implemented dog cat classifier

app.py

@@ -1,7 +1,31 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: dog_cat_predicter.ipynb.
+
+# %% auto 0
+__all__ = ['learn', 'labels', 'image', 'label', 'examples', 'interface', 'is_cat', 'predict_image']
+
+# %% dog_cat_predicter.ipynb 1
+from fastai.vision.all import *
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+# %% dog_cat_predicter.ipynb 3
+def is_cat(x): return x[0].isupper() 
+
+learn = load_learner('models/dog_cat_model.pkl')
+
+# %% dog_cat_predicter.ipynb 5
+labels = ['Dog', 'Cat']
+
+def predict_image(img):
+    #Function to predict input image and return a dictionary with each label and probability (as a float)
+    pred,pred_idx,probs = learn.predict(img)
+    return dict(zip(labels, map(float, probs)))
+
+# %% dog_cat_predicter.ipynb 7
+#Define the Gradio Interface
+
+image = gr.inputs.Image(shape=(224, 224))
+label = gr.outputs.Label()
+examples = ['dog.jpg', 'cat.jpg', 'hamster.jpg']
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+interface = gr.Interface(fn=predict_image, inputs=image, outputs=label, examples=examples)
+interface.launch(inline=False)

models/dog_cat_model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d64b3d64e418b1660bd37c832374ddc8052f350ea003ab7c3dd20689b84c83dd
+size 47071225