testing

app.py

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+import numpy as np
+import streamlit as st
+from fastai.vision.core import *
+from fastai.vision.all import *
+import pathlib
+import platform
+
+if platform.system() == 'Windows':
+    temp = pathlib.PosixPath
+    pathlib.PosixPath = pathlib.WindowsPath
+def is_cat(x): return x[0].isupper()
+if __name__=='__main__':
+    learn = load_learner(pathlib.Path()/'model.pkl')
+    uploaded_file = st.file_uploader("Choose an image of a dog or cat")
+    if uploaded_file is not None:
+        im = PILImage.create((uploaded_file))
+        st.image(im.to_thumb(500, 500), caption='Uploaded Image')
+        if st.button('Classify'):
+            pred, ix, probs = learn.predict(im.convert('RGB'))
+            data = dict(zip(('Dog', 'Cat'), map(float, probs)))
+            st.bar_chart(data=data)
+        else:
+            st.write(f'Click the button to classify')
+
+

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e87969a9ecd168698eef4a6edeb04e5c4f57768fb30d7a1d08d7d5f422587738
+size 47061483