Update app.py

app.py

@@ -4,7 +4,7 @@ from PIL import Image
 import os
 
 # Load the trained YOLOv8 model
-model = YOLO("yolov8n.pt")
+model = YOLO("best.pt")
 
 # Define the prediction function
 def predict(image):
@@ -33,18 +33,18 @@ if uploaded_image is not None:
     image = Image.open(uploaded_image)
 
     # Display the uploaded image
-    st.image(image, caption="Uploaded Image", use_column_width=True)
+    st.image(image, caption="Uploaded Image", use_container_width=True)
 
     # Run the model prediction
     st.subheader("Prediction Results:")
     result_image = predict(image)
     
     # Display the result image with bounding boxes
-    st.image(result_image, caption="Detected Image", use_column_width=True)
+    st.image(result_image, caption="Detected Image", use_container_width=True)
 
 # Optionally, show example images from the folder
 if st.checkbox('Show example images'):
     example_images = get_example_images()
     for example_image in example_images:
         img = Image.open(example_image)
-        st.image(img, caption=os.path.basename(example_image), use_column_width=True)
+        st.image(img, caption=os.path.basename(example_image), use_container_width=True)