4

app.py

@@ -16,22 +16,53 @@ def resize_image(image_path):
     resized_img = cv2.resize(img, (512, 512), interpolation = cv2.INTER_LINEAR)
 
     return resized_img
-
-
 def prediction1(image_path):
-    #image = resize_image(image_path)
+    # Read the image using OpenCV
     image = cv2.imread(image_path)
-    outputs = model.predict(source=image_path)
+    outputs = model.predict(image_path)
     results = outputs[0].cpu().numpy()
+
+    # Initialize maximum area and index
+    max_area = 0
+    max_index = -1
+
+    # Calculate areas and find the box with the maximum area
     for i, det in enumerate(results.boxes.xyxy):
+        width = det[2] - det[0]
+        height = det[3] - det[1]
+        area = width * height
+        if area > max_area:
+            max_area = area
+            max_index = i
+
+        # Draw bounding box for each detected pothole
         cv2.rectangle(
             image,
             (int(det[0]), int(det[1])),
             (int(det[2]), int(det[3])),
-            color=(0,255, 0),
+            color=(0, 255, 0),
             thickness=1,
             lineType=cv2.LINE_AA,
         )
+
+    # Add label to the bounding box with the maximum area
+    if max_index != -1:
+        det = results.boxes.xyxy[max_index]
+        # Compute relative width and height
+        relative_width = (det[2] - det[0]) / image.shape[1]
+        relative_height = (det[3] - det[1]) / image.shape[0]
+
+        # Draw relative width and height on the bounding box
+        cv2.putText(
+            image,
+            f'W: {relative_width:.2f}, H: {relative_height:.2f}',
+            (int(det[0]), int(det[1]) - 5),
+            cv2.FONT_HERSHEY_SIMPLEX,
+            0.5,
+            (0, 0, 255),
+            1,
+            cv2.LINE_AA
+        )
     return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
 
 inputs_image = [
@@ -47,7 +78,7 @@ interface_image = gr.Interface(
     title="Pothole detection",
     description="Detects potholes in images",
     #cache_examples=True,
-    examples=path
+    examples=[['pothole1.jpg'], ['pothole2.jpg'], ['pothole3.jpg'],['pothole4.jpg']]
     
 )