Update app.py

app.py

@@ -10,6 +10,27 @@ model = YOLO('HandSignDetector.pt')  # Replace with the path to your best.pt mod
 st.title("YOLOv5 Object Detection with Streamlit")
 uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
 
+from PIL import Image, ImageDraw, ImageFont
+
+def draw_bounding_box(image, box, class_label, probability):
+    # Convert to ImageDraw format
+    draw = ImageDraw.Draw(image)
+
+    # Draw bounding box
+    draw.rectangle(box, outline="red", width=3)
+
+    # Add class label and probability
+    label = f"{class_label}: {probability:.2f}"
+    font = ImageFont.load_default()
+    text_width, text_height = draw.textsize(label, font)
+
+    # Calculate position to center the text inside the bounding box
+    text_position = ((box[0] + box[2]) - text_width) / 2, box[3] + 5
+
+    # Draw text on the image
+    draw.text(text_position, label, font=font, fill="red")
+    return draw
+    
 if uploaded_file is not None:
     # Read the uploaded image
     image = Image.open(uploaded_file)
@@ -27,5 +48,4 @@ if uploaded_file is not None:
         score = det.boxes.conf
 
         # Draw box on the image
-        st.image(model.plot([image], boxes=[box], labels=[cls], confidences=[score])[0],
-                 channels="RGB", caption=f"Class {label} - Confidence: {score:.2f}", use_column_width=True)
+        st.image(draw_bounding_box(image,box,cls,score))