dog cat classify

app.py

@@ -1,7 +1,28 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
+
+# %% auto 0
+__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image']
+
+# %% app.ipynb 1
+from fastai.vision.all import *
+import nbdev
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+# %% app.ipynb 3
+def is_cat(x): return x[0].isupper() 
+learn = load_learner('model.pkl')
+
+# %% app.ipynb 5
+categories = ('Dog', 'Cat')
+
+def classify_image(img):
+    pred, idx, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+# %% app.ipynb 7
+image = gr.components.Image(height=192, width=192)
+label = gr.components.Label()
+examples = ['dog.png', 'cat.png']
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+intf = gr.Interface(fn=classify_image, inputs='image', outputs='label', examples=examples)
+intf.launch()