app.py

app.py

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+import streamlit as st
+from fastai.vision.all import *
+
+learn = load_learner('stage-1_resnet.pkl')
+
+categories = ('DR','NO_DR')
+
+def classify_image(img):
+    img = PILImage.create(img)
+    pred, idx, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+st.title('Image Classification with Fastai and Streamlit')
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "png"])
+
+if uploaded_file is not None:
+    image = PILImage.create(uploaded_file)
+    st.image(image, caption='Uploaded Image.', use_column_width=True)
+    prediction = classify_image(image)
+    st.write("Prediction:", prediction)