Spaces:
Sleeping
Sleeping
let's deploy to huggingface spaces
Browse files
app.py
CHANGED
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import gradio as gr
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def greet(name):
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return "Hello " + name + "!!"
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iface = gr.Interface(fn=greet, inputs="text", outputs="text")
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iface.launch()
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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.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()
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