @@
 """
-Score Vision SN44 — Unified miner v3.23.3 (2026-04-07). Diagnostic: vehicle provider logging. Lazy FP32, trigger 0 boxes. TTA consensus (person), parts_confirm on vehicle, car 0.60, VEH_MIN_WH=20.
+Score Vision SN44 — Unified miner v3.24 (2026-04-07). Petrol v4 weights (960px, GDINO+Mapillary), petrol TTA consensus, hard geometric filter, provider logging. Vehicle: lazy FP32, 0-box trigger. Person: TTA consensus.
 Tri-model: vehicle (YOLO11m INT8 1280) + person (YOLO12s FP16 960 TRT) + petrol (end2end 640).
 Pose model: YOLOv8n-pose FP16 640 for false-positive filtering + keypoint box refinement.
 Vehicle weights loaded from secondary HF repo (meaculpitt/ScoreVision-Vehicle).
@@ -378,7 +378,9 @@ VEHICLE_HF_REPO = "meaculpitt/ScoreVision-Vehicle"
 
 # ── Petrol config ───────────────────────────────────────────────────────────
 PETROL_HF_REPO = "meaculpitt/ScoreVision-Petrol"
-PETROL_CONF = 0.25
+PETROL_CONF = 0.30
+PETROL_CONF_ORIG = 0.35
+PETROL_TTA_MATCH_IOU = 0.50
 PETROL_IOU = 0.45
 # Class IDs (petrol model output — independent of person/vehicle cls_ids
 # because element_hint routing ensures only one pipeline runs per challenge)
@@ -391,7 +393,6 @@ PETROL_CANOPY_MIN_ASPECT = 0.8
 PETROL_PUMP_MAX_ASPECT = 4.0
 PETROL_PRICEBOARD_MAX_AREA_FRAC = 0.15
 PETROL_HOSE_MIN_AREA_FRAC = 0.0005
-PETROL_GEOM_PENALTY = 0.10
 # Spatial co-occurrence
 PETROL_COOCCUR_PUMP_CANOPY = 0.05
 PETROL_COOCCUR_PUMP_HOSE = 0.08
@@ -715,7 +716,11 @@ class Miner:
                 and petrol_out_shape[2] == 6
                 and (petrol_out_shape[1] or 0) <= 1000
             )
-            logger.info(f"[init] Petrol model loaded: {petrol_shape}, end2end={self._petrol_end2end}")
+            petrol_actual = self.petrol_session.get_providers()
+            logger.warning(f"[init] Petrol session ACTIVE providers: {petrol_actual}")
+            if "CUDAExecutionProvider" not in petrol_actual:
+                logger.error("[init] ⚠ PETROL IS ON CPU — CUDA EP NOT ACTIVE")
+            logger.info(f"[init] Petrol model loaded: {self.petrol_h}x{self.petrol_w}, end2end={self._petrol_end2end}")
         else:
             self.petrol_session = None
             self._petrol_end2end = False
@@ -2244,7 +2249,7 @@ class Miner:
         return [dets[idx] for idx in kept]
 
     def _petrol_geometric_validate(self, dets, orig_h, orig_w):
-        """Per-class shape filters: aspect ratio + area checks."""
+        """Per-class hard shape filters. Reject detections that fail."""
         img_area = max(orig_h * orig_w, 1)
         result = []
         for x1, y1, x2, y2, conf, cls_id in dets:
@@ -2252,18 +2257,15 @@ class Miner:
             bh = max(y2 - y1, 1)
             aspect = bw / bh
             area_frac = (bw * bh) / img_area
-            penalty = 0.0
             if cls_id == PETROL_CLS_CANOPY and aspect < PETROL_CANOPY_MIN_ASPECT:
-                penalty = PETROL_GEOM_PENALTY
-            elif cls_id == PETROL_CLS_PUMP and aspect > PETROL_PUMP_MAX_ASPECT:
-                penalty = PETROL_GEOM_PENALTY
-            elif cls_id == PETROL_CLS_PRICEBOARD and area_frac > PETROL_PRICEBOARD_MAX_AREA_FRAC:
-                penalty = PETROL_GEOM_PENALTY
-            elif cls_id == PETROL_CLS_HOSE and area_frac < PETROL_HOSE_MIN_AREA_FRAC:
-                penalty = PETROL_GEOM_PENALTY
-            new_conf = max(0.0, conf - penalty)
-            if new_conf >= PETROL_CONF:
-                result.append((x1, y1, x2, y2, new_conf, cls_id))
+                continue
+            if cls_id == PETROL_CLS_PUMP and (aspect > PETROL_PUMP_MAX_ASPECT or bh < 30):
+                continue
+            if cls_id == PETROL_CLS_PRICEBOARD and (area_frac > PETROL_PRICEBOARD_MAX_AREA_FRAC or (bw * bh) < 200):
+                continue
+            if cls_id == PETROL_CLS_HOSE and (bw * bh) < 400:
+                continue
+            result.append((x1, y1, x2, y2, conf, cls_id))
         return result
 
     def _petrol_spatial_cooccurrence(self, dets, orig_h, orig_w):
@@ -2315,28 +2317,77 @@ class Miner:
                 result.append((x1, y1, x2, y2, new_conf, cls_id))
         return result
 
