datasciencedojo commited on
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  1. app.py +24 -0
  2. handpose.pkl +3 -0
  3. requirements.txt +1 -0
app.py ADDED
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+ __all__ = ['learn','classify_image','categories','image','label','examples','intf']
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+
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+ from fastai.vision.all import *
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+ import gradio as gr
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+
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+ # Cell
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+ learn = load_learner('handpose.pkl')
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+
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+ # Cell
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+ categories = ('call', 'dislike', 'fist', 'four', 'like', 'mute', 'ok', 'one', 'palm', 'peace',
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+ 'peace_inverted', 'rock', 'stop', 'stop_inverted', 'three', 'three2', 'two_up', 'two_up_inverted')
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+
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+ def classify_image(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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+
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+ # Cell
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+ image = gr.inputs.Image(shape=(192,192),source='webcam')
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+ label = gr.outputs.Label()
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+ #examples = ['beyonce-ok.jpg','dalai-lama-one.jpg']
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+
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+
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+ intf = gr.Interface(fn=classify_image, inputs=image, outputs=label)
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+ intf.launch(inline=False)
handpose.pkl ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:ae10ad0053e07306173de79a2fe67b1391edf5722d45ce1d6512de6b270073df
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+ size 47033899
requirements.txt ADDED
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+ fastai