firefly-rk3399 开发记录8-NCNN检测_rk3399 vulkan

1.NCNN编译

NCNN就不描述了，这里采用NCNN最新的发布版ncnn-20200727，buildroot中的mk文件如下

 
NCNN_VERSION = 20200727
NCNN_SITE = $(call github,Tencent,ncnn,$(NCNN_VERSION))
NCNN_INSTALL_STAGING = YES
NCNN_LICENSE = BSD-2-Clause or GPL-2.0+
NCNN_LICENSE_FILES = LICENSE
NCNN_CONF_OPTS += -DNCNN_ARM82=OFF
 
$(eval $(cmake-package))

NCNN_ARM82这个要稍微注意下，这里用不到的，但是编译的时候再cmakelists中，检测到arm之后就默认开启了，这里会编译出错.

2.retinaface

这里就直接采用NCNN历程中的retinaface.cpp了，基本都可以直接使用，模型文件在另外的仓库上https://github.com/nihui/ncnn-assets/tree/master/models

QSmartNcnn::QSmartNcnn()
{
    retinaface.opt.use_vulkan_compute = true;
    retinaface.opt.num_threads        = 6;
    // model is converted from
    // https://github.com/deepinsight/insightface/tree/master/RetinaFace#retinaface-pretrained-models
    // https://github.com/deepinsight/insightface/issues/669
    // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
    //     retinaface.load_param("retinaface-R50.param");
    //     retinaface.load_model("retinaface-R50.bin");
    int ret = retinaface.load_param("/root/ncnn-assets/models/mnet.25-opt.param");
    qDebug() << "load param " << ret;
    ret = retinaface.load_model("/root/ncnn-assets/models/mnet.25-opt.bin");
    qDebug() << "load bin " << ret;
}
 
QSmartNcnn::~QSmartNcnn()
{
 
}
 
int QSmartNcnn::detect_face(const cv::Mat &image, QVector<QRect> &rect)
{
    std::vector<FaceObject> faceobjects;
    qDebug() << "need do detect";
    if(detect_retinaface(image, faceobjects) < 0)
        return -1;
    qDebug() << faceobjects.size();
    for(auto &item : faceobjects)
    {
        rect.append(QRect(item.rect.x,item.rect.y,
                          item.rect.width,item.rect.height));
    }
    return rect.size();
}
 
int QSmartNcnn::extract_feature(const cv::Mat &image, const QRect &rect, QByteArray &feature)
{
 
}
 
 
 
 
void QSmartNcnn::qsort_descent_inplace(std::vector<FaceObject>& faceobjects, int left, int right)
{
    int i = left;
    int j = right;
    float p = faceobjects[(left + right) / 2].prob;
 
    while (i <= j)
    {
        while (faceobjects[i].prob > p)
            i++;
 
        while (faceobjects[j].prob < p)
            j--;
 
        if (i <= j)
        {
            // swap
            std::swap(faceobjects[i], faceobjects[j]);
 
            i++;
            j--;
        }
    }
 
    #pragma omp parallel sections