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from fastai.vision.all import *
import gradio as gr
# Cargamos el learner
learn = load_learner('export.pkl')
# Definimos las etiquetas de nuestro modelo
labels = learn.dls.vocab
# Definimos una función que se encarga de llevar a cabo las predicciones
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))}
# Establecemos el título de la App y también indicamos
title = "Blindness Classifier"
description = "A Diabetic Retinopathy disease (DR) classifier trained on a Retine Image dataset with fastai. It classifies 5 degrees in the advance of the disease ranging from: [0]-No DR, [1]-Mild DR, [2]-Moderate DR, [3]-Severe DR y [4]-Proliferative DR"
# Creamos la interfaz y la lanzamos.
gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(320, 320)), outputs=gr.outputs.Label(num_top_classes=5), title=title, description=description, examples=['f576e45d1da2.png','1df0a4c23c95.png']).launch(share=False)
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