1，介紹

開始之前，向大家提前說聲抱歉，上一篇文章末尾提到了，在這篇文章將給大家介紹關于用 OpenCV 實現(xiàn)人臉融合技術，由于人臉融合技術所需的知識儲備有點多，不只是之前介紹的的特征點提取，還有本文所提到的三角剖分，因此文章會向后面推遲一點，但請大家放心，人臉融合技術一定會在隨后的幾篇文章安排上日程。

看到標題里的兩個詞 Delaunay 三角剖分 和 Voronoi，估計第一次見到的小伙伴可能一臉懵(說的就是我自己)，為了更直觀地認識這兩個概念，請看下圖：

左圖：68個人臉特征點 中圖：Delaunay 三角剖分，右圖 Voronoi 圖表

左圖是上篇文章提到的 68個人臉特征點標記，中圖是基于左圖的基礎上對 68個點進行 點與點之間形成 Delaunay 三角剖分(德勞內)，左圖是基于中間圖繪制的的 Voronoi Diagram (沃羅諾伊圖)

2，Delaunay 三角剖分

Delaunay 三角剖分算法命名那個來源于俄國數(shù)學家 Boris Delaunay，該方法目的是最大化三角剖分中三角形中最小角，目的是避免“極瘦“的三角形的出現(xiàn)

Snipaste_2020-06-04_15-23-46.png

上方左圖與右圖的變換站示的就是 Delaunay 怎樣最大化最小角，左右兩圖是對于四個頂點的兩種不同的剖分方式；但左圖中 頂點 A、C 不在三角形 BCD、ABD 的外接圓內，使得 角 C 非常大

右圖對剖分形式有兩個方的 改動：1，B、D 坐標右移；2，剖分線由 BD 變?yōu)?AC ；最后使得剖分后的三角形不那么”瘦“

3，Voronoi Diagram

Voronoi 命名同樣也是來源于一個 俄國數(shù)學家 Georgy Voronoy，有趣的是 Georgy Voronoy 是 Boris Delaunay 的博士導師

Voronoi 圖是基于 Delaunay 三角剖分創(chuàng)建，取 Delaunay 剖分的所有頂點，用線段連接相鄰三角形的外接圓心，構成一個區(qū)域，相鄰不同區(qū)域用不同顏色覆蓋；Voronoi 圖目前常用于凸邊形區(qū)域分割領域

從下面20個頂點組成的 Voronoi 圖種可以了解到，圖中相鄰點與點之間的距離是等長的

20個頂點構成的 Voronoi

4，OpenCV 代碼實現(xiàn)

1，首先需要獲取人臉 68 個特征點坐標，并寫入 txt 文件，方便后面使用,這里會用到的代碼

import dlib
import cv2

predictor_path  = "E:/data_ceshi/shape_predictor_68_face_landmarks.dat"
png_path = "E:/data_ceshi/timg.jpg"

txt_path = "E:/data_ceshi/points.txt"
f = open(txt_path,'w+')


detector = dlib.get_frontal_face_detector()
#相撞
predicator = dlib.shape_predictor(predictor_path)
win = dlib.image_window()
img1 = cv2.imread(png_path)


dets = detector(img1,1)
print("Number of faces detected : {}".format(len(dets)))
for k,d in enumerate(dets):
    print("Detection {}  left:{}  Top: {} Right {}  Bottom {}".format(
        k,d.left(),d.top(),d.right(),d.bottom()
    ))
    lanmarks = [[p.x,p.y] for p in predicator(img1,d).parts()]
    for idx,point in enumerate(lanmarks):
        f.write(str(point[0]))
        f.write("\t")
        f.write(str(point[1]))
        f.write('\n')

寫入后，txt 中格式如下

image

2，利用圖像大小創(chuàng)建一個矩形范圍( 因為臉部特征點都是圖中)，創(chuàng)建一個 Subdiv2D 實例(后面兩個圖的繪制都會用到這個類)，把點都插入創(chuàng)建的類中：

 #Create an instance of Subdiv2d
    subdiv = cv2.Subdiv2D(rect)
    #Create an array of points
    points = []
    #Read in the points from a text file
    with open("E:/data_ceshi/points.txt") as file:
        for line in file:
            x,y = line.split()
            points.append((int(x),int(y)))
    #Insert points into subdiv
    for p in points:
        subdiv.insert(p)

3，在原圖上繪制 Delaunay 三角剖分并預覽，這里我加入了動畫效果 — 逐線段繪制(用了 for 循環(huán))

#Draw delaunay triangles
def draw_delaunay(img,subdiv,delaunay_color):
    trangleList = subdiv.getTriangleList()
    size = img.shape
    r = (0,0,size[1],size[0])
    for t in  trangleList:
        pt1 = (t[0],t[1])
        pt2 = (t[2],t[3])
        pt3 = (t[4],t[5])
        if (rect_contains(r,pt1) and rect_contains(r,pt2) and rect_contains(r,pt3)):
            cv2.line(img,pt1,pt2,delaunay_color,1)
            cv2.line(img,pt2,pt3,delaunay_color,1)
            cv2.line(img,pt3,pt1,delaunay_color,1)
            
 #Insert points into subdiv
    for p in points:
        subdiv.insert(p)

