作业题目

对于资料包中的兔耳朵帽子特效的图片处理代码学习。
编写读取视频 video.mov，进行兔耳帽帽子特效的代码，实现对视频进行兔耳朵帽子特效。在作业中，将视频处理的其中一张效果图也截图附在作业中。
将整个兔耳朵帽子特效的流程拆解，写出实现的步骤，和自己对于人脸特效的心得理
解。

1、视频图片截屏

在这里插入图片描述

2、流程拆解

人脸侦测
帽子处理
人脸图片处理
帽子和人脸组装

具体位置见代码注释

import cv2  # 图像处理的opencv库
import dlib  # 加载dlib算法模块
import argparse  # 加载解析模块


def hat_face(opt):
    detector = dlib.get_frontal_face_detector()
    cap = cv2.VideoCapture(opt.video_path)
    img_hat = cv2.imread(opt.hat_path)

    frame_id=0
    while True:
        ret, img = cap.read()
        
        # 人脸侦测
        faceRects = detector(img, 0)
        for box_info in faceRects:
            x0, y0, width_face, height_face = box_info.left(), box_info.top(), box_info.right() - box_info.left(), box_info.bottom() - box_info.top()
            
            # 帽子处理
            height_hat, width_hat = img_hat.shape[0], img_hat.shape[1]
            imgComposeSizeH = int(height_hat / width_hat * width_face)
            if imgComposeSizeH > (y0 - 20):
                imgComposeSizeH = (y0 - 20)
            imgComposeSize = cv2.resize(img_hat, (width_face, imgComposeSizeH), interpolation=cv2.INTER_NEAREST)
            top = (y0 - 20 - imgComposeSizeH)
            if top <= 0:
                top = 0
            height_hat_new, width_hat_new = imgComposeSize.shape[0], imgComposeSize.shape[1]
            small_img_hat = img[top:top + height_hat_new, x0:x0 + width_hat_new]
            small_img_hat_gray = cv2.cvtColor(imgComposeSize, cv2.COLOR_RGB2GRAY)
            ret, mask_hat = cv2.threshold(small_img_hat_gray, 10, 255, cv2.THRESH_BINARY)

            mask_hat_inv = cv2.bitwise_not(mask_hat)
            
            # 背景处理
            img1_bg = cv2.bitwise_and(small_img_hat, small_img_hat, mask=mask_hat_inv)
            img2_fg = cv2.bitwise_and(imgComposeSize, imgComposeSize, mask=mask_hat)
            dst = cv2.add(img1_bg, img2_fg)
            
            # 贴图
            img[top:top + height_hat_new, x0:x0 + width_hat_new] = dst

        img = cv2.resize(img, (500, 600))
        cv2.imshow("image", img)
        frame_id+=1
        if int(frame_id)%5!=0:continue
        cv2.waitKey(10)


if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument('--video_path', default="video.mov", help='path of read video')
    parser.add_argument('--hat_path', default="maozi.png", help='path of hat image')

    opt = parser.parse_args()
    hat_face(opt)