求opencv中Hog行人检测视频中实现的C++代码!

求opencv中Hog行人检测视频中实现的C++代码!,第1张

整个项目的结构图:

编写DetectFaceDemo.java,代码如下:

[java] view

plaincopyprint?

package com.njupt.zhb.test

import org.opencv.core.Core

import org.opencv.core.Mat

import org.opencv.core.MatOfRect

import org.opencv.core.Point

import org.opencv.core.Rect

import org.opencv.core.Scalar

import org.opencv.highgui.Highgui

import org.opencv.objdetect.CascadeClassifier

//

// Detects faces in an image, draws boxes around them, and writes the results

// to "faceDetection.png".

//

public class DetectFaceDemo {

public void run() {

System.out.println("\nRunning DetectFaceDemo")

System.out.println(getClass().getResource("lbpcascade_frontalface.xml").getPath())

// Create a face detector from the cascade file in the resources

// directory.

//CascadeClassifier faceDetector = new CascadeClassifier(getClass().getResource("lbpcascade_frontalface.xml").getPath())

//Mat image = Highgui.imread(getClass().getResource("lena.png").getPath())

//注意:源程序的路径会多打印一个‘/’,因此总是出现如下错误

/*

* Detected 0 faces Writing faceDetection.png libpng warning: Image

* width is zero in IHDR libpng warning: Image height is zero in IHDR

* libpng error: Invalid IHDR data

*/

//因此,我们将第一个字符去掉

String xmlfilePath=getClass().getResource("lbpcascade_frontalface.xml").getPath().substring(1)

CascadeClassifier faceDetector = new CascadeClassifier(xmlfilePath)

Mat image = Highgui.imread(getClass().getResource("we.jpg").getPath().substring(1))

// Detect faces in the image.

// MatOfRect is a special container class for Rect.

MatOfRect faceDetections = new MatOfRect()

faceDetector.detectMultiScale(image, faceDetections)

System.out.println(String.format("Detected %s faces", faceDetections.toArray().length))

// Draw a bounding box around each face.

for (Rect rect : faceDetections.toArray()) {

Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 255, 0))

}

// Save the visualized detection.

String filename = "faceDetection.png"

System.out.println(String.format("Writing %s", filename))

Highgui.imwrite(filename, image)

}

}

package com.njupt.zhb.test

import org.opencv.core.Core

import org.opencv.core.Mat

import org.opencv.core.MatOfRect

import org.opencv.core.Point

import org.opencv.core.Rect

import org.opencv.core.Scalar

import org.opencv.highgui.Highgui

import org.opencv.objdetect.CascadeClassifier

//

// Detects faces in an image, draws boxes around them, and writes the results

// to "faceDetection.png".

//

public class DetectFaceDemo {

public void run() {

System.out.println("\nRunning DetectFaceDemo")

System.out.println(getClass().getResource("lbpcascade_frontalface.xml").getPath())

// Create a face detector from the cascade file in the resources

// directory.

//CascadeClassifier faceDetector = new CascadeClassifier(getClass().getResource("lbpcascade_frontalface.xml").getPath())

//Mat image = Highgui.imread(getClass().getResource("lena.png").getPath())

//注意:源程序的路径会多打印一个‘/’,因此总是出现如下错误

/*

* Detected 0 faces Writing faceDetection.png libpng warning: Image

* width is zero in IHDR libpng warning: Image height is zero in IHDR

* libpng error: Invalid IHDR data

*/

//因此,我们将第一个字符去掉

String xmlfilePath=getClass().getResource("lbpcascade_frontalface.xml").getPath().substring(1)

CascadeClassifier faceDetector = new CascadeClassifier(xmlfilePath)

Mat image = Highgui.imread(getClass().getResource("we.jpg").getPath().substring(1))

// Detect faces in the image.

// MatOfRect is a special container class for Rect.

MatOfRect faceDetections = new MatOfRect()

faceDetector.detectMultiScale(image, faceDetections)

System.out.println(String.format("Detected %s faces", faceDetections.toArray().length))

// Draw a bounding box around each face.

for (Rect rect : faceDetections.toArray()) {

Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 255, 0))

}

// Save the visualized detection.

String filename = "faceDetection.png"

System.out.println(String.format("Writing %s", filename))

Highgui.imwrite(filename, image)

}

}

3.编写测试类:

[java] view

plaincopyprint?

package com.njupt.zhb.test

public class TestMain {

public static void main(String[] args) {

System.out.println("Hello, OpenCV")

// Load the native library.

System.loadLibrary("opencv_java246")

new DetectFaceDemo().run()

}

}

//运行结果:

//Hello, OpenCV

//

//Running DetectFaceDemo

///E:/eclipse_Jee/workspace/JavaOpenCV246/bin/com/njupt/zhb/test/lbpcascade_frontalface.xml

//Detected 8 faces

//Writing faceDetection.png

package com.njupt.zhb.test

public class TestMain {

public static void main(String[] args) {

System.out.println("Hello, OpenCV")

// Load the native library.

System.loadLibrary("opencv_java246")

new DetectFaceDemo().run()

}

}

//运行结果:

//Hello, OpenCV

//

//Running DetectFaceDemo

///E:/eclipse_Jee/workspace/JavaOpenCV246/bin/com/njupt/zhb/test/lbpcascade_frontalface.xml

//Detected 8 faces

//Writing faceDetection.png

这个一般成熟点的网站都是看不到的,因为成熟的网站都是专门有一个文件是做数据库接口,其他页面执行时只会调用它来读取数据库,所以一般只能靠猜测,小型网站一般来说php的用的大多是mysql,asp的大多是mssql.大型的就不好说了,很多

国内的一些权威检测机构,会对一些厂商的源代码的原创性和同源性进行检测,这种检测的目标是要检查出这些代码中哪些是对应的厂商编写开发的,哪些是从其它渠道获取的。这种检测,通常来说,是通过将被测代码与数据库中的样本代码进行比较,从而得出结果。

Black Duck 的Protex 工具,已经被广泛应用于此类检测,成为了该领域的主要解决方案。

基于全球最权威的Black Duck 开源知识库,Protex 可以对软件代码的原创性和同源性进行检查,找到软件代码中所含的开源代码。


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