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import gradio as gr
from fastai.vision.all import *
def classify_img(img):
pred , idx , probs = learn.predict(img)
return dict(zip(categories , map(float , probs)))
import pathlib
plt = platform.system()
if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath
learn = load_learner('bears_model.pkl')
categories = ( 'black bear','grizzly bear' , 'teddy bear')
image = gr.inputs.Image(shape=(194,194))
label = gr.outputs.Label()
examples = [
'teddy_bear.jpg' ,
'grizzly_bear.jpg' ,
'black_bear.jpg'
]
intf = gr.Interface(fn = classify_img , inputs = image , outputs = label , examples = examples)
intf.launch(inline = False) |