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import gradio as gr
from transformers import pipeline
def predict_image(img):
img_4d=img.reshape(-1,180,180,3)
prediction=model.predict(img_4d)[0]
return {class_names[i]: float(prediction[i]) for i in range(4)}
pipe = pipeline(task = 'image-classification', model = "google/vit-base-patch16-224")
image = gr.inputs.Image(shape=(180,180))
label = gr.outputs.Label(num_top_classes=4)
gr.Interface.from_pipeline(pipe,
title = "Maize Leaf Disease Detection",
description = "Corn Leaf disease classification",
fn=predict_image, inputs=image, outputs=label,interpretation='default',
allow_flagging = "never").launch(inbrowser=True, debug='True', share='True')
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