Python CVLIB-如何将模糊子面添加到原始图像?
朋友们,我需要实现一个代码,从给定的图像中模糊人脸(我不是开发人员,所以这对我来说非常困难)。我发现我可以使用OpenCV和cvlib来完成这项工作,并找到了一个示例代码(cvlib中的存储库),它完成了部分工作 我知道我需要获得子面并对其应用面部模糊,我可以做到,但现在我不知道如何将模糊的面部添加到原始图像中。有人能帮我吗Python CVLIB-如何将模糊子面添加到原始图像?,python,opencv,computer-vision,cvlib,Python,Opencv,Computer Vision,Cvlib,朋友们,我需要实现一个代码,从给定的图像中模糊人脸(我不是开发人员,所以这对我来说非常困难)。我发现我可以使用OpenCV和cvlib来完成这项工作,并找到了一个示例代码(cvlib中的存储库),它完成了部分工作 我知道我需要获得子面并对其应用面部模糊,我可以做到,但现在我不知道如何将模糊的面部添加到原始图像中。有人能帮我吗 import cvlib as cv import sys from cv2 import cv2 import os # read input image image
import cvlib as cv
import sys
from cv2 import cv2
import os
# read input image
image = cv2.imread('path')
# apply face detection
faces, confidences = cv.detect_face(image)
print(faces)
print(confidences)
# loop through detected faces
for face,conf in zip(faces,confidences):
(startX,startY) = face[0],face[1]
(endX,endY) = face[2],face[3]
subFace = image[startY:endY,startX:endX]
subFace = cv2.GaussianBlur(subFace,(23, 23), 30)
# display output
# press any key to close window
cv2.imshow("face_detection", image)
cv2.waitKey()
cv2.imshow("face_detection", subFace)
# release resources
cv2.destroyAllWindows()
我终于想出了办法:
import cvlib as cv
import sys
from cv2 import cv2
import os
# read input image
image = cv2.imread('path')
# apply face detection
faces, confidences = cv.detect_face(image)
# print the array with the coordinates and the confidence
print(faces)
print(confidences)
# loop through detected faces
for face,conf in zip(faces,confidences):
(startX,startY) = face[0],face[1]
(endX,endY) = face[2],face[3]
# get the subface
subFace = image[startY:endY,startX:endX]
# apply gaussian blur over subfaces
subFace = cv2.GaussianBlur(subFace,(23, 23), 30)
# add the subfaces to de original image
image[startY:startY+subFace.shape[0], startX:startX+subFace.shape[1]] = subFace
cv2.imshow("face_detection", image)
cv2.waitKey()
# save output
cv2.imwrite("face_detection.jpg", image)
# release resources
cv2.destroyAllWindows()