jph

app.py

@@ -1,20 +1,27 @@
-import gradio as gr
+# AUTOGENERATED! DO NOT EDIT! File to edit: . (unless otherwise specified).
+
+__all__ = ['is_cat', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']
+
+# Cell
 from fastai.vision.all import *
+import gradio as gr
 
-__all__ = ['is_cat', 'learn', 'classify_image', 'categories', 'image', 'label', 'iface']
+def is_cat(x): return x[0].isupper()
 
+# Cell
 learn = load_learner('model.pkl')
 
+# Cell
 categories = ('Dog', 'Cat')
 
-def is_cat(x : str):
-    return x[0].isupper()
-
 def classify_image(img):
-    pred, idx, probs = learn.predict(img)
-    return dict(zip(categories, map(float, probs)))
+    pred,idx,probs = learn.predict(img)
+    return dict(zip(categories, map(float,probs)))
 
-image = gr.inputs.Image(shape = (192, 192))
+# Cell
+image = gr.inputs.Image(shape=(192, 192))
 label = gr.outputs.Label()
-iface = gr.Interface(fn=classify_image, inputs=image, outputs=label)
-iface.launch(inline = False)
+examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)