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import gradio as gr
from fastai.vision.all import *
import skimage
import pathlib
temp = pathlib.PosixPath
pathlib.PosixPath = pathlib.WindowsPath
learn = load_learner('eksport.pkl')
labels = learn.dls.vocab
def predict(img):
img = PILImage.create(img)
pred, pred_idx, probs = learn.predict(img)
return {labels[i]: float(probs[i]) for i in range(len(labels))}
title = 'Potato Disease Classifier'
description = 'A potato disease classifier trained on random images from internet with fastai. Created as a demo for Gradio and HuggingFace Spaces.'
examples = ['early_blight.JPG', 'healthy.JPG', 'late_blight.JPG']
gr.Interface(fn = predict,
inputs = 'image',
outputs = 'label',
title = title,
description = description,
examples = examples).launch()