basic model prediction

app.py

@@ -1,4 +1,16 @@
 import streamlit as st
+from fastai.vision.all import *
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+def is_cat(x) : return x[0].isupper()
+
+learn = load_learner('model.pkl')
+
+categories = ('Dog', 'Cat')
+
+def classify_image(img):
+    pred,idx,probs = learn.predict(img)
+    return dict(zip(categories,map(float,probs)))
+
+image = st.file_uploader("Choose a file")
+
+label = st.write(classify_image(image))

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fb83624a71f64fcfc2e3a0f392b5137e84183f95f6a610ec6f746537a016d966
+size 47063057