Fix model.info() TypeError - handle tuple return in newer Ultralytics versions

app/services/image_processing.py

@@ -951,12 +951,16 @@ async def detect_objects_in_image(image_url: str) -> Optional[Dict]:
                 
                 # Use even lower confidence threshold for bigger models
                 # Larger models are more accurate so we can trust lower confidence predictions
-                if yolo_model.__class__.__name__ == "YOLO":
-                    model_size = yolo_model.info()['model_type']
-                    if 'x' in model_size:  # YOLOv8x (extra large)
-                        min_confidence = 0.003  # Accept even lower confidence detections
-                    elif 'l' in model_size:  # YOLOv8l (large)
-                        min_confidence = 0.004
+                try:
+                    if yolo_model is not None and hasattr(yolo_model, 'model') and hasattr(yolo_model.model, 'yaml'):
+                        # Try to get model size from the model name
+                        model_name = str(yolo_model.model.yaml.get('yaml_file', ''))
+                        if 'yolov8x' in model_name.lower():
+                            min_confidence = 0.003  # Accept even lower confidence detections
+                        elif 'yolov8l' in model_name.lower():
+                            min_confidence = 0.004
+                except Exception:
+                    pass  # Use default min_confidence if we can't determine model size
                         
                 # Skip only extremely low confidence detections
                 if confidence < min_confidence:
@@ -1211,15 +1215,37 @@ async def detect_objects_in_image(image_url: str) -> Optional[Dict]:
             model_info = {}
             if yolo_model is not None:
                 try:
+                    # Handle different return types from model.info()
+                    info_result = yolo_model.info() if hasattr(yolo_model, 'info') else None
+                    
+                    # Determine model type
+                    model_type = "unknown"
+                    if isinstance(info_result, dict):
+                        model_type = info_result.get('model_type', 'unknown')
+                    elif isinstance(info_result, tuple) and len(info_result) > 0:
+                        # New versions return tuple: try to extract model info from tuple
+                        model_type = str(info_result[0]) if info_result else 'unknown'
+                    
+                    # Try to get model name from file path or model itself
+                    model_name = "YOLOv8"
+                    if hasattr(yolo_model, 'model') and hasattr(yolo_model.model, 'yaml'):
+                        yaml_file = yolo_model.model.yaml.get('yaml_file', '')
+                        if 'yolov8x' in str(yaml_file).lower():
+                            model_name = "YOLOv8x"
+                        elif 'yolov8l' in str(yaml_file).lower():
+                            model_name = "YOLOv8l"
+                        elif 'yolov8m' in str(yaml_file).lower():
+                            model_name = "YOLOv8m"
+                    
                     model_info = {
-                        "model_type": yolo_model.info().get('model_type', 'unknown'),
-                        "model_name": yolo_model.__class__.__name__,
+                        "model_type": model_type,
+                        "model_name": model_name,
                         "framework": "YOLOv8",
                     }
-                    logger.info(f"Using {model_info['model_type']} model for detection")
+                    logger.info(f"Using {model_name} model for detection")
                 except Exception as e:
                     logger.warning(f"Could not get model info: {e}")
-                    model_info = {"model_type": "unknown", "model_name": "YOLO"}
+                    model_info = {"model_type": "unknown", "model_name": "YOLO", "framework": "YOLOv8"}
             
             # Return the results with model information
             return {