Update app.py

app.py

@@ -1,10 +1,10 @@
 import streamlit as st
-from ultralytics import YOLO
 from ultralytics.utils.plotting import Annotator
 import numpy as np
 import cv2
-import yolov9
 from PIL import Image
+import io
+import yolov9
 
 # Load the YOLOv9 model
 model = yolov9.load('fracture.pt', device="cpu")
@@ -39,8 +39,13 @@ st.title("YOLOv9 Fracture Detection")
 uploaded_file = st.file_uploader("Choose an image...", type=["png", "jpg", "jpeg"])
 
 if uploaded_file is not None:
-    # Load the image
-    image = Image.open(uploaded_file)
+    # Convert the uploaded file to a JPEG image
+    image = Image.open(uploaded_file).convert("RGB")
+    img_byte_arr = io.BytesIO()
+    image.save(img_byte_arr, format="JPEG")
+    image = Image.open(io.BytesIO(img_byte_arr.getvalue()))
+
+    # Display the uploaded image
     st.image(image, caption='Uploaded Image.', use_column_width=True)
 
     # Run the prediction