        #Show animate
        if animate:
            img_copy = img_orig.copy()
            #Draw delaunay triangles
            draw_delaunay(img_copy,subdiv,(255,255,255))
            cv2.imshow(win_delaunary,img_copy)
            cv2.waitKey(100)

預覽效果如下：

imag11252323.gif

4，最后繪制 Voronoi Diagram

 def draw_voronoi(img,subdiv):
    (facets,centers) = subdiv.getVoronoiFacetList([])

    for i in range(0,len(facets)):
        ifacet_arr = []
        for f in facets[i]:
            ifacet_arr.append(f)

        ifacet = np.array(ifacet_arr,np.int)
        color = (random.randint(0,255),random.randint(0,255),random.randint(0,255))
        cv2.fillConvexPoly(img,ifacet,color)
        ifacets = np.array([ifacet])
        cv2.polylines(img,ifacets,True,(0,0,0),1)
        cv2.circle(img,(centers[i][0],centers[i][1]),3,(0,0,0))
    
  for p in points:
        draw_point(img,p,(0,0,255))

  #Allocate space for Voroni Diagram
  img_voronoi = np.zeros(img.shape,dtype = img.dtype)

  #Draw Voonoi diagram
  draw_voronoi(img_voronoi,subdiv)

Snipaste_2020-06-04_14-43-10.png

4，小總結

Delaunay 三角剖分對于第一次接觸的小伙伴來說可能還未完全理解，但這一剖分技術對于做人臉識別、融合、換臉是不可或缺的，本篇文章只是僅通過 OpenCV 的 Subdiv2D 函數(shù)下實現(xiàn)此功能，真正的識別技術要比這個復雜地多。

對于感興趣的小伙伴們，我的建議還是跟著提供的代碼敲一遍，完整代碼貼在下面：

import cv2
import numpy as np
import random

#Check if a point is insied a rectangle
def rect_contains(rect,point):
    if point[0] <rect[0]:
        return False
    elif point[1]<rect[1]:
        return  False
    elif point[0]>rect[2]:
        return False
    elif point[1] >rect[3]:
        return False
    return True

# Draw a point
def draw_point(img,p,color):
    cv2.circle(img,p,2,color)

#Draw delaunay triangles
def draw_delaunay(img,subdiv,delaunay_color):
    trangleList = subdiv.getTriangleList()
    size = img.shape
    r = (0,0,size[1],size[0])
    for t in  trangleList:
        pt1 = (t[0],t[1])
        pt2 = (t[2],t[3])
        pt3 = (t[4],t[5])
        if (rect_contains(r,pt1) and rect_contains(r,pt2) and rect_contains(r,pt3)):
            cv2.line(img,pt1,pt2,delaunay_color,1)
            cv2.line(img,pt2,pt3,delaunay_color,1)
            cv2.line(img,pt3,pt1,delaunay_color,1)

# Draw voronoi diagram
def draw_voronoi(img,subdiv):
    (facets,centers) = subdiv.getVoronoiFacetList([])

    for i in range(0,len(facets)):
        ifacet_arr = []
        for f in facets[i]:
            ifacet_arr.append(f)

        ifacet = np.array(ifacet_arr,np.int)
        color = (random.randint(0,255),random.randint(0,255),random.randint(0,255))
        cv2.fillConvexPoly(img,ifacet,color)
        ifacets = np.array([ifacet])
        cv2.polylines(img,ifacets,True,(0,0,0),1)
        cv2.circle(img,(centers[i][0],centers[i][1]),3,(0,0,0))


if __name__ == '__main__':
    #Define window names;
    win_delaunary = "Delaunay Triangulation"
    win_voronoi = "Voronoi Diagram"

    #Turn on animations while drawing triangles
    animate = True

    #Define colors for drawing
    delaunary_color = (255,255,255)
    points_color = (0,0,255)

    #Read in the image
    img_path = "E:/data_ceshi/timg.jpg"

    img = cv2.imread(img_path)

    #Keep a copy   around
    img_orig = img.copy()

    #Rectangle to be used with Subdiv2D
    size = img.shape
    rect = (0,0,size[1],size[0])

    #Create an instance of Subdiv2d
    subdiv = cv2.Subdiv2D(rect)
    #Create an array of points
    points = []
    #Read in the points from a text file
    with open("E:/data_ceshi/points.txt") as file:
        for line in file:
            x,y = line.split()
            points.append((int(x),int(y)))
    #Insert points into subdiv
    for p in points:
        subdiv.insert(p)

        #Show animate
        if animate:
            img_copy = img_orig.copy()
            #Draw delaunay triangles
            draw_delaunay(img_copy,subdiv,(255,255,255))
            cv2.imshow(win_delaunary,img_copy)
            cv2.waitKey(100)

    #Draw delaunary triangles
    draw_delaunay(img,subdiv,(255,255,255))

    #Draw points
    for p in points:
        draw_point(img,p,(0,0,255))

    #Allocate space for Voroni Diagram
    img_voronoi = np.zeros(img.shape,dtype = img.dtype)

    #Draw Voonoi diagram
    draw_voronoi(img_voronoi,subdiv)

    #Show results
    cv2.imshow(win_delaunary,img)
    cv2.imshow(win_voronoi,img_voronoi)
    cv2.waitKey(0)

參考鏈接：

https://www.learnopencv.com/