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app.ipynb
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"categories = learn.dls.vocab\n",
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"def classify_dance(img):\n",
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"id": "04067853-7c15-4d1e-97e1-492bbf673e95",
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"id": "e509f89e-afaf-4113-b306-2c87ba47b3f5",
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"metadata": {
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" 9.5897e-01, 1.0382e-05]))"
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"id": "dce7eb50-5d6c-49ff-af40-38661c5a4382",
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"metadata": {
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"tags": []
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"outputs": [],
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"source": [
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"#|export\n",
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"categories = learn.dls.vocab\n",
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"\n",
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"def classify_dance(img):\n",
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"id": "9ac8e22b-fc1c-4c70-887a-c28ad297563d",
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"metadata": {
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"tags": []
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" 'sattriya': 1.0382239452155773e-05}"
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"id": "68faa281-c721-407a-87f5-dcdfce9cf55a",
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"metadata": {
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app.py
CHANGED
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# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
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# %% auto 0
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__all__ = ['learn', 'image', 'label', 'examples', 'intf']
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# %% app.ipynb 1
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from fastai.vision.all import *
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# %% app.ipynb 3
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learn = load_learner('model/indian_dance_forms_resnet50.pkl')
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# %% app.ipynb 7
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image = gr.inputs.Image(shape=(192,192))
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label = gr.outputs.Label()
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# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
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# %% auto 0
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__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'classify_dance']
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# %% app.ipynb 1
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from fastai.vision.all import *
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# %% app.ipynb 3
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learn = load_learner('model/indian_dance_forms_resnet50.pkl')
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# %% app.ipynb 5
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categories = learn.dls.vocab
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def classify_dance(img):
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pred,idx,probs = learn.predict(img)
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return dict(zip(categories, map(float,probs)))
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# %% app.ipynb 7
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image = gr.inputs.Image(shape=(192,192))
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label = gr.outputs.Label()
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