#include <basic/util/app/AppPreference.hpp>
#include "DnDetect.h"

DnDetect::DnDetect::DnDetect(const int gpuIndex) : m_net(nullptr), m_thresh(0.5), m_hier_thresh(0.5), m_nms(0.45),
                                                   names(nullptr), alphabet(nullptr), m_thdInit(init, this),
                                                   m_bInitThd(false) {

}

DnDetect::DnDetect::~DnDetect() {

}

std::vector<DnDetect::YoloObjInfo> DnDetect::DnDetect::detect(cv::Mat &img) {
    std::lock_guard<std::mutex> dataGuard(dataMtx);

    ClockTimer cl("DnDetect::DnDetect");
    std::vector<YoloObjInfo> objInfos;
    if (!m_bInitThd) return objInfos;
    double bttime = what_time_is_it_now();
    image im = matToImg(img);
//        DBG("matToImg : "<<what_time_is_it_now()-bttime);
//        printf("matToImg %f seconds.\n", what_time_is_it_now()-bttime);
    image sized = letterbox_image(im, m_net->w, m_net->h);
    layer l = m_net->layers[m_net->n - 1];

    float *X = sized.data;
    //attime=what_time_is_it_now();p->
    network_predict(m_net, X);
    //printf("Predicted in %f seconds.\n", what_time_is_it_now()-attime);
    int nboxes = 0;

    detection *dets;

    {
//        std::lock_guard<std::mutex> dataGuard(dataMtx);
//        dataMtx.