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jatin
2025-08-26 13:07:59 -07:00
parent 4732549791
commit 6d9a27f1e8
38 changed files with 6600 additions and 1792 deletions
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156
qt_app_pyside1/controllers/model_manager.py
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@@ -52,7 +52,8 @@ class ModelManager:
"confidence_threshold": 0.3,
"enable_ocr": True,
"enable_tracking": True,
"model_path": None
"model_path": None,
"device": "GPU" # Force GPU usage for Intel Arc
},
"violations": {
"red_light_grace_period": 2.0,
@@ -97,13 +98,27 @@ class ModelManager:
# Initialize detector
print(f"✅ Initializing OpenVINO detector with model: {model_path}")
# Store current model info for stats
self.current_model_path = model_path
self.current_model_name = self._extract_model_name_from_path(model_path)
device = self.config["detection"].get("device", "AUTO")
print(f"✅ Using inference device: {device}")
print(f"🔧 Model Manager: Config device setting: {device}")
print(f"🔧 Model Manager: Creating detector with device: {device}")
self.detector = OpenVINOVehicleDetector(
model_path=model_path,
device=device,
confidence_threshold=self.config["detection"]["confidence_threshold"]
)
print(f"✅ Detector created with device: {device}")
# Verify the detector is using the correct device
if hasattr(self.detector, 'device'):
actual_device = self.detector.device
print(f"🔍 Model Manager: Detector reports device as: {actual_device}")
else:
print(f"🔍 Model Manager: Detector device attribute not available")
# Use only RedLightViolationPipeline for violation/crosswalk/traffic light logic
self.violation_pipeline = RedLightViolationPipeline(debug=True)
@@ -128,18 +143,48 @@ class ModelManager:
traceback.print_exc()
def _find_best_model_path(self, base_model_name: str = None) -> Optional[str]:
"""
Find the best model path based on configuration.
Now respects the model selection from config panel.
"""
if base_model_name is None:
device = self.config["detection"].get("device", "AUTO")
if device == "CPU" or device == "AUTO":
# Use yolo11n for CPU - faster, lighter model
base_model_name = "yolo11n"
print(f"🔍 Device is {device}, selecting {base_model_name} model (optimized for CPU)")
# First, check if a specific model is selected in config
selected_model = self.config["detection"].get("model", None)
if selected_model and selected_model.lower() != "auto":
base_model_name = selected_model.lower()
# Convert YOLOv11x format to yolo11x format
if 'yolov11' in base_model_name:
base_model_name = base_model_name.replace('yolov11', 'yolo11')
print(f"🎯 Using model selected from config panel: {base_model_name}")
else:
# Use yolo11x for GPU - larger model with better accuracy
base_model_name = "yolo11x"
print(f"🔍 Device is {device}, selecting {base_model_name} model (optimized for GPU)")
# Fallback to device-based selection only if no specific model selected
device = self.config["detection"].get("device", "AUTO")
if device == "CPU" or device == "AUTO":
# Use yolo11n for CPU - faster, lighter model
base_model_name = "yolo11n"
print(f"🔍 Device is {device}, selecting {base_model_name} model (optimized for CPU)")
else:
# Use yolo11x for GPU - larger model with better accuracy
base_model_name = "yolo11x"
print(f"🔍 Device is {device}, selecting {base_model_name} model (optimized for GPU)")
# Ensure we have a clean model name (remove any version suffixes)
if base_model_name:
# Handle different model name formats
if "yolo11" in base_model_name.lower():
if "11n" in base_model_name.lower():
base_model_name = "yolo11n"
elif "11x" in base_model_name.lower():
base_model_name = "yolo11x"
elif "11s" in base_model_name.lower():
base_model_name = "yolo11s"
elif "11m" in base_model_name.lower():
base_model_name = "yolo11m"
elif "11l" in base_model_name.lower():
base_model_name = "yolo11l"
print(f"🔍 Looking for model: {base_model_name}")
# Check if the openvino_models directory exists in the current working directory
cwd_openvino_dir = Path.cwd() / "openvino_models"
