Update app.py

app.py

@@ -52,19 +52,58 @@ class SmartGlassesSystem:
                 device=0 if using_gpu else -1
             )
             
-            # Load object detection model
-            logger.info("Loading object detection model...")
-            self.detector = pipeline(
-                "object-detection", 
-                model="facebook/detr-resnet-50", 
-                device=0 if using_gpu else -1
-            )
+            # Check if timm is installed for object detection
+            try:
+                import timm
+                logger.info("Loading object detection model...")
+                self.detector = pipeline(
+                    "object-detection", 
+                    model="facebook/detr-resnet-50", 
+                    device=0 if using_gpu else -1
+                )
+            except ImportError:
+                logger.warning("timm library not found, using YOLOv5 as fallback for object detection")
+                try:
+                    import torch
+                    # Use YOLOv5 as a fallback (it has fewer dependencies)
+                    self.detector = torch.hub.load('ultralytics/yolov5', 'yolov5s', pretrained=True)
+                    # Make detector interface compatible with transformers pipeline
+                    self._original_detect = self.detector
+                    self.detector = self._yolo_detector_wrapper
+                except Exception as e2:
+                    logger.error(f"Fallback object detection also failed: {str(e2)}")
+                    logger.warning("Object detection will be disabled")
+                    self.detector = self._dummy_detector
             
             logger.info("All models loaded successfully!")
             
         except Exception as e:
             logger.error(f"Error initializing models: {str(e)}")
             raise RuntimeError(f"Failed to initialize AI models: {str(e)}")
+            
+    def _yolo_detector_wrapper(self, image):
+        """Wrapper to make YOLOv5 output compatible with transformers pipeline format"""
+        results = self._original_detect(image)
+        detections = []
+        
+        # Convert YOLOv5 results to transformers pipeline format
+        for i, (x1, y1, x2, y2, conf, cls) in enumerate(results.xyxy[0]):
+            detections.append({
+                'score': float(conf),
+                'label': results.names[int(cls)],
+                'box': {
+                    'xmin': int(x1),
+                    'ymin': int(y1),
+                    'xmax': int(x2),
+                    'ymax': int(y2)
+                }
+            })
+        return detections
+        
+    def _dummy_detector(self, image):
+        """Dummy detector when no object detection is available"""
+        logger.warning("Object detection is disabled due to missing dependencies")
+        return []
     
     def get_ocr_reader(self, language_choice):
         """Get or create appropriate OCR reader based on language choice"""