Create app.py

app.py

@@ -0,0 +1,25 @@
+import streamlit as st
+from PIL import Image
+from fastai.vision.all import *
+
+def is_cat(x): 
+    return x[0].isupper()
+
+learn = load_learner('model.pkl')
+categories = ('Dog', 'Cat')
+
+def classify_image(img):
+    img = Image.open(img)
+    pred, idx, probs = learn.predict(img)
+    return {categories[i]: float(probs[i]) for i in range(len(categories))}
+
+st.title("Image Classifier")
+uploaded_file = st.file_uploader("Choose an image...", type="jpg")
+
+if uploaded_file is not None:
+    image = Image.open(uploaded_file)
+    st.image(image, caption='Uploaded Image', use_column_width=True)
+    st.write("")
+    st.write("Classifying...")
+    result = classify_image(uploaded_file)
+    st.write(result)