pushing first DL model to huggingface

CatsClassifier.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5589472f554647dbf4115edfd518b01583038316943b0e699cc031e0038bb71c
+size 47061355

app.py

@@ -1,9 +1,25 @@
 import gradio as gr
+from fastai.vision.all import *
+_all_ = ['is_cat', 'learn', 'classify_image',
+         'categories', 'image', 'label', 'examples', 'intf']
 
 
-def greet(name):
-    return "Hello " + name + "!!"
+def is_cat(x): return x[0].isupper()
 
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+learn = load_learner('CatsClassifier.pkl')
+categories = ("Dog", "Cat")
+
+
+def classify_image(img):
+    pred, idx, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+
+image = gr.inputs.Image(shape=(192, 192))
+label = gr.outputs.Label()
+examples = ['dog.jpg', 'cat.jpeg', 'ambiguous.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image,
+                    outputs=label, examples=examples)
+intf.launch(inline=False)