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from fastai.vision.all import *
import gradio as gr
def label_func(f): return f[0] == 'p'
def acc_camvid(*_): pass
def get_y(*_): pass
learner = load_learner('my_export.pkl')
categories = ('Poison Ivy', 'Not Poison Ivy')
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 = ["pepe.jpg"]
demo = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
demo.launch(inline=False)
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