python人脸对齐——dlib+opencv

人脸对齐：利用dlib的模型可以识别出图片中的人脸，为方便后续处理，通常还需要把图片中的人脸截取出来并将倾斜的人脸处理成正常的姿态。imutils库中集成了一个人脸对齐的类 FaceAligner，我们直接使用它进行处理。FaceAligner的代码如下：

# import the necessary packages
from .helpers import FACIAL_LANDMARKS_68_IDXS
from .helpers import FACIAL_LANDMARKS_5_IDXS
from .helpers import shape_to_np
import numpy as np
import cv2


class FaceAligner:
    def __init__(self, predictor, desiredLeftEye=(0.35, 0.35),
                 desiredFaceWidth=256, desiredFaceHeight=None):
        # store the facial landmark predictor, desired output left
        # eye position, and desired output face width + height
        self.predictor = predictor
        self.desiredLeftEye = desiredLeftEye
        self.desiredFaceWidth = desiredFaceWidth
        self.desiredFaceHeight = desiredFaceHeight

        # if the desired face height is None, set it to be the
        # desired face width (normal behavior)
        if self.desiredFaceHeight is None:
            self.desiredFaceHeight = self.desiredFaceWidth

    def align(self, image, gray, rect):
        # convert the landmark (x, y)-coordinates to a NumPy array
        shape = self.predictor(gray, rect)
        shape = shape_to_np(shape)

        # simple hack ;)
        if (len(shape) == 68):
            # extract the left and right eye (x, y)-coordinates
            (lStart, lEnd) = FACIAL_LANDMARKS_68_IDXS["left_eye"]
            (rStart, rEnd) = FACIAL_LANDMARKS_68_IDXS["right_eye"]
        else:
            (lStart, lEnd) = FACIAL_LANDMARKS_5_IDXS["left_eye"]
            (rStart, rEnd) = FACIAL_LANDMARKS_5_IDXS["right_eye"]

        leftEyePts = shape[lStart:lEnd]
        rightEyePts = shape[rStart:rEnd]

        # compute the center of mass for each eye
        leftEyeCenter = leftEyePts.mean(axis=0).astype("int")
        rightEyeCenter = rightEyePts.mean(axis=0).astype("int")

        # compute the angle between the eye centroids
        dY = rightEyeCenter[1] - leftEyeCenter[1]
        dX = rightEyeCenter[0] - leftEyeCenter[0]
        angle = np.degrees(np.arctan2(dY, dX)) - 180

        # compute the desired right eye x-coordinate based on the
        # desired x-coordinate of the left eye
        desiredRightEyeX = 1.0 - self.desiredLeftEye[0]

        # determine the scale of the new resulting image by taking
        # the ratio of the distance between eyes in the *current*
        # image to the ratio of distance between eyes in the
        # *desired* image
        dist = np.sqrt((dX ** 2) + (dY ** 2))
        desiredDist = (desiredRightEyeX - self.desiredLeftEye[0])
        desiredDist *= self.desiredFaceWidth
        scale = desiredDist / dist

        # compute center (x, y)-coordinates (i.e., the median point)
        # between the two eyes in the input image
        eyesCenter = ((leftEyeCenter[0] + rightEyeCenter[0]) // 2,
                      (leftEyeCenter[1] + rightEyeCenter[1]) // 2)

        # grab the rotation matrix for rotating and scaling the face
        M = cv2.getRotationMatrix2D(eyesCenter, angle, scale)

        # update the translation component of the matrix
        tX = self.desiredFaceWidth * 0.5
        tY = self.desiredFaceHeight * self.desiredLeftEye[1]
        M[0, 2] += (tX - eyesCenter[0])
        M[1, 2] += (tY - eyesCenter[1])

        # apply the affine transformation
        (w, h) = (self.desiredFaceWidth, self.desiredFaceHeight)
        output = cv2.warpAffine(image, M, (w, h),
                                flags=cv2.INTER_CUBIC)

        # return the aligned face
        return output

详细说明可参考文章：https://www.pyimagesearch.com/2017/05/22/face-alignment-with-opencv-and-python/

代码如下：

from imutils.face_utils import FaceAligner
from imutils.face_utils import rect_to_bb
import imutils
import dlib
import cv2
import sys


def _help():
    print("Usage:")
    print("     python face_align.py ")
    print("For example:")
    print("     python face_align.py pic/HL.jpg")


def face_align(img_path):
    detector = dlib.get_frontal_face_detector()
    predictor = dlib.shape_predictor("model/shape_predictor_68_face_landmarks.dat")
    
    # 初始化 FaceAligner 类对象
    fa = FaceAligner(predictor, desiredFaceWidth=256)

    image = cv2.imread(img_path)
    image = imutils.resize(image, width=600)
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

    cv2.imshow("Input", image)
    rects = detector(gray, 2)
    for rect in rects:
        (x, y, w, h) = rect_to_bb(rect)
        face_orig = imutils.resize(image[y:y + h, x:x + w], width=256)
   
        # 调用 align 函数对图像中的指定人脸进行处理
        face_aligned = fa.align(image, gray, rect)
        cv2.imshow("Original", face_orig)
        cv2.imshow("Aligned", face_aligned)
        cv2.waitKey(0)


if len(sys.argv) == 1 or "-h" in sys.argv or "--help" in sys.argv:
    _help()
else:
    face_align(sys.argv[1])

实现效果：

        

不管哪个角度看都很美~