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Ok, estoy en  medio de la redacción de la serie de artículos intentando dar una visión para aprendices (básica y funcional, sobre todo) de Open CV en Python, y una de las cosas que quiero explicar en ella es la posibilidad de trabajar con librerías haarcascade que pueden detectar e incluso reconocer rasgos faciales. Como eso puede alargarse en el tiempo, y yo ahora mismo tengo que recoger a mis chiquillas del cole, no quiero dejar pasar la oportunidad de mostraros el código que podéis implementar para hacer esta tontuna:

 

 

 

Es una chorradica, pero espectacular. La idea es ir revisando las imágenes que envía la webcam, y si en algún momento detecta un rostro, recuadrarlo con un rectángulo, y reducir el tamaño de la ventana para que encaje con dicho rectángulo. Dicho de otro modo: tenemos una ventana dinámica que se redimensiona según acerquemos o alejemos nuestros jetos de la webcam.

 

Ya te digo que ando algo corto de tiempo. Aquí os dejo el código para que trasteéis. Cualquier duda, tiráis de comentario o me venís al Twitter: www.twitter.com/antoniotecnocr

 

import numpy as np
import cv2

cap = cv2.VideoCapture(0)
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')



while(True):
    imagen=cv2.imread('logoOriginal.jpg')
    ret, frame = cap.read()

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    for (x,y,w,h) in faces:
        cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),2)
        roi=frame[x:x+w,y:y+h]
        

   
    cv2.imshow('frame',roi)
    if cv2.waitKey(1) &0xFF == ord('q'):
        break


cap.release()
cv2.destroyAllWindows()

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