Boiler plate 0.1

.gitignore

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+.venv/

app.py

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