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from transformers import pipeline | |
import gradio as gr | |
def alz_mri_classification(image): | |
classifier = pipeline("image-classification", model="dewifaj/alzheimer_mri_classification") | |
result = classifier(image) | |
# extract the highest score | |
prediction = result[0] | |
score = prediction['score'] | |
label = prediction['label'] | |
return {"score": score, "label": label} | |
example_image_paths = ["Very_Mild_Demented.png", "Mild_Demented.png", "Moderate_Demented.png", "Non_Demented.png"] | |
image_input = gr.Image(type="pil", label="Upload Image") | |
iface = gr.Interface(fn=alz_mri_classification, | |
inputs=image_input, | |
outputs="json", | |
examples=[example_image_paths], | |
title="Alzheimer Recognition from MRI") | |
iface.launch() | |