前言

突然想起opencv，一直想做人脸识别，可是理论基础太水，只能慢慢来，去年学习了一会，然后公司让我去搞app和网络，就一直搁着，现在学习qml，突然想能不能在qml里面使用opencv，所以就有了这篇文章。

QQuickItem和QObject

在QML中，可视化的基础组件是Item，不可视化的就是QtObject，它们对应C++中的QQuickItem和QObject类，扩展QML组件一个继续基于QML中的Item扩张，还有就是继承QQuickItem，我们想把opencv加到QML中，那么只有继承QQuickItem了。
怎么使用，那还要看QML新的渲染机制，Qt5的QML渲染基于OpenGL，其场景的渲染在单独的线程进行，我们需要需要QQuickItem返回能够描述场景的对象，就是QSGNode。实现QQuick的updatePaintNode函数就OK了，我们在updatePaintNode，描述怎么渲染。

类的关系

OpenCVcapture继承QOjbect，其是图像捕获的基类，OpenCVcamera是OpenCVcapture子类，完成从摄像头捕获数据。OpenCVaction类封装了opencv图像算法操作。OpenCVshowFrame继承QQuickItem，实现可视化。

#include <QApplication>
#include <QQmlApplicationEngine>
#include <QtQml/qqml.h>
#include "opencvcamera.h"
#include "opencvshowframe.h"

int main(int argc, char *argv[])
{
    QApplication app(argc, argv);

    qmlRegisterType<OpenCVcamera>("OpenCV", 1, 0, "OpenCVcamera");
    qmlRegisterType<OpenCVshowFrame>("OpenCV", 1, 0, "OpenCVshowFrame");

    QQmlApplicationEngine engine;
    engine.load(QUrl(QStringLiteral("qrc:/main.qml")));

    return app.exec();
}


import QtQuick 2.4
import QtQuick.Controls 1.3
import QtQuick.Window 2.2
import QtQuick.Dialogs 1.2
import OpenCV 1.0

ApplicationWindow {
    title: qsTr("Hello World")
    width: 640
    height: 480
    visible: true

    menuBar: MenuBar {
        Menu {
            title: qsTr("&File")
            MenuItem {
                text: qsTr("&Open")
                onTriggered: {

                    //messageDialog.show(qsTr("Open OpenCV triggered"));
                    opencvCamera.m_run = true
                }

            }
            MenuItem {
                text: qsTr("&Close")
                onTriggered: {

                    //messageDialog.show(qsTr("Open OpenCV triggered"));
                    opencvCamera.m_run = false
                }

            }
            MenuItem {
                text: qsTr("E&xit")
                onTriggered: Qt.quit();
            }
        }
    }

    OpenCVcamera {
        id:opencvCamera
        m_cameraId: 1
        m_run: false

        //width: 320
        //height: 240
    }

    OpenCVshowFrame {
        anchors.centerIn: parent
        id:opencvShowFrame
        m_capture: opencvCamera
        m_frameRate: 33
        m_run: true
        width: 480
        height: 320
    }


    MessageDialog {
        id: messageDialog
        title: qsTr("May I have your attention, please?")

        function show(caption) {
            messageDialog.text = caption;
            messageDialog.open();
        }
    }
}

效果

我封装了轮廓扫描的算法操作。

updatePaintNode

QSGNode* OpenCVshowFrame::updatePaintNode(QSGNode *old, UpdatePaintNodeData *)
{
    QSGSimpleTextureNode *texture = static_cast<QSGSimpleTextureNode*>(old);
    if (texture == NULL) {
        texture = new QSGSimpleTextureNode();
    }
    QImage img;
    IplImage *iplImage = NULL;
    IplImage *out = NULL;
    if (m_capture) {
        iplImage = static_cast<OpenCVcapture*>(m_capture)->getFrame();
    }
    if (iplImage != NULL) {
        out = doActions(iplImage);
        uchar *imgData = (uchar *)out->imageData;
        //qDebug() << out->depth << out->nChannels;
        img = QImage(imgData, out->width, out->height, QImage::Format_RGB888);
    } else {
        img = QImage(boundingRect().size().toSize(), QImage::Format_RGB888);
    }
    QSGTexture *t = window()->createTextureFromImage(img.scaled(boundingRect().size().toSize()));
    if (t) {
        QSGTexture *tt = texture->texture();
        if (tt) {
            tt->deleteLater();
        }
        texture->setRect(boundingRect());
        texture->setTexture(t);
    }
    if (out) {
        cvReleaseImage(&out);
    }
    return texture;
}

使用了QSGSimpleTextureNode，然后我们将opencv的图像，作为一个QSGTexture，然后返回给渲染的线程进行场景的渲染。

这里还要说下，Qt的QImage，不支持单通道的灰度图，我们需要转换成RGB才能正确的显示。