使用 Python-OpenCV 实时检测猫脸
原文:https://www . geesforgeks . org/detect-cat-face-in-time-use-python-opencv/
人脸检测 是一种从图像中识别人脸的技术。我们为此使用 Python 的 OpenCV。我们也可以在动物的情况下使用人脸检测。如果可以仔细查看 OpenCV 存储库，haar 级联目录是特定的(OpenCV 在这里存储其所有预先训练的 haar 分类器，以检测各种对象、身体部位等。)，有两个文件:
- haarcascade _ frontalcatface . xml
- haarcscade _ frontal catface _ extended . XML
给定程序的目标是实时检测感兴趣的对象(猫脸)，并保持跟踪同一对象。这是一个如何在 Python 中检测猫脸的简单例子。您可以尝试使用您选择的任何其他对象的训练样本，通过在所需对象上训练分类器来进行检测。
下面是实现。
# OpenCV program to detect cat face in real time
# import libraries of python OpenCV
# where its functionality resides
import cv2
# load the required trained XML classifiers
# https://github.com/Itseez/opencv/blob/master/
# data/haarcascades/haarcascade_frontalcatface.xml
# Trained XML classifiers describes some features of some
# object we want to detect a cascade function is trained
# from a lot of positive(faces) and negative(non-faces)
# images.
face_cascade = cv2.CascadeClassifier('haarcascade_frontalcatface.xml')
# capture frames from a camera
cap = cv2.VideoCapture(0)
# loop runs if capturing has been initialized.
while 1:
# reads frames from a camera
ret, img = cap.read()
# convert to gray scale of each frames
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Detects faces of different sizes in the input image
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x,y,w,h) in faces:
# To draw a rectangle in a face
cv2.rectangle(img,(x,y),(x+w,y+h),(255,255,0),2)
roi_gray = gray[y:y+h, x:x+w]
roi_color = img[y:y+h, x:x+w]
# Display an image in a window
cv2.imshow('img',img)
# Wait for Esc key to stop
k = cv2.waitKey(30) & 0xff
if k == 27:
break
# Close the window
cap.release()
# De-allocate any associated memory usage
cv2.destroyAllWindows()
输出:
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