@@ -201,6 +246,55 @@ class ModelManager:
print(f"❌ No model found for {base_model_name}")
return None
def _extract_model_name_from_path(self, model_path: str) -> str:
"""Extract model name from file path"""
try:
# Convert to lowercase for matching
path_lower = model_path.lower()
print(f"🔍 Extracting model name from path: {model_path}")
print(f"🔍 Path lower: {path_lower}")
# Check for specific models
if 'yolo11n' in path_lower:
extracted_name = 'YOLOv11n'
print(f"✅ Extracted model name: {extracted_name}")
return extracted_name
elif 'yolo11s' in path_lower:
extracted_name = 'YOLOv11s'
print(f"✅ Extracted model name: {extracted_name}")
return extracted_name
elif 'yolo11m' in path_lower:
extracted_name = 'YOLOv11m'
print(f"✅ Extracted model name: {extracted_name}")
return extracted_name
elif 'yolo11l' in path_lower:
extracted_name = 'YOLOv11l'
print(f"✅ Extracted model name: {extracted_name}")
return extracted_name
elif 'yolo11x' in path_lower:
extracted_name = 'YOLOv11x'
print(f"✅ Extracted model name: {extracted_name}")
return extracted_name
elif 'yolo11' in path_lower:
extracted_name = 'YOLOv11'
print(f"✅ Extracted model name: {extracted_name}")
return extracted_name
else:
extracted_name = 'YOLO'
print(f"⚠️ Fallback model name: {extracted_name}")
return extracted_name
except Exception as e:
print(f"⚠️ Error extracting model name: {e}")
return 'Unknown'
def get_current_model_info(self) -> dict:
"""Get current model information for stats"""
return {
'model_path': getattr(self, 'current_model_path', None),
'model_name': getattr(self, 'current_model_name', 'Unknown'),
'device': self.detector.get_device() if self.detector else 'Unknown'
}
def detect(self, frame: np.ndarray) -> List[Dict]:
"""
@@ -392,8 +486,9 @@ class ModelManager:
if not new_config:
return
# Store old device setting to check if it changed
# Store old settings to check if they changed
old_device = self.config["detection"].get("device", "AUTO") if "detection" in self.config else "AUTO"
old_model = self.config["detection"].get("model", "auto") if "detection" in self.config else "auto"
# Update configuration
for section in new_config:
@@ -402,21 +497,46 @@ class ModelManager:
else:
self.config[section] = new_config[section]
# Check if device changed - if so, we need to reinitialize models
# Check if device or model changed - if so, we need to reinitialize models
new_device = self.config["detection"].get("device", "AUTO")
new_model = self.config["detection"].get("model", "auto")
device_changed = old_device != new_device
model_changed = old_model != new_model
if device_changed:
print(f"📢 Device changed from {old_device} to {new_device}, reinitializing models...")
# Reinitialize models with new device
self._initialize_models()
if device_changed or model_changed:
print(f"📢 Configuration changed:")
if device_changed:
print(f" Device: {old_device} → {new_device}")
if model_changed:
print(f" Model: {old_model} → {new_model}")
print(f" Reinitializing models...")
# Force complete reinitialization - let the model path extraction handle the naming
self.force_model_reload()
return
# Just update detector confidence threshold if device didn't change
# Just update detector confidence threshold if device and model didn't change
if self.detector:
conf_thres = self.config["detection"].get("confidence_threshold", 0.5)
self.detector.conf_thres = conf_thres
def force_model_reload(self):
"""Force complete model reload with current config"""
print("🔄 Force reloading models with current configuration...")
# Get the configured model selection
selected_model = self.config["detection"].get("model", "auto")
print(f"🎯 Force reload: Config model selection = {selected_model}")
# Clear current models
self.detector = None
self.violation_pipeline = None
# Reinitialize with current config - let _initialize_models handle the naming
self._initialize_models()
print("✅ Models reloaded successfully")
def _bbox_iou(self, boxA, boxB):
# Compute the intersection over union of two boxes
xA = max(boxA[0], boxB[0])