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from fastai.vision.all import*
import gradio as gr
from joblib import dump, load
import pathlib
plt = platform.system()
if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath
learn = load_learner('model.pkl')
im_bb = PILImage.create('samp_bb.jpg')
im_lf = PILImage.create('samp_lf.jpg')
im_other = PILImage.create('samp_other.jpg')
categories = ('bb', 'lf', 'other')
def classify_image(img):
pred, idx, probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
image = gr.Image(height=500, width=500)
label = gr.Label()
examples = ['samp_lf.jpg', 'samp_other.jpg']
intf= gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False) |