首页 > 解决方案 > 错误:(-215:断言失败)!函数'cv :: CascadeClassifier :: detectMultiScale'中的empty()

问题描述

我正在尝试使用 python 的“Open-CV”进行人脸检测。该程序向我抛出了一个我作为 python 初学者无法理解的错误。程序的错误:

Traceback (most recent call last):
  File "c:\Users\(User's name)\Documents\Python\Face-dection\Facedectection.py", line 6, in <module>
    gray_img=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
cv2.error: OpenCV(4.5.1) C:\Users\appveyor\AppData\Local\Temp\1\pip-req-build-wvn_it83\opencv\modules\imgproc\src\color.cpp:182: error: (-215:Assertion failed) !_src.empty() in function 'cv::cvtColor' 

编码:

import cv2

face_cascade=cv2.CascadeClassifier("haarcascade_frontalface_default.xml")

img = cv2.imread("photo.jpg")
gray_img=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

faces=face_cascade.detectMultiScale(gray_img, scaleFactor=1.05,minNeighbors=5)

for x, y, w, h in faces:
    img=cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),3)

resized=cv2.resize(img,(int(img.shape[1]/3)),(int(img.shape[0]/3)))

cv2.imshow("Deteced-face",resized)
cv2.waitKey(0)
cv2.destroyAllWindows()

注意:照片和.xml文件放在同一个文件夹中

标签: python-3.xface-detectionopencv-pythonface

解决方案


您需要cv2.data.haarcascades在引用.xml文件之前添加。

#[...]

face_cascade=cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml") #Note the change

#[...]

您的代码中还有一个问题,请查看以下代码块:

resized=cv2.resize(img,(int(img.shape[1]/3)),(int(img.shape[0]/3)))

您应该传递一个图像,它是新的宽度和高度(以元组格式)作为参数,但是您将图像以及宽度和高度作为单独的整数而不是元组格式传递。

这应该是这样的:

resized=cv2.resize(img,(int(img.shape[1]/3), int(img.shape[0]/3))) 
'''
Notice I have removed an extra bracket after
cv2.resize(img,(int(img.shape[1]/3)) -> cv2.resize(img,(int(img.shape[1]/3)...
and also I have removed an extra bracket before
(int(img.shape[0]/3))) -> int(img.shape[0]/3)))
'''

这应该工作:

import cv2

face_cascade=cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml") #Note the change

img = cv2.imread("photo.jpg")
gray_img=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

faces=face_cascade.detectMultiScale(gray_img, scaleFactor=1.05,minNeighbors=5)

for x, y, w, h in faces:
    img=cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),3)

resized=cv2.resize(img,(int(img.shape[1]/3), int(img.shape[0]/3))) 

cv2.imshow("Deteced-face",resized)
cv2.waitKey(0)
cv2.destroyAllWindows()

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