Upload app.py

app.py

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+from fastai.vision.all import *
+import gradio as gr
+
+learn = load_learner("classifier.pkl")
+
+labels = learn.dls.vocab
+examples = ['dolphin.jpg', 'shark.jpg', 'whale.jpg']
+
+def predict(img_file):
+  img = PILImage.create(img_file)
+  pred, idx, probs = learn.predict(img)
+  return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+gr.Interface(fn=predict,
+             inputs=gr.inputs.Image(shape=(512,512)),
+             outputs=gr.outputs.Label(num_top_classes=3),
+             examples=examples).launch(share=True, debug=False)