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from fastai import *
from fastai.vision.all import *
import gradio as gr
import pathlib
# def is_cat(x): return x[0].isupper()
# Ensure that the correct Path object is used here based on the OS
pathlib.PosixPath = pathlib.WindowsPath
learn = load_learner('export.pkl')
categories = ('black', 'grizzly', 'teddy')
def classify_image(img):
pred, idx, probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
image = gr.components.Image(type="pil", height=192, width=192)
label = gr.Label()
examples = ['bear.jpg', 'cat.jpg', 'dog.jpg']
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False) |