-    def _infer_petrol(self, image_bgr: ndarray) -> list[BoundingBox]:
-        """Full petrol inference pipeline: preprocess → forward → decode → validate → cooccurrence."""
+    def _petrol_run_pass(self, image_bgr):
+        """Single petrol inference pass: preprocess -> forward -> decode."""
         inp, (orig_h, orig_w) = self._petrol_preprocess(image_bgr)
         out = self.petrol_session.run(None, {self.petrol_input_name: inp})[0]
-
         if self._petrol_end2end:
-            dets = self._petrol_decode_end2end(out, orig_h, orig_w)
+            return self._petrol_decode_end2end(out, orig_h, orig_w), orig_h, orig_w
         else:
-            dets = self._petrol_decode_raw(out, orig_h, orig_w)
-        if not dets:
+            return self._petrol_decode_raw(out, orig_h, orig_w), orig_h, orig_w
+
+    def _infer_petrol(self, image_bgr: ndarray) -> list[BoundingBox]:
+        """Petrol inference with flip TTA consensus merging."""
+        if not hasattr(self, '_petrol_providers_logged'):
+            provs = self.petrol_session.get_providers()
+            logger.warning(f"[petrol] First inference — active providers: {provs}")
+            self._petrol_providers_logged = True
+
+        oh, ow = image_bgr.shape[:2]
+
+        # Original pass
+        dets_orig, _, _ = self._petrol_run_pass(image_bgr)
+
+        # Flip pass
+        flipped = cv2.flip(image_bgr, 1)
+        dets_flip, _, _ = self._petrol_run_pass(flipped)
+        # Mirror flip boxes back
+        dets_flip = [(ow - x2, y1, ow - x1, y2, conf, cls_id)
+                     for x1, y1, x2, y2, conf, cls_id in dets_flip]
+
+        # Consensus merge: match across views
+        matched_orig = set()
+        matched_flip = set()
+        merged = []
+
+        for i, (ox1, oy1, ox2, oy2, oc, ocls) in enumerate(dets_orig):
+            for j, (fx1, fy1, fx2, fy2, fc, fcls) in enumerate(dets_flip):
+                if ocls != fcls or j in matched_flip:
+                    continue
+                ix1, iy1 = max(ox1, fx1), max(oy1, fy1)
+                ix2, iy2 = min(ox2, fx2), min(oy2, fy2)
+                inter = max(0, ix2 - ix1) * max(0, iy2 - iy1)
+                oa = (ox2 - ox1) * (oy2 - oy1)
+                fa = (fx2 - fx1) * (fy2 - fy1)
+                iou = inter / max(oa + fa - inter, 1e-6)
+                if iou >= PETROL_TTA_MATCH_IOU:
+                    conf = max(oc, fc)
+                    if conf >= PETROL_CONF:
+                        merged.append((ox1, oy1, ox2, oy2, conf, ocls))
+                    matched_orig.add(i)
+                    matched_flip.add(j)
+                    break
+
+        # Original-only: keep at stricter threshold
+        for i, det in enumerate(dets_orig):
+            if i not in matched_orig and det[4] >= PETROL_CONF_ORIG:
+                merged.append(det)
+
+        # Flip-only: discard
+
+        if not merged:
             return []
 
-        dets = self._petrol_geometric_validate(dets, orig_h, orig_w)
-        dets = self._petrol_spatial_cooccurrence(dets, orig_h, orig_w)
+        merged = self._petrol_geometric_validate(merged, oh, ow)
+        merged = self._petrol_spatial_cooccurrence(merged, oh, ow)
 
         out_boxes = []
-        for x1, y1, x2, y2, conf, cls_id in dets:
+        for x1, y1, x2, y2, conf, cls_id in merged:
             out_boxes.append(BoundingBox(
-                x1=max(0, min(orig_w, math.floor(x1))),
-                y1=max(0, min(orig_h, math.floor(y1))),
-                x2=max(0, min(orig_w, math.ceil(x2))),
-                y2=max(0, min(orig_h, math.ceil(y2))),
+                x1=max(0, min(ow, math.floor(x1))),
+                y1=max(0, min(oh, math.floor(y1))),
+                x2=max(0, min(ow, math.ceil(x2))),
+                y2=max(0, min(oh, math.ceil(y2))),
                 cls_id=cls_id,
                 conf=max(0.0, min(1.0, conf)),
             ))