deploying cats and dogs

app.py

@@ -1,7 +1,46 @@
-import gradio as gr
+# -*- coding: utf-8 -*-
+"""dogs_cats.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1M-mzhZdFQ2XWBSbLCuKzrmLsm0aLEYxQ
+
+## Gradio Pets
+"""
+
+
+
+#|export
+from fastai.vision.all import *
+
+def is_cat(x): return x[0].isupper()
+
+
+
+#|export
+learn = load_learner('cat_dog.pkl')
+
+#|export
+categories = ('Dog','Cat')
+def classify_image(img):
+  pred,idx,probs=learn.predict(img)
+  return dict(zip(categories,map(float,probs)))
+
+
+
+
+
+#|export
+
+import gradio
+image = gradio.Image(type='pil')
+label = gradio.Label()
+
+examples = ['dog.jpeg','cat.jpeg']
+intf = gradio.Interface(fn=classify_image,inputs=image,outputs=label,examples=examples)
+intf.launch(inline=False)
+
+
 
-def greet(name):
-    return "Hello " + name + "!!"
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:036e01abcf091bb1ca180ae913d2d5d6555f1e436960b428a40746c3419d41f4
+size 46966993