人脸检测Python(用摄像头采集图像然后检测人脸位置)

再来搬运一个人脸检测的例子,是《Python机器学习经典实例》的第10章的例子,书的代码可以从https://github.com/PacktPublishing/Python-Machine-Learning-Cookbook下载,本文为第10章的例子

可以用摄像头采集人的图像然后检测出人脸。代码如下

import cv2
import numpy as np

# Load the face cascade file 按照自己的文件位置加入,如果是下载的原书的程序包那就不用改了
face_cascade = cv2.CascadeClassifier('cascade_files/haarcascade_frontalface_alt.xml')

# Check if the face cascade file has been loaded
if face_cascade.empty():
	raise IOError('Unable to load the face cascade classifier xml file')

# Initialize the video capture object
cap = cv2.VideoCapture(0)

# Define the scaling factor
scaling_factor = 0.5

# Loop until you hit the Esc key
while True:
    # Capture the current frame and resize it
    ret, frame = cap.read()
    frame = cv2.resize(frame, None, fx=scaling_factor, fy=scaling_factor, 
            interpolation=cv2.INTER_AREA)

    # Convert to grayscale
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # Run the face detector on the grayscale image
    face_rects = face_cascade.detectMultiScale(gray, 1.3, 5)

    # Draw rectangles on the image
    for (x,y,w,h) in face_rects:
        cv2.rectangle(frame, (x,y), (x+w,y+h), (0,255,0), 3)

    # Display the image
    cv2.imshow('Face Detector', frame)

    # Check if Esc key has been pressed
    c = cv2.waitKey(1)
    if c == 27:
        break

# Release the video capture object and close all windows
cap.release()
cv2.destroyAllWindows()

运行该例子就可以看到效果啦。

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