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Parent(s):
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Upload 5 Files
Browse files- app.py +20 -0
- dogs_cats.ipynb +0 -0
- model.pkl +3 -0
- requirements.txt +3 -0
- siamese.jpeg +0 -0
app.py
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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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learn = load_learner('export.pkl')
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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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title = "Pet Breed Classifier"
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description = "A pet breed classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces."
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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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gr.Interface(fn=predict, inputs=gr.Image(height = 512, width = 512), outputs=gr.Label(num_top_classes=3)).launch(share=True)
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dogs_cats.ipynb
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model.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:34a219550af3263a28e3c5608e558e8432bda00e3e02af6e768bde1111cde8d6
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size 47062910
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requirements.txt
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fastai==2.7.13
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gradio==4.12.0
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skimage==0.0
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siamese.jpeg
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