在较大的图像上覆盖较小的图像 python OpenCv

问题描述

我正在创建一个程序，用其他人的脸替换图像中的脸.但是，我一直在尝试将新面孔插入到原始的较大图像中.我已经研究了 ROI 和 addWeight(需要图像大小相同)，但我还没有找到在 python 中执行此操作的方法.任何建议都很棒.我是 opencv 的新手.

Hi I am creating a program that replaces a face in a image with someone else's face. However, I am stuck on trying to insert the new face into the original, larger image. I have researched ROI and addWeight(needs the images to be the same size) but I haven't found a way to do this in python. Any advise is great. I am new to opencv.

我正在使用以下测试图像:

I am using the following test images:

较小的图像:

更大的图像:

到目前为止，这是我的代码......其他示例的混合:

Here is my Code so far... a mixer of other samples:

import cv2
import cv2.cv as cv
import sys
import numpy

def detect(img, cascade):
    rects = cascade.detectMultiScale(img, scaleFactor=1.1, minNeighbors=3, minSize=(10, 10), flags = cv.CV_HAAR_SCALE_IMAGE)
    if len(rects) == 0:
        return []
    rects[:,2:] += rects[:,:2]
    return rects

def draw_rects(img, rects, color):
    for x1, y1, x2, y2 in rects:
        cv2.rectangle(img, (x1, y1), (x2, y2), color, 2)

if __name__ == '__main__':
    if len(sys.argv) != 2:                                         ## Check for error in usage syntax

    print "Usage : python faces.py <image_file>"

else:
    img = cv2.imread(sys.argv[1],cv2.CV_LOAD_IMAGE_COLOR)  ## Read image file

    if (img == None):
        print "Could not open or find the image"
    else:
        cascade = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml")
        gray = cv2.cvtColor(img, cv.CV_BGR2GRAY)
        gray = cv2.equalizeHist(gray)

        rects = detect(gray, cascade)

        ## Extract face coordinates
        x1 = rects[0][3]
        y1 = rects[0][0]
        x2 = rects[0][4]
        y2 = rects[0][5]
        y=y2-y1
        x=x2-x1
        ## Extract face ROI
        faceROI = gray[x1:x2, y1:y2]

        ## Show face ROI
        cv2.imshow('Display face ROI', faceROI)
        small = cv2.imread("average_face.png",cv2.CV_LOAD_IMAGE_COLOR)
        print "here"
        small=cv2.resize(small, (x, y))
        cv2.namedWindow('Display image')          ## create window for display
        cv2.imshow('Display image', small)          ## Show image in the window

        print "size of image: ", img.shape        ## print size of image
        cv2.waitKey(1000)

推荐答案

一个简单的方法来实现你想要的:

A simple way to achieve what you want:

import cv2
s_img = cv2.imread("smaller_image.png")
l_img = cv2.imread("larger_image.jpg")
x_offset=y_offset=50
l_img[y_offset:y_offset+s_img.shape[0], x_offset:x_offset+s_img.shape[1]] = s_img

我想您也想处理 Alpha 通道.这是一种快速而肮脏的方法:

I suppose you want to take care of the alpha channel too. Here is a quick and dirty way of doing so:

s_img = cv2.imread("smaller_image.png", -1)

y1, y2 = y_offset, y_offset + s_img.shape[0]
x1, x2 = x_offset, x_offset + s_img.shape[1]

alpha_s = s_img[:, :, 3] / 255.0
alpha_l = 1.0 - alpha_s

for c in range(0, 3):
    l_img[y1:y2, x1:x2, c] = (alpha_s * s_img[:, :, c] +
                              alpha_l * l_img[y1:y2, x1:x2, c])

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