qml+opencv(二)

最新推荐文章于 2024-12-17 18:13:11 发布

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最新推荐文章于 2024-12-17 18:13:11 发布

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文章标签：人工智能 python

原文链接：https://my.oschina.net/u/854744/blog/418190

本文介绍了一个基于OpenCV的人脸检测算法实现。通过使用Haar分类器进行人脸定位，并实现了简单的图像预处理步骤如灰度转换、图像缩放及直方图均衡化。此外，文章还展示了如何将该算法集成到OpenCV项目中。

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2019独角兽企业重金招聘Python工程师标准>>>

实现人脸检测。opencv提供了Haar分类器，其在data文件下还提供了训练的数据，所以实现这个不是很难。
我继承OpenCVaction，实现了人脸检测的算法。

#ifndef OPENCVFACEDETECTACTION_H
#define OPENCVFACEDETECTACTION_H
#include "opencvaction.h"
 class OpenCVfaceDetectAction : public OpenCVaction { Q_OBJECT public: OpenCVfaceDetectAction(QObject *parent = 0); ~OpenCVfaceDetectAction(); void action(IplImage *imgin, IplImage *&imgout); signals: void a(); private: CvHaarClassifierCascade* m_cascade; CvMemStorage* m_storage; double m_scale; }; #endif // OPENCVFACEDETECTACTION_H #include "opencvfacedetectaction.h" #include <QDebug> const char* cascade_name = "data/haarcascade_frontalface_alt.xml"; OpenCVfaceDetectAction::OpenCVfaceDetectAction(QObject *parent): OpenCVaction(parent), m_cascade(NULL), m_storage(NULL), m_scale(1.3) { m_cascade = (CvHaarClassifierCascade*)cvLoad(cascade_name, 0, 0, 0); if (!m_cascade) { qDebug() << "load Cascade fail!"; } m_storage = cvCreateMemStorage(0); } OpenCVfaceDetectAction::~OpenCVfaceDetectAction() { if (m_cascade) { cvReleaseHaarClassifierCascade(&m_cascade); } cvReleaseMemStorage(&m_storage); } void OpenCVfaceDetectAction::action(IplImage *imgin, IplImage *&imgout) { imgout = cvCloneImage(imgin); if (!m_cascade) { qDebug() << "Cascade is invaild!"; return; } static CvScalar color = CV_RGB(255, 255, 255); //Image Preparation // IplImage* gray = cvCreateImage(cvGetSize(imgin), 8, 1); IplImage* small_img = cvCreateImage(cvSize(cvRound(imgin->width / m_scale), cvRound(imgin->height / m_scale)), 8, 1); cvCvtColor(imgin, gray, CV_BGR2GRAY); cvResize(gray, small_img, CV_INTER_LINEAR); cvEqualizeHist(small_img, small_img); //直方图均衡 //Detect objects if any // cvClearMemStorage(m_storage); double t = (double)cvGetTickCount(); CvSeq *objects = cvHaarDetectObjects(small_img, m_cascade, m_storage, 1.1, 2, 0, cvSize(50,50)); t = (double)cvGetTickCount() - t; qDebug() << "detection time =" << t / ((double)cvGetTickFrequency()*1000.) << "ms"; //Loop through found objects and draw boxes around them for(int i=0; i < (objects ? objects->total : 0); ++i) { CvRect* r = (CvRect*)cvGetSeqElem(objects, i); cvRectangle(imgout, cvPoint(r->x * m_scale, r->y * m_scale), cvPoint((r->x + r->width) * m_scale, (r->y + r->height) * m_scale), color, 2, CV_AA); } cvReleaseImage(&gray); cvReleaseImage(&small_img); emit a(); }

在OpenCVshowFrame中，添加下面

 OpenCVfaceDetectAction *f = new OpenCVfaceDetectAction(); m_actions.push_back(f);

就ok了。
运行效果如下：
这里写图片描述

转载于:https://my.oschina.net/u/854744/blog/418190