Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+from io import StringIO
+from fastai import *
+from fastai.vision.all import *
+import bz2file as bz2
+import pickle
+
+header = st.container()
+inference = st.container()
+
+with header:
+	st.title("Cuisine Classifier")
+	st.text("Is your food Italian, French, Chinese, Indian, or Japanese?")
+
+with inference:
+
+    learn_inf = load_learner('export.pkl')
+
+    st.header('Show me your food pic!')
+    st.text("(I currently accept Italian, French, Chinese, Indian, or Japanese. Otherwise, I guesss wildly!)")
+    uploaded_file = st.file_uploader("Show me your food pic!")    
+    if uploaded_file is not None:
+        img = load_image(uploaded_file)
+        pred, pred_idx, probs = learn_inf.predict(img)
+        prob_value = probs[pred_idx].item()
+        rounded_prob_percentage = round(prob_value * 100)
+        st.text(f"This is {pred}, isn't it? Believe me, I am {rounded_prob_percentage}% sure!")