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from fastai.vision.all import *
import gradio as gr
def is_cat(x): return x[0].isupper()
learn = load_learner('model.pkl')
categories = ('Dog', 'Cat')
def classify_image(img):
pred,idx,probs = learn.predict(img)
return dict(zip(categories, map(float,probs)))
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ['dog.jpeg', 'cat.webp', 'cat1.jpeg']
# create gradio interface
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False) |