Update app.py

app.py

@@ -7,7 +7,7 @@ import numpy as np
 from PIL import Image
 
 # Step 1: Download the YOLO model weights from your Hugging Face repository
-weights_path = hf_hub_download(repo_id="krishnamishra8848/Nepal-Vehicle-License-Plate-Detection", filename="best.pt")
+weights_path = hf_hub_download(repo_id="krishnamishra8848/Nepal-Vehicle-License-Plate-Detection", filename="last.pt")
 
 # Step 2: Load the YOLO model
 model = YOLO(weights_path)
@@ -27,7 +27,7 @@ def detect_license_plate(image):
             for box, conf in zip(result.boxes.xyxy, result.boxes.conf):
                 x1, y1, x2, y2 = map(int, box)  # Convert to integers
                 cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 0), 2)  # Green rectangle
-                label = f"{conf:.2f}"
+                label = f"Confidence: {conf:.2f}"
                 cv2.putText(img, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
 
     # Convert back to RGB for Streamlit display