基于Python+OpenCV的人脸识别实现带墨镜效果

相关介绍

你好！ 项目起初来源于一本科生的毕业设计，由于我给了一版更加优秀，所以初始版本的例子给予分享。其中可能最难的地方就在于环境配置，其他的要求基本没啥。对了可以随意的添加你想要的图片效果，就在文件夹里替换就行。本次代码也是基于这个大佬的文章

https://www.makeartwithpython.com/blog/deal-with-it-generator-face-recognition/

环境配置

起初Opencv就不是为了Python所使用的，谁让他简单易用而且库多呢，对吧，而且谁让我这两年就学了python呢（此处狗头）。原谅我才疏学浅：

1. win ，window10+python3.6以上+vs2017+opencv+pycharm；
2. mac，macos+python3.6以上+opencv+pycharm；

详细库如下所示：

相关库安装介绍

一般玩python的人都知道，这些库就跟做饭加酱油一样，放那种调料，该怎么放它饭好吃一直是各个csdn大佬的贡献，所以我也不多比比，直接上各位大佬的教程。
1、切记安装一定要对应python版本号，建议python3.6以上，下面是安装教程。

https://blog.csdn.net/u012325865/article/details/83961127

2、由于在安装python版本的opencv支持库回遇到版本以及32位64位的问题，需要自己去寻找python版本的.whl下载.下面的地址是各种whl网址

https://www.lfd.uci.edu/~gohlke/pythonlibs/

上面网址详细说明了whl的库文件如何使用。

https://blog.csdn.net/weixin_38168838/article/details/99738371?utm_medium=distribute.pc_relevant.none-task-blog-baidujs_title-11&spm=1001.2101.3001.4242

3、cmake与dlib安装比较复杂，这两个库是必须要安装的，且需要支持的环境，而且由于windows系统并不集成vs相关库而opencv却又是需要安装vs库，所以建议直接下菜vs2017版本。下面网址会详细描述。

https://www.cnblogs.com/wdzn/p/9675821.html

4、待各种库文件安装完毕需要执行realtime_liu即可进行视频实时换眼镜，这里在弹出框里进行按键操作，d按键代表开始，c按键代表替换眼镜，q按键代表退出程序。

上代码

说得多不如做的做，直接上代码。

#具体啥玩意的你就点击运行就行了。d键是开始，c键是替换照片，q键是结束。这代码一看就会。
import dlib
from PIL import Image, ImageDraw, ImageFont
import random

import cv2

from imutils.video import VideoStream
from imutils import face_utils, translate, rotate, resize

import numpy as np

vs = VideoStream().start()

detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor('shape_predictor_68_face_landmarks.dat')

max_width = 500
frame = vs.read()
frame = resize(frame, width=max_width)

fps = vs.stream.get(cv2.CAP_PROP_FPS) # need this for animating proper duration

animation_length = fps * 5
current_animation = 0
glasses_on = fps * 3

# uncomment for fullscreen, remember 'q' to quit
# cv2.namedWindow('deal generator', cv2.WND_PROP_FULLSCREEN)
#cv2.setWindowProperty('deal generator', cv2.WND_PROP_FULLSCREEN,
#                          cv2.WINDOW_FULLSCREEN)

deal = Image.open("./Glasses/0.png")
text = Image.open('text.png')

dealing = False
number =0
while True:
    frame = vs.read()
    frame = resize(frame, width=max_width)
    img_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = []

    rects = detector(img_gray, 0)
    img = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
    # print(rects)
    for rect in rects:
        face = {
     }
        shades_width = rect.right() - rect.left()

        # predictor used to detect orientation in place where current face is
        shape = predictor(img_gray, rect)
        shape = face_utils.shape_to_np(shape)

        # grab the outlines of each eye from the input image
        leftEye = shape[36:42]
        rightEye = shape[42:48]

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

	    # compute the angle between the eye centroids
        dY = leftEyeCenter[1] - rightEyeCenter[1]
        dX = leftEyeCenter[0] - rightEyeCenter[0]
        angle = np.rad2deg(np.arctan2(dY, dX)) 
        # print((shades_width, int(shades_width * deal.size[1] / deal.size[0])))
        # 图片重写
        current_deal = deal.resize((shades_width, int(shades_width * deal.size[1] / deal.size[0])),
                               resample=Image.LANCZOS)
        current_deal = current_deal.rotate(angle, expand=True)
        current_deal = current_deal.transpose(Image.FLIP_TOP_BOTTOM)

        face['glasses_image'] = current_deal
        left_eye_x = leftEye[0,0] - shades_width // 4
        left_eye_y = leftEye[0,1] - shades_width // 6
        face['final_pos'] = (left_eye_x, left_eye_y)

        # I got lazy, didn't want to bother with transparent pngs in opencv
        # this is probably slower than it should be
        # 图片动画以及配置
        if dealing:
            # print("current_y",int(current_animation / glasses_on * left_eye_y))
            if current_animation < glasses_on:
                current_y = int(current_animation / glasses_on * left_eye_y)
                img.paste(current_deal, (left_eye_x, current_y-20), current_deal)
            else:
                img.paste(current_deal, (left_eye_x, left_eye_y-20), current_deal)
                # img.paste(text, (75, img.height // 2 - 52), text)

    # 起初动画配置
    if dealing:
        current_animation += 1
        frame = cv2.cvtColor(np.asarray(img), cv2.COLOR_RGB2BGR)
    # 按键选择
    cv2.imshow("deal generator", frame)
    key = cv2.waitKey(1) & 0xFF
    #退出程序
    if key == ord("q"):
        break
    # 开始程序
    if key == ord("d"):
        dealing = not dealing
    # 图片切换
    if key == ord("c"):
        # 让图片从上面重新开始
        # current_animation = 0

        number = str(random.randint(0, 8))
        print(number)
        deal = Image.open("./Glasses/"+number+".png")
cv2.destroyAllWindows()
vs.stop()

github地址

这是大佬原始
https://github.com/burningion/automatic-memes.git
这是我的也就是本文的
https://github.com/Proshare/Auto-Glasses.git

动图介绍

本人太丑，我就不上了，就随便整个别人的吧（原始老哥贼帅），我这唯一区别就是可以替换眼镜。

改进

由于本科毕设不能太low，就最好能做到那种眼镜360度跟着头部来进行角度替换，所以这个就过时了。于是出了第二版，这里就不上代码了，等明年这同学搞完我再贴上代码。类似于这种。
http://pan.baidu.com/s/1dDGs7Sl