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from fastai.vision.all import *
import gradio as gr
def hello(name):
return 'Hello ' + name
def bye(name):
return 'Bye ' + name
def cat_vs_dog(image):
learn = load_learner('cat-vs-dog.pkl')
image = PILImage.create(image)
label, index, probabilities = learn.predict(image)
# Create a dictionary with class label as the key and probability as value.
return dict(zip(learn.dls.vocab, probabilities.tolist()))
def fish_vs_face(image):
learn = load_learner('fish-vs-face.pkl')
image = PILImage.create(image)
label, index, probabilities = learn.predict(image)
# Create a dictionary with class label as the key and probability as value.
return dict(zip(learn.dls.vocab, probabilities.tolist()))
hello_world = gr.Interface(fn=hello, inputs='text', outputs='text')
bye_world = gr.Interface(fn=bye, inputs='text', outputs='text')
cat_vs_dog_interface = gr.Interface(fn=cat_vs_dog, inputs='image', outputs='label')
fish_vs_face_interface = gr.Interface(fn=fish_vs_face, inputs='webcam', outputs='label')
demo = gr.TabbedInterface([hello_world, bye_world, cat_vs_dog_interface, fish_vs_face_interface], ['Hello', 'Bye', 'Cat vs Dog', 'Fish vs Face'])
if __name__ == '__main__':
demo.launch()
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