import gradio as gr
from fastai.vision.all import *
import skimage


def get_volumen(): return 0

learn1 = load_learner('resnetrs50VolumenHeight.pkl')
learn2 = load_learner('efficientnetv2_rw_s_volumen_height.pkl')
learn3 = load_learner('efficientnetv2_rw_s_Volumen.pkl')



def predict(Imagen_Ortophoto,Imagen_Altura):
    imgOrtophoto = PILImage.create(Imagen_Ortophoto)
    imgAltura = PILImage.create(Imagen_Altura)
    _,pred1,_ = learn1.predict(imgAltura)
    _,pred2,_ = learn1.predict(imgAltura)
    _,pred3,_ = learn3.predict(imgOrtophoto)
    return (pred1[0]+pred2[0]+pred3[0])/3

title = "Cálculo de volumen de silos"
description = "Demo para el proyecto SEPARA."
examples = [['ortophoto1.jpg','altura1.jpg'],['ortophoto2.jpg','altura2.jpg']]
interpretation='default'
enable_queue=True

gr.Interface(fn=predict,inputs=[gr.inputs.Image(shape=(224,224)),gr.inputs.Image(shape=(224,224))],outputs=gr.outputs.Textbox(label="volumen"),title=title,description=description,examples=examples,enable_queue=enable_queue).launch()