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from fastai.vision.all import *
import gradio as gr
import pathlib
plt = platform.system()
if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath
modelPath = Path('model.pkl')
learn = load_learner(modelPath)
categories = ('0', '1', '2', '3', '4', '5', '6', '7', '8', '9')
def classify_image(img):
pred,idx,probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
image = gr.inputs.Image(shape=(28,28))
label = gr.outputs.Label()
examples = ['img_0.jpg', 'img_1.jpg', 'img_2.jpg', 'img_4.jpg', 'img_7.jpg']
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False) |