fixed bugs

app.py

@@ -1,6 +1,8 @@
+import io
 import timm
 import torch
 import streamlit as st
+from PIL import Image
 from timm.data import resolve_data_config
 from timm.data.transforms_factory import create_transform
 
@@ -17,7 +19,9 @@ uploaded_image = st.file_uploader("Choose an image...", type=["jpg", "png", "jpe
 if uploaded_image is not None:
     st.image(uploaded_image, caption="Uploaded Image", use_column_width=True)
     st.subheader("Classification Results:")
-    output = model(transform(uploaded_image).unsqueeze(0))
+    image_data = uploaded_image.read()
+    image = Image.open(io.BytesIO(image_data))
+    output = model(transform(image).unsqueeze(0))
     probabilities = torch.nn.functional.softmax(output[0], dim=0)
     values, indices = torch.topk(probabilities, 5)
     predictions = [
@@ -25,4 +29,4 @@ if uploaded_image is not None:
         for i, v in zip(indices, values)
     ]
     for prediction in predictions:
-        st.write(f"- {prediction.label}: {prediction.score:.4f}")
+        st.write(f"- {prediction['label']}: {prediction['score']:.4f}")