人脸识别有趣应用1——给自己带上胡子墨镜和帽子

前言

最近发现了一个好用的人脸识别python库，能够较为快速准确的识别人脸，并且能够识别出人脸的9个特征部位的特征点，包括：眉毛、眼睛、鼻子、嘴唇等，可以利用这个库结合笔者的实用工具集，加上一些逻辑运算，可以玩出各种花样。本次，我们来给人脸加上胡子、墨镜和帽子，效果如下：

基本原理

利用人脸识别库（face_recognition）逐帧识别摄像头的图像，获得人脸的左右眼眼睛，上嘴唇的特征点坐标系列，计算得到左右眼的中心，用opencv画出两个圆形，并用直线连接起来就成了一幅墨镜；再更具眼睛中心坐标在头上画椭圆就加了个帽子；胡子的画法：
利用ps画出想要的胡子形状，并保存为png透明背景格式，然后通过带alpha通道的操作，将胡子加载调整大小后，与当前的帧相叠加，就完成了初步效果。

Python源码

# -*- coding: utf-8 -*-
"""
Created on Thu Mar 31 18:12:53 2022
@author: JAMES FEI 
Copyright (C) 2022 FEI PANFENG, All rights reserved.
THIS SOFTEWARE, INCLUDING DOCUMENTATION,IS PROTECTED BY COPYRIGHT CONTROLLED 
BY FEI PANFENG ALL RIGHTS ARE RESERVED.

"""

# -*- coding: utf-8 -*-
"""
Created on Thu Mar 31 15:58:32 2022

@author: Administrator
"""

import face_recognition
import cv2
import numpy as np

video_capture = cv2.VideoCapture(0)

process_this_frame = True
 #载入胡子，带透明通道
huzi = cv2.imread('huzi.png', cv2.IMREAD_UNCHANGED)
ratio=1/4
huzi = cv2.resize(huzi, (int(huzi.shape[1]*ratio),int(huzi.shape[0]*ratio)), interpolation=cv2.INTER_LINEAR)

def putonhuzi(huzi,backimg,leftup):  
    
    #print(leftup)
    x1 = leftup[0]
    if x1<0:
        x1=0
    y1 = leftup[1]
    if y1<0:
        y1=0
    x2 = x1 + huzi.shape[1]
    y2 = y1 + huzi.shape[0] 
    usy=huzi.shape[0] 
    usx=huzi.shape[1]
    
    if x2>backimg.shape[1]:
        x2=backimg.shape[1]
        usx=backimg.shape[1]-x1
        
    if y2>backimg.shape[0]:
        y2=backimg.shape[1]
        usy=backimg.shape[0]-y1
    
    
    if backimg.shape[2] == 3:       
        b, g, r = cv2.split(backimg) 
        alpha = np.ones(b.shape, dtype=b.dtype) * 255 # 创建Alpha通道 
        backimg = cv2.merge((b, g, r, alpha))
 
    alpha_huzip = huzi[:usy,:usx,3] / 255.0
    alpha_huzij = 1 - alpha_huzip

    for c in range(0,3):
        backimg[y1:y2, x1:x2, c] = ((alpha_huzij*backimg[y1:y2,x1:x2,c]) + (alpha_huzip*huzi[:usy,:usx,c]))
    
    
    return backimg[:,:,:3]


while True:
    ret, frame = video_capture.read()

    small_frame = cv2.resize(frame, (0, 0), fx=1/4, fy=1/4)

    rgb_frame = small_frame[:, :, ::-1]

    if process_this_frame: 
        face_landmarks_list = face_recognition.face_landmarks(rgb_frame)
        for face_landmarks in face_landmarks_list:
        #打印此图像中每个面部特征的位置
            facial_features = [
                    
                    'chin',
                    'left_eyebrow',
                    'right_eyebrow',
                    'nose_bridge',
                    'nose_tip',
                    'left_eye',
                    'right_eye',
                    'top_lip',
                    'bottom_lip'
            ]


    lef_center_x=0
    lef_center_y=0
    
    for point in face_landmarks["left_eye"]:
            lef_center_x+=point[0]*4
            lef_center_y+=point[1]*4
    lef_center_x=int(lef_center_x/len(face_landmarks["left_eye"]))
    lef_center_y=int(lef_center_y/len(face_landmarks["left_eye"]))
    cv2.circle(frame, (lef_center_x,lef_center_y), 30, (0,0,0), -1)  
    rig_center_x=0
    rig_center_y=0
    
    for point in face_landmarks["right_eye"]:
            rig_center_x+=point[0]*4
            rig_center_y+=point[1]*4
    rig_center_x=int(rig_center_x/len(face_landmarks["left_eye"]))
    rig_center_y=int(rig_center_y/len(face_landmarks["left_eye"]))
    cv2.circle(frame, (rig_center_x,rig_center_y), 30, (0,0,0), -1)     
    cv2.line(frame, (rig_center_x,rig_center_y),(lef_center_x,lef_center_y), (0,0,0), 4)  
    cv2.ellipse(frame,(int((rig_center_x+lef_center_x)/2),int((rig_center_y+lef_center_y)/2-80)),(200,50),0,0,360, (0,0,0),-1)
    
    cv2.ellipse(frame,(int((rig_center_x+lef_center_x)/2),int((rig_center_y+lef_center_y)/2-100)),(90,60),0,0,360, (0,0,0),-1)
    
    top_lip_x=0
    top_lip_y=0
    
    for point in face_landmarks["top_lip"]:
        top_lip_x+=point[0]*4
        top_lip_y+=point[1]*4
    
    top_lip_x= int(top_lip_x/len(face_landmarks["top_lip"]))   
    top_lip_y= int(top_lip_y/len(face_landmarks["top_lip"]))  
    ouput=putonhuzi(huzi,frame,(top_lip_x-int(huzi.shape[1]/2),top_lip_y-20))

    cv2.imshow('huzi', ouput)

    # 按Q退出
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

video_capture.release()
cv2.destroyAllWindows()