/

app.py

@@ -1,4 +1,46 @@
-import streamlit as st
+# Hide - Connects voila to current notebook
+#!jupyter serverextension enable --sys-prefix voila
+
+# Voila runs jpnb but hides the code cells and only displays the output (including the ipywidgets) as well as the markdown cells.
+
+#import fastbook
+#fastbook.setup_book()
+from fastbook import *
+from fastai.vision.widgets import *
+
+# Load the model
+path = Path()
+path.ls(file_exts='.pkl')
+
+learn_inf = load_learner(path/'export.pkl')
+
+# Create a button widget
+btn_upload = widgets.FileUpload()
+btn_upload
+
+# Create a clear_output widget
+out_pl = widgets.Output()
+out_pl.clear_output()
+
+# Create a label widget
+lbl_pred = widgets.Label()
+
+# Create a run button widget
+btn_run = widgets.Button(description='Classify')
+btn_run
+
+# Function to classify the image
+def on_click_classify(change):
+    img = PILImage.create(btn_upload.data[-1])
+    out_pl.clear_output()
+    with out_pl: display(img.to_thumb(128,128))
+    pred,pred_idx,probs = learn_inf.predict(img)
+    lbl_pred.value = f'Prediction: {pred}; Probability: {probs[pred_idx]:.04f}'
+
+btn_run.on_click(on_click_classify)
+
+# Create a Vertical Box (VBox) to hold the widgets
+btn_upload = widgets.FileUpload()
+VBox([widgets.Label('Select your forest!'),
+      btn_upload, btn_run, out_pl, lbl_pred])
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)