deploy to huggingface spaces

app.py

@@ -1,7 +1,21 @@
-import gradio as gr
+# import all the fastai stuff.
+from fastai.vision.all import *
+
+# load our model.
+learn = load_learner('export.pkl')
 
-def greet(name):
-    return "Hello " + name + "!!"
+# define a prediction function, not sure what this means.
+labels = learn.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    # this returns 
+    #   predicted category
+    #   index
+    #   probabilities of each category
+    pred,pred_idx,probs = learn.predict(img)
+    # we return a weird dictionary or JSON?
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+import gradio as gr
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)