Upload app.py

src/app.py

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+import streamlit as st
+import requests
+from PIL import Image
+import io
+
+# Streamlit app title
+st.title("🥔 Potato Leaf Disease Classifier")
+
+# Upload image
+uploaded_file = st.file_uploader("Upload a potato leaf image", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    # Show preview
+    image = Image.open(uploaded_file)
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+
+    # Button to trigger prediction
+    if st.button("Predict"):
+        with st.spinner("Classifying..."):
+            # Send image to FastAPI backend
+            response = requests.post(
+                "http://localhost:8000/predict",
+                files={"file": uploaded_file.getvalue()}
+            )
+            
+            if response.status_code == 200:
+                result = response.json()
+                st.success(f"🌿 Predicted Class: **{result['class']}**")
+                st.info(f"📈 Confidence: **{result['confidence'] * 100:.2f}%**")
+            else:
+                st.error("Prediction failed. Please try again.")