final app.py file

app.py

@@ -1,7 +1,17 @@
+from fastai.vision.all import *
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+learn = load_learner('model.pkl')
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+
+categories = ('Car', 'Bike')
+def classify_image(img):
+    is_car,_,probs = learn.predict(PILImage.create(img))
+    return dict(zip(categories, map(float,probs))) #gradio only supports floats and it doesn't handle PyTorch tensors
+
+image = gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label()
+examples = ['volkswagen.jpg','motorbike.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0362548f7d683cb903cdd048e4084539cb1dfd57a91e1d81eee63b315fb8135d
+size 46954713