export with nbdev

app.py

@@ -1,7 +1,38 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
+
+# %% auto 0
+__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image']
+
+# %% app.ipynb 2
+from fastai.vision.all import *
+import PIL
+import pathlib
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+def is_cat(x): return x[0].isupper()
+
+# %% app.ipynb 4
+# Check if you are on a Windows system
+if sys.platform == 'win32': 
+    # Set the base PosixPath to WindowsPath
+    pathlib.PosixPath = pathlib.WindowsPath
+pathlib.PosixPath
+
+# %% app.ipynb 5
+learn =load_learner('cat_dog_model.pkl')
+
+# %% app.ipynb 7
+categories= ('Dog', 'Cat')
+
+def classify_image(img):
+    pred,idx, probs = learn.predict(img)
+    return dict(zip(categories, map(float,probs)))
+
+# %% app.ipynb 9
+image = gr.Image(height=192,width=192)
+label = gr.Label()  
+examples =['dog.jpg', 'cats.jpeg', 'dogs.png']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)