python - 如何从同一图像中检测多个人脸？

Question

我正在尝试使用 python 和 opencv 从同一图像中裁剪多个面孔，但它显示错误。如果有其他方法请告诉我。下面是代码以及错误。

import cv2

# Load some pre-trained data on face frontals from opencv (haar cascade algorithm)
trained_face_data = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

# Choose an image to detect faces in
img = cv2.imread('mask.png')
    
# Must convert to greyscale
grayscaled_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    
# Detect Faces 
face_coordinates = trained_face_data.detectMultiScale(grayscaled_img)

img_crop = []

# Draw rectangles around the faces
for (x, y, w, h) in face_coordinates:
    cv2.rectangle(img, (x,y), (x+w, y+h), (0, 255, 0), 2)
    img_crop.append(img[y:y+h, x:x+w])

    
cv2.imshow('Cropped', img_crop)

cv2.waitKey()

---

**TypeError**                                 Traceback (most recent call last)
<ipython-input-4-7c85402c34e9> in <module>
     32 [enter image description here][1]
     33 
---> 34 cv2.imshow('Cropped', img_crop)
     35 #cv2.imshow('crop', img_crop2)
     36 #cv2.imshow('Face Detector',  img)

TypeError: Expected Ptr<cv::UMat> for argument 'mat'e here

Answer 1

一种解决方案是，在将所有图像存储在列表中之后：

一次显示每个图像

for cropped in img_crop:
    cv2.imshow('Cropped', cropped)
    cv2.waitKey(0)

假设您的输入图像：

结果：

如果你想保存它们，你可以这样做：

for counter, cropped in enumerate(img_crop):
    cv2.imshow('Cropped', cropped)
    cv2.imwrite("pose_result_{}.png".format(counter), cropped)
    cv2.waitKey(0)

代码：

import cv2
import numpy as np

# Load some pre-trained data on face frontal from opencv (haar cascade algorithm)
trained_face_data = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

# Choose an image to detect faces in
img = cv2.imread('mask.png')

# Must convert to greyscale
grayscaled_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Detect Faces
face_coordinates = trained_face_data.detectMultiScale(grayscaled_img)

img_crop = []

# Draw rectangles around the faces
for (x, y, w, h) in face_coordinates:
    cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
    img_crop.append(img[y:y + h, x:x + w])

for counter, cropped in enumerate(img_crop):
    cv2.imshow('Cropped', cropped)
    cv2.imwrite("pose_result_{}.png".format(counter), cropped)
    cv2.waitKey(0)