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from fastai.vision.all import *
import gradio as gr
def is_cat(x): return x[0].isupper()
# cell
learn = load_learner('model.pkl')
# cell
categories = ['Cat', 'Dog']
def classify_image(img):
pred,idx,probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
# cell
#image = gr.inputs.image(shape=(192, 192))
#label = gr.outputs.Label()
#examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']
intf = gr.Interface(fn=classify_image, inputs="image", outputs="label")
#intf = gr.Interface(fn=classify_image, inputs="image", outputs="label", examples="examples")
intf.launch(inline=False)
#cell
#import gradio as gr
#gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)
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