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from fastai.vision.all import *
import gradio as gr
# dependent function
# labeling function
def is_cat(x):
return x[0].isupper()
learn = load_learner('model.pkl')
categories = ('Dog', 'Cat')
# function to classify image
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.jpg', 'cat.jpg', 'dunno.jpg']
# gradio interface what kind of ouput
# input and output
# can provide some examples
# the gradio interface can take different kinds of inputs
intf = gr.Interface(fn=classify_image, inputs = image, outputs=label)#, examples = examples)
intf.launch(inline = False)
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