Update app.py

app.py

@@ -31,7 +31,7 @@ def calculate_materials(detected_objects, image_width, image_height):
             materials['bricks'] += area * 10  # Bricks estimation
             materials['steel'] += area * 0.05  # Steel estimation
         
-        if obj['name'] == 'foundation':  # Example: For 'foundation' objects
+        elif obj['name'] == 'foundation':  # Example: For 'foundation' objects
             materials['cement'] += area * 0.2  # More cement for foundation
             materials['bricks'] += area * 15  # More bricks for foundation
             materials['steel'] += area * 0.1  # More steel for foundation
@@ -49,6 +49,10 @@ def predict_image(image):
     # Print out the detection results for debugging purposes
     print(f"Detected objects: {detected_objects}")
     
+    # Set the confidence threshold (e.g., 0.5 means 50% confidence)
+    confidence_threshold = 0.5
+    detected_objects = detected_objects[detected_objects['confidence'] > confidence_threshold]
+    
     # Assume blueprint image size (in cm, adjust based on real-world image size)
     image_width = 91  # Example width in cm (adjust this)
     image_height = 61  # Example height in cm (adjust this)
@@ -57,7 +61,7 @@ def predict_image(image):
     detected_objects_list = []
     for _, row in detected_objects.iterrows():
         detected_objects_list.append({
-            'name': row['name'],   # Detected object class name (e.g., 'wall', 'foundation')
+            'name': row['name'],  # Detected object class name (e.g., 'wall', 'foundation')
             'bbox': [row['xmin'], row['ymin'], row['xmax'], row['ymax']]  # Bounding box coordinates
         })