Delete app.py
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app.py
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#|default_exp app
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# %% [code] {"execution":{"iopub.status.busy":"2023-01-17T14:41:33.341222Z","iopub.execute_input":"2023-01-17T14:41:33.341652Z","iopub.status.idle":"2023-01-17T14:41:34.776787Z","shell.execute_reply.started":"2023-01-17T14:41:33.341595Z","shell.execute_reply":"2023-01-17T14:41:34.775663Z"}}
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#|export
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from fastai.vision.all import *
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import gradio as gr
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# %% [code] {"execution":{"iopub.status.busy":"2023-01-17T14:43:57.890571Z","iopub.execute_input":"2023-01-17T14:43:57.891069Z","iopub.status.idle":"2023-01-17T14:43:58.607922Z","shell.execute_reply.started":"2023-01-17T14:43:57.891028Z","shell.execute_reply":"2023-01-17T14:43:58.606710Z"}}
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#|export
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learn = load_learner('/minima/model.pkl')
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# %% [code] {"execution":{"iopub.status.busy":"2023-01-17T14:45:36.880658Z","iopub.execute_input":"2023-01-17T14:45:36.881241Z","iopub.status.idle":"2023-01-17T14:45:36.890302Z","shell.execute_reply.started":"2023-01-17T14:45:36.881102Z","shell.execute_reply":"2023-01-17T14:45:36.889172Z"}}
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labels = learn.dls.vocab
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def predict(img):
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img = PILImage.create(img)
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pred,pred_idx,probs = learn.predict(img)
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return {labels[i]: float(probs[i]) for i in range(len(labels))}
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# %% [code] {"execution":{"iopub.status.busy":"2023-01-17T14:46:08.717339Z","iopub.execute_input":"2023-01-17T14:46:08.717913Z","iopub.status.idle":"2023-01-17T14:46:15.759750Z","shell.execute_reply.started":"2023-01-17T14:46:08.717858Z","shell.execute_reply":"2023-01-17T14:46:15.758401Z"}}
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gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)
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