进行人脸检测时不能只拍人脸

Question

我正在尝试使用开源教程中的OpenCV制作人脸检测程序。目标是从视频中检测人脸，其结果被用作每个人脸的模型。每个脸将保存在文件夹中，我有2个问题，当我尝试的程序:

1. OpenCV不仅捕捉人脸，而且捕捉整个视频

2. 只拍摄一张照片，而需要多张(每帧)

#insert picture 1

有解决方案吗?

代码如下:

model = cv2.CascadeClassifier("../model/haarcascade_frontalface_alt2.xml")
cap = cv2.VideoCapture('../video/videoplayback.mp4') #Video
while True:
ret, image = cap.read()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
bounding_box = model.detectMultiScale(gray, scaleFactor=1.01,
minNeighbors=5, minSize=(30, 30), flags=cv2.CASCADE_SCALE_IMAGE)

for (x, y, w, h) in bounding_box:
cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)
image2 = image[y:(y+h),x:(x+w)]

image3 = cv2.blur(image2, (40,40))
image[y:(y+h),x:(x+w)] = image3
cv2.imwrite("../output_model/videos/image.jpg", image) 
cv2.imshow("hasil", image)
if cv2.waitKey(1) and 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()```

Answer 1

1. 要只取人脸，就必须只取人脸的变量(它在image2变量中)。当它检测到视频时，你所做的就是模糊检测到的人脸，这样它就可以捡起模糊的部分。

image2 = image[y:(y+h),x:(x+w)]
cv2.imwrite("../output_model/videos/{}.jpg".format(counter), image2)

2. 可以被加载人脸图像时执行的增量和循环欺骗。每个文件夹都用增量填充。下面是一个例子:

counter = 0 #Increment
while True:
ret, image = cap.read()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
bounding_box = detector_wajah.detectMultiScale(gray, scaleFactor=1.01,
minNeighbors=5, minSize=(30, 30), flags=cv2.CASCADE_SCALE_IMAGE)

for (x, y, w, h) in bounding_box:
counter+=1 #Increment
cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)
image2 = image[y:(y+h),x:(x+w)]

为了完整起见(有变量被改变了)，如下所示:

import cv2
model = cv2.CascadeClassifier("../model/haarcascade_frontalface_alt2.xml")
cap = cv2.VideoCapture('../video/videoplayback.mp4') #Video
counter = 0
while True:
ret, image = cap.read()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
bounding_box = model.detectMultiScale(gray, scaleFactor=1.01,
minNeighbors=5, minSize=(30, 30), flags=cv2.CASCADE_SCALE_IMAGE)
for (x, y, w, h) in bounding_box:
counter+=1
cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)
face = image[y:(y+h),x:(x+w)]
cv2.imwrite("../output_model/videos/{}.jpg".format(counter), face) 
blur_face = cv2.blur(face, (40,40))
image[y:(y+h),x:(x+w)] = blur_face
cv2.imshow("hasil", image)
if cv2.waitKey(1) and 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()