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import gradio as gr
from fastai.vision.all import *
from glob import glob
learn_inf = load_learner('model.pkl')
categories = ("Decease", "Healthy")
def classify(img):
pred, pred_idx, probs = learn_inf.predict(img)
return dict(zip(categories, map(float, probs)))
image = gr.inputs.Image(shape=(224, 224))
label = gr.outputs.Label()
examples = glob("*.jpg")
title = "Strawberry Leaves Decease Classifier"
description = "This classifier was trained on the ['Image Dataset for Tipburn Disorder Detection in Strawberry Leaves'](https://data.mendeley.com/datasets/trwfmgjjr6/1) and it is designed to help you detect weather straberry leaves are infected or not."
interpretation='default'
iface = gr.Interface(fn=classify, inputs=image, outputs=label, examples=examples,
title=title, description=description, interpretation=interpretation)
iface.launch(enable_queue=True)
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