Update app.py

app.py

@@ -27,28 +27,13 @@ ocr_reader = load_easyocr_reader()
 def process_image(image, confidence_threshold=0.5):
     # Perform license plate detection
     results = yolo_model(image, conf=confidence_threshold)
-    annotated_image = image.copy()  # Work on a copy to draw the bounding boxes
+    annotated_image = cv2.cvtColor(results[0].plot(), cv2.COLOR_BGR2RGB)
     
-    # Loop through detections and draw red, thicker bounding boxes
-    for result in results:
-        boxes = result.boxes.xyxy.cpu().numpy().astype(int)
-        if len(boxes) == 0:
-            st.warning("No license plate detected!")
-            return
-        
-        for box in boxes:
-            x1, y1, x2, y2 = box
-            # Draw the bounding box (red, thickness 3)
-            cv2.rectangle(annotated_image, (x1, y1), (x2, y2), (255, 0, 0), 3)
-    
-    # Convert to RGB for display
-    annotated_image_rgb = cv2.cvtColor(annotated_image, cv2.COLOR_BGR2RGB)
-
     # Create columns to display the uploaded image, cropped image, and extracted text side by side
     c1, c2 = st.columns(2)
     
     with c1:
-        st.image(annotated_image_rgb, caption="Detected License Plate(s)", use_container_width=True)
+        st.image(annotated_image, caption="Detected License Plate(s)", use_container_width=True)
 
     # Loop through detections and perform OCR
     for result in results: