视频1 视频21 视频41 视频61 视频文章1 视频文章21 视频文章41 视频文章61 推荐1 推荐3 推荐5 推荐7 推荐9 推荐11 推荐13 推荐15 推荐17 推荐19 推荐21 推荐23 推荐25 推荐27 推荐29 推荐31 推荐33 推荐35 推荐37 推荐39 推荐41 推荐43 推荐45 推荐47 推荐49 关键词1 关键词101 关键词201 关键词301 关键词401 关键词501 关键词601 关键词701 关键词801 关键词901 关键词1001 关键词1101 关键词1201 关键词1301 关键词1401 关键词1501 关键词1601 关键词1701 关键词1801 关键词1901 视频扩展1 视频扩展6 视频扩展11 视频扩展16 文章1 文章201 文章401 文章601 文章801 文章1001 资讯1 资讯501 资讯1001 资讯1501 标签1 标签501 标签1001 关键词1 关键词501 关键词1001 关键词1501 专题2001
python中使用OpenCV进行人脸检测的例子
2020-11-27 14:38:34 责编:小采
文档

OpenCV的人脸检测功能在一般场合还是不错的。而ubuntu正好提供了python-opencv这个包,用它可以方便地实现人脸检测的代码。

写代码之前应该先安装python-opencv:

代码如下:


$ sudo apt-get install python-opencv

具体原理就不多说了,可以参考一下这篇文章。直接上源码。

代码如下:


#!/usr/bin/python
# -*- coding: UTF-8 -*-

# face_detect.py

# Face Detection using OpenCV. Based on sample code from:
# http://python.pastebin.com/m76db1d6b

# Usage: python face_detect.py

import sys, os
from opencv.cv import *
from opencv.highgui import *
from PIL import Image, ImageDraw
from math import sqrt

def detectObjects(image):
"""Converts an image to grayscale and prints the locations of any faces found"""
grayscale = cvCreateImage(cvSize(image.width, image.height), 8, 1)
cvCvtColor(image, grayscale, CV_BGR2GRAY)

storage = cvCreateMemStorage(0)
cvClearMemStorage(storage)
cvEqualizeHist(grayscale, grayscale)

cascade = cvLoadHaarClassifierCascade(
'/usr/share/opencv/haarcascades/haarcascade_frontalface_default.xml',
cvSize(1,1))
faces = cvHaarDetectObjects(grayscale, cascade, storage, 1.1, 2,
CV_HAAR_DO_CANNY_PRUNING, cvSize(20,20))

result = []
for f in faces:
result.append((f.x, f.y, f.x+f.width, f.y+f.height))

return result

def grayscale(r, g, b):
return int(r * .3 + g * .59 + b * .11)

def process(infile, outfile):

image = cvLoadImage(infile);
if image:
faces = detectObjects(image)

im = Image.open(infile)

if faces:
draw = ImageDraw.Draw(im)
for f in faces:
draw.rectangle(f, outline=(255, 0, 255))

im.save(outfile, "JPEG", quality=100)
else:
print "Error: cannot detect faces on %s" % infile

if __name__ == "__main__":
process('input.jpg', 'output.jpg')

下载本文
显示全文
专题