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from fastai.vision.all import *
import gradio as gr
def is_cat(x): return x[0].isupper()
import pathlib
temp = pathlib.PosixPath
pathlib.PosixPath = pathlib.WindowsPath
learner = load_learner('cat.pkl')
categories = ['Dog', 'Cat']
def classify_image(img):
pred,idx,probs = learner.predict(img)
return dict(zip(categories, map(float, probs)))
image = gr.Image(height=192, width=192)
labels = gr.Label()
examples = ['dog.jpg', 'cat.jpg']
intf = gr.Interface(fn=classify_image, inputs=image, outputs=labels, examples=examples)
intf.launch(inline=False) |