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  1. app.py +22 -0
  2. export.pkl +3 -0
  3. golden-retriever-dog-21668976.jpg +0 -0
  4. requirements.txt +2 -0
app.py ADDED
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+ import gradio as gr
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+ from fastai.vision.all import *
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+ import skimage
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+
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+ learn = load_learner('export.pkl')
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+
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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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+
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+ title = "์• ์™„๋™๋ฌผ ํ’ˆ์ข… ๋ถ„๋ฅ˜๊ธฐ"
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+ description = "fastai๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ Oxford Pets ๋ฐ์ดํ„ฐ ์„ธํŠธ์—์„œ ํ›ˆ๋ จ๋œ ์• ์™„ โ€‹โ€‹๋™๋ฌผ ํ’ˆ์ข… ๋ถ„๋ฅ˜๊ธฐ์ž…๋‹ˆ๋‹ค. Gradio์™€ HuggingFace Spaces ๋ฐ๋ชจ๋กœ ์ œ์ž‘๋˜์—ˆ์Šต๋‹ˆ๋‹ค."
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+ #article="<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Blog post</a></p>"
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+ examples = ['siamese.jpg']
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+ interpretation='default'
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+ enable_queue=True
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+
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+ gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,
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+ #article=article,
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+ examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()
export.pkl ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:55f77d239cd8e1b9088d9413dd271f75d37855443dcf2f6953605fde43241bb0
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+ size 103045373
golden-retriever-dog-21668976.jpg ADDED
requirements.txt ADDED
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+ fastai
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+ scikit-image