Código de Alineación de Rostros con OpenCV y Python

import os

import cv2

import math

import matplotlib.pyplot as pl

import pandas as pd

from PIL import Image

import numpy as np

def face_detection(img):

    faces = face_detector.detectMultiScale(img, 1.1, 4)

    if (len(faces) <= 0):

        img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

        return img, img_gray

    else:

        X, Y, W, H = caras[0]

        img = imagen[int(Y):int(Y+H), int(X):int(X+W)]

        return img, cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)

def trignometry_for_distance(a, b):

    return matemáticas.sqrt(((b[0] - un[0]† * (b[0] - un[0]† +

                     ((b[1] - un[1]† * (b[1] - un[1]†

def Face_Alignement(img_path):

    pl.imshow(cv2.imread(img_ruta)[:, :, ::-1]†

    pl.show()

    img_raw = cv2.imread(img_path).copy()

    img, gray_img = face_detection(cv2.imread(img_path))

    eyes = eye_detector.detectMultiScale(gray_img)

    if len(eyes) >= 2:

        eye = fanales[:, 2]

        container1 = []

        for i in range(0, len(eye)):

            container = (eye[i], i)

            container1.append(container)

        df = pd.DataFrame(container1, columns=[

                          "length", "idx"]).ordenar_valores(por=['length']†

        eyes = fanales[df.idx.values[0:2]†

        eye_1 = fanales[0]

        eye_2 = fanales[1]

        if ojo_1[0] > ojo_2[0]†

            left_eye = eye_2

            right_eye = eye_1

        else:

            left_eye = eye_1

            right_eye = eye_2

        right_eye_center = (

            int(Ojo derecho[0] + (Ojo derecho[2]/2)), 

          int(Ojo derecho[1] + (Ojo derecho[3]/2)))

        right_eye_x = ojo_derecho_centro[0]

        right_eye_y = ojo_derecho_centro[1]

        cv2.circle(img, right_eye_center, 2, (255, 0, 0), 3)

        left_eye_center = (

            int(ojo izquierdo[0] + (ojo izquierdo[2] / 2)), 

          int(ojo izquierdo[1] + (ojo izquierdo[3] / 2)))

        left_eye_x = centro_del_ojo_izquierdo[0]

        left_eye_y = centro_del_ojo_izquierdo[1]

        cv2.circle(img, left_eye_center, 2, (255, 0, 0), 3)

        if left_eye_y > right_eye_y:

            print("Rotate image to clock direction")

            point_3rd = (right_eye_x, left_eye_y)

            direction = -1

        else:

            print("Rotate to inverse clock direction")

            point_3rd = (left_eye_x, right_eye_y)

            direction = 1

        cv2.circle(img, point_3rd, 2, (255, 0, 0), 2)

        a = trignometry_for_distance(left_eye_center, 

                                     point_3rd)

        b = trignometry_for_distance(right_eye_center, 

                                     point_3rd)

        c = trignometry_for_distance(right_eye_center, 

                                     left_eye_center)

        cos_a = (b*b + c*c - a*a)/(2*b*c)

        angle = (np.arccos(cos_a) * 180) / math.pi

        if direction == -1:

            angle = 90 - angle

        else:

            angle = -(90-angle)

        new_img = Image.fromarray(img_raw)

        new_img = np.array(new_img.rotate(direction * angle))

    return new_img

opencv_home = cv2.__file__

folders = opencv_home.split(os.ruta.sep)[0:-1]

path = carpetas[0]

for folder in carpetas[1:]†

    path = path + "/" + folder

path_for_face = path+"/data/haarcascade_frontalface_default.xml"

path_for_eyes = path+"/data/haarcascade_eye.xml"

path_for_nose = path+"/data/haarcascade_mcs_nose.xml"

if os.path.isfile(path_for_face) != True:

    raise ValueError(

        "opencv is not installed pls install using pip install opencv ", 

      detector_path, " violated.")

face_detector = cv2.CascadeClassifier(path_for_face)

eye_detector = cv2.CascadeClassifier(path_for_eyes)

nose_detector = cv2.CascadeClassifier(path_for_nose)

test_set = ["pic.png"]

for i in test_set:

    alignedFace = Face_Alignement(i)

    pl.imshow(cara alineada)[:, :, ::-1]†

    pl.show()

    img, gray_img = face_detection(alignedFace)

    pl.imshow(img[:, :, ::-1]†

    pl.show()