from kivy.app import App
from kivy.uix.button import Button
from kivy.uix.image import Image
from kivy.uix.floatlayout import FloatLayout
from kivy.graphics.texture import Texture
from kivy.clock import Clock
import numpy as np
import cv2
from playsound import playsound
from keras.models import load_model
import speech_recognition as sr

### este main.py necesita "test.py", "keras_model.h5" y "label.text"




model = load_model('keras_model.h5')
labels = open('labels.txt', 'r').readlines()

cont = 0

aux = ['nada', 'mil','dos mil', 'cinco mil']



class MainApp(App):

    def build(self):
        global text
        layout = FloatLayout(size=(300, 300))
        self.image = Image()
        layout.add_widget(self.image)
        layout.add_widget(Button(
            opacity=0,
            on_release=self.on_press_button)
        )
        self.capture = cv2.VideoCapture(0)

        Clock.schedule_interval(self.load_video, 1.0/60.0)
        return layout

    def load_video(self, *args):
            global probabilities
            ret, frame = self.capture.read()
            image = frame.copy()
            image = cv2.resize(image, (224, 224), interpolation=cv2.INTER_AREA)
            image = np.asarray(image, dtype=np.float32).reshape(1, 224, 224, 3)
            image = (image / 127.5) - 1
            probabilities = model.predict(image)
            cv2.putText(frame, f'{aux[np.argmax(probabilities)]}', (5, 30), cv2.FONT_ITALIC, 1, (255, 0, 255), 2, cv2.LINE_AA)
            cv2.putText(frame, f'{cont}', (5, 450), cv2.FONT_ITALIC, 1, (255, 0, 255), 2,
                        cv2.LINE_AA)
            self.image_frame = frame
            buffer = cv2.flip(frame, 0).tostring()
            texture = Texture.create(size=(frame.shape[1], frame.shape[0]), colorfmt='bgr')
            texture.blit_buffer(buffer, colorfmt='bgr', bufferfmt='ubyte')
            self.image.texture = texture





    def on_press_button(self, *args):
            global cont

            r = sr.Recognizer()
            with sr.Microphone() as source:
                audio = r.listen(source)

                try:
                    text = r.recognize_google(audio, language='es-ES')
                    if text == 'contar':
                        if np.argmax(probabilities) == 1:
                            playsound('mil pesos.mp3')
                            cont += 1

                        elif np.argmax(probabilities) == 2:
                            playsound('2.mp3')
                            playsound('mil pesos.mp3')
                            cont += 2

                        elif np.argmax(probabilities) == 3:
                            playsound('5.mp3')
                            playsound('mil pesos.mp3')
                            cont += 5

                        else:
                            playsound('enfocar.mp3')
                        return 0
                    elif text == 'total':
                        if cont == 1:
                            playsound('mil pesos.mp3')

                        elif cont < 16 and cont > 0:
                            playsound('{}.mp3'.format(cont))
                            playsound('mil pesos.mp3')
                        elif cont != 0 and (cont % 10) == 0 and cont < 60:
                            playsound('{}.mp3'.format(cont))
                            playsound('mil pesos.mp3')
                        elif cont != 0:
                            aux = cont % 10
                            digito = cont - aux
                            playsound('{}.mp3'.format(digito))
                            playsound('y.mp3')
                            playsound('{}.mp3'.format(aux))
                            playsound('mil pesos.mp3')
                        else:
                            playsound('enfocar.mp3')

                        return 0
                    elif text == 'borrar':
                        cont = 0
                    else:
                        return 0
                except:
                    return 0








if __name__ == '__main__':
    MainApp().run()