scorevision: push artifact

miner.py

@@ -1,5 +1,5 @@
 """
-Score Vision SN44 — Unified miner v3.23.2 (2026-04-07). Force 24GB GPU, lazy-load FP32 fallback. FP32 trigger 0 boxes only. TTA consensus (person), parts_confirm on vehicle challenges, car conf 0.60, VEH_MIN_WH=20.
+Score Vision SN44 — Unified miner v3.23.3 (2026-04-07). Diagnostic: vehicle provider logging. 4090 only. Lazy FP32, trigger 0 boxes. TTA consensus (person), parts_confirm on vehicle, car 0.60, VEH_MIN_WH=20.
 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).
@@ -597,6 +597,10 @@ class Miner:
             veh_weights,
             providers=["CUDAExecutionProvider", "CPUExecutionProvider"],
         )
+        veh_actual = self.veh_session.get_providers()
+        logger.warning(f"[init] Vehicle session ACTIVE providers: {veh_actual}")
+        if "CUDAExecutionProvider" not in veh_actual:
+            logger.error("[init] ⚠ VEHICLE IS ON CPU — CUDA EP NOT ACTIVE")
         self.veh_input_name = self.veh_session.get_inputs()[0].name
         veh_shape = self.veh_session.get_inputs()[0].shape
         self.veh_h = int(veh_shape[2])
@@ -934,6 +938,10 @@ class Miner:
         see block 7905900), retries with FP32 model. Single-box results are
         kept as-is — likely real sparse scenes, not INT8 degradation.
         """
+        if not hasattr(self, '_veh_providers_logged'):
+            provs = self.veh_session.get_providers()
+            logger.warning(f"[vehicle] First inference — active providers: {provs}")
+            self._veh_providers_logged = True
         boxes = self._infer_vehicle_core(image_bgr, self.veh_session)
 
         if len(boxes) == 0 and (self.veh_session_fp32 or self._veh_fp32_path):