scorevision: push artifact

miner.py

@@ -52,6 +52,104 @@ def _preload_cuda_libs():
 
 _preload_cuda_libs()
 
+import subprocess as _subprocess
+import sys as _sys
+
+def _try_gpu_ort():
+    """Attempt runtime install of onnxruntime-gpu for CUDA inference."""
+    import time as _t
+    _t0 = _t.time()
+
+    # Diagnostic: torch + CUDA
+    try:
+        import torch
+        print(f"[GPU_SETUP] torch={torch.__version__} cuda={torch.cuda.is_available()} "
+              f"devices={torch.cuda.device_count()}", flush=True)
+        if torch.cuda.is_available():
+            print(f"[GPU_SETUP] GPU: {torch.cuda.get_device_name(0)}", flush=True)
+    except Exception as e:
+        print(f"[GPU_SETUP] torch check failed: {e}", flush=True)
+
+    # Check current ORT providers
+    try:
+        import onnxruntime as _ort
+        providers = _ort.get_available_providers()
+        print(f"[GPU_SETUP] ORT={_ort.__version__} providers={providers}", flush=True)
+        if 'CUDAExecutionProvider' in providers:
+            print("[GPU_SETUP] CUDAExecutionProvider already available!", flush=True)
+            return
+    except ImportError:
+        print("[GPU_SETUP] onnxruntime not importable", flush=True)
+        return
+
+    # List key packages for diagnostics
+    result = _subprocess.run(
+        [_sys.executable, '-m', 'pip', 'list', '--format=columns'],
+        capture_output=True, text=True, timeout=15
+    )
+    for pkg in ['onnxruntime', 'torch', 'nvidia-cu', 'ultralytics']:
+        for line in result.stdout.splitlines():
+            if pkg.lower() in line.lower():
+                print(f"[GPU_SETUP] pkg: {line.strip()}", flush=True)
+
+    print("[GPU_SETUP] Attempting onnxruntime-gpu install...", flush=True)
+    try:
+        # Uninstall CPU onnxruntime
+        r1 = _subprocess.run(
+            [_sys.executable, '-m', 'pip', 'uninstall', 'onnxruntime', '-y'],
+            capture_output=True, text=True, timeout=30
+        )
+        print(f"[GPU_SETUP] uninstall rc={r1.returncode}", flush=True)
+
+        # Install GPU version (no-deps to avoid reinstalling torch etc)
+        r2 = _subprocess.run(
+            [_sys.executable, '-m', 'pip', 'install', 'onnxruntime-gpu', '--no-deps'],
+            capture_output=True, text=True, timeout=180
+        )
+        print(f"[GPU_SETUP] install rc={r2.returncode}", flush=True)
+        if r2.stdout:
+            for line in r2.stdout.strip().splitlines()[-3:]:
+                print(f"[GPU_SETUP] stdout: {line}", flush=True)
+        if r2.stderr:
+            for line in r2.stderr.strip().splitlines()[-3:]:
+                print(f"[GPU_SETUP] stderr: {line}", flush=True)
+
+        if r2.returncode != 0:
+            print("[GPU_SETUP] FAILED — reinstalling CPU onnxruntime", flush=True)
+            _subprocess.run(
+                [_sys.executable, '-m', 'pip', 'install', 'onnxruntime', '--no-deps'],
+                capture_output=True, timeout=60
+            )
+            return
+
+        # Clear cached onnxruntime modules
+        for key in list(_sys.modules.keys()):
+            if 'onnxruntime' in key:
+                del _sys.modules[key]
+
+        # Reimport and check
+        import onnxruntime as _ort2
+        new_providers = _ort2.get_available_providers()
+        _dt = _t.time() - _t0
+        print(f"[GPU_SETUP] SUCCESS: ORT={_ort2.__version__} providers={new_providers} ({_dt:.1f}s)", flush=True)
+
+    except Exception as e:
+        print(f"[GPU_SETUP] EXCEPTION: {e}", flush=True)
+        # Try to restore CPU onnxruntime
+        try:
+            for key in list(_sys.modules.keys()):
+                if 'onnxruntime' in key:
+                    del _sys.modules[key]
+            _subprocess.run(
+                [_sys.executable, '-m', 'pip', 'install', 'onnxruntime', '--no-deps'],
+                capture_output=True, timeout=60
+            )
+            print("[GPU_SETUP] Restored CPU onnxruntime", flush=True)
+        except Exception:
+            pass
+
+_try_gpu_ort()
+
 
 from pathlib import Path
 import math
@@ -75,15 +173,15 @@ logger = logging.getLogger(__name__)
 VEH_MODEL_TO_OUT: dict[int, int] = {0: 1, 1: 0, 2: 2, 3: 3}
 VEH_NUM_CLASSES = 4
 # VEH_IMG_SIZE: now read dynamically from model input shape in __init__
-VEH_CONF_PER_CLASS = {0: 0.33, 1: 0.50, 2: 0.40, 3: 0.36}
+VEH_CONF_PER_CLASS = {0: 0.15, 1: 0.30, 2: 0.20, 3: 0.15}
 VEH_CONF_DEFAULT = 0.35
-VEH_TTA_CONF = 0.25
-VEH_WBF_IOU = 0.55
+VEH_TTA_CONF = 0.10
+VEH_WBF_IOU = 0.40
 
 # ── Person config ───────────────────────────────────────────────────────────
-PER_CONF = 0.35
+PER_CONF = 0.15
 PER_TTA_CONF = 0.25
-PER_WBF_IOU = 0.45
+PER_WBF_IOU = 0.40
 
 # ── Shared ──────────────────────────────────────────────────────────────────
 WBF_SKIP_THR = 0.0001