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# !conda install conda=23.7.3 -y

# !nbdev_migrate

#|export
# !pip install gradio

#|export
from fastai.vision.all import *
import gradio as gd

im = PILImage.create('car.jpg')
im.thumbnail((192,192))
im

#|export
learn = load_learner('export.pkl')

# %time learn.predict(im)

# +
#|export
categories = ('car','motorbike')

def classify_images(img):
    pred,idx,probs = learn.predict(img)
    return dict(zip(categories,map(float,probs)))


# -

classify_images(im)

# +
#|export
image = gd.inputs.Image(shape=(192,192))
label = gd.outputs.Label()
examples = ['car.jpg','bike.jpg']

intf = gd.Interface(fn = classify_images,inputs = image, outputs = label, examples = examples)
intf.launch(inline=False)