Update app.py

app.py

@@ -5,9 +5,9 @@ import os
 from ultralytics import YOLO
 
 file_urls = [
-    # 'https://www.dropbox.com/s/b5g97xo901zb3ds/pothole_example.jpg?dl=1',
-    # 'https://www.dropbox.com/s/86uxlxxlm1iaexa/pothole_screenshot.png?dl=1',
-    # 'https://www.dropbox.com/s/7sjfwncffg8xej2/video_7.mp4?dl=1'
+    'https://www.dropbox.com/scl/fi/kqd1z6wby1212c6ndodb3/Pol_20_jpg.rf.133c835b66958a7d48c12deeda31a719.jpg?rlkey=uqgvs2cwvahnmju15fv1zgorg&st=snv2yvtk&dl=0',
+    'https://www.dropbox.com/scl/fi/39aakapeh2y5ztk94rsyu/11e-a347-3f2d_jpg.rf.c66e5aeb57ee2ed660fdf0162156127d.jpg?rlkey=xoi3iw45vksgiejycau2ha7fh&st=etiawigv&dl=0',
+    'https://www.dropbox.com/scl/fi/8f08ehy53vsemw164g8n7/Recording2024-06-26184319.mp4?rlkey=pnmov906ttodl0cm92rpvc5ta&st=2twc9pjn&dl=0'
 ]
 
 def download_file(url, save_name):
@@ -29,7 +29,9 @@ def show_preds_image(image_path):
     image = cv2.imread(image_path)
     outputs = model.predict(source=image_path)
     results = outputs[0].cpu().numpy()
+
     for i, det in enumerate(results.boxes.xyxy):
+        # Draw the bounding box
         cv2.rectangle(
             image,
             (int(det[0]), int(det[1])),
@@ -38,8 +40,36 @@ def show_preds_image(image_path):
             thickness=2,
             lineType=cv2.LINE_AA
         )
+        
+        # Get the class label and confidence score
+        class_id = int(results.boxes.cls[i])
+        confidence = results.boxes.conf[i]
+        label = f"{model.names[class_id]}: {confidence:.2f}"
+        
+        # Draw the label
+        label_size, _ = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, 0.5, 1)
+        top_left = (int(det[0]), int(det[1]) - 10)
+        bottom_right = (int(det[0]) + label_size[0], int(det[1]))
+        cv2.rectangle(image, top_left, bottom_right, (0, 0, 255), cv2.FILLED)
+        cv2.putText(image, label, (int(det[0]), int(det[1]) - 5), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1)
+
     return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
 
+# def show_preds_image(image_path):
+#     image = cv2.imread(image_path)
+#     outputs = model.predict(source=image_path)
+#     results = outputs[0].cpu().numpy()
+#     for i, det in enumerate(results.boxes.xyxy):
+#         cv2.rectangle(
+#             image,
+#             (int(det[0]), int(det[1])),
+#             (int(det[2]), int(det[3])),
+#             color=(0, 0, 255),
+#             thickness=2,
+#             lineType=cv2.LINE_AA
+#         )
+#     return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+
 inputs_image = [
     gr.Image(type="filepath", label="Input Image"),
 ]
@@ -51,7 +81,7 @@ interface_image = gr.Interface(
     fn=show_preds_image,
     inputs=inputs_image,
     outputs=outputs_image,
-    title="Pothole detector",
+    title="Smoke Detection on Indian Roads",
     examples=path,
     cache_examples=False,
 )