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import gradio as gr
from fastai.vision.all import *
# load model
learn = load_learner('./model.pkl')
categories = ('CLEAR', 'PNEUMONIA')
def classify_image(img):
pred, idx, probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
examples = ['./unseen_data/NORMAL/NORMAL2-IM-1427-0001.jpeg',
'./unseen_data/PNEUMONIA/person1946_bacteria_4874.jpeg',
'./unseen_data/NORMAL/NORMAL2-IM-1430-0001.jpeg',
'./unseen_data/PNEUMONIA/person1946_bacteria_4875.jpeg']
title = 'Pneumonia Child Chest X-Ray Classifier'
description = """An X-Ray classifier trained on the Children Chest X-Ray Images."""
article="""
<p>License: CC BY 4.0</p><br
<p><a href='http://www.cell.com/cell/fulltext/S0092-8674(18)30154-5' target='_blank'>Citation: Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning</a></p><br>
<p><a href='https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia' target='_blank'>Kaggle Dataset</a></p><br>
<p>Trained using the fast.ai library</p>
"""
intf = gr.Interface(fn=classify_image,
inputs=gr.Image(type='pil'),
outputs=gr.Label(),
examples=examples,
title = title,
description = description,
article = article)
intf.launch(inline=False, share=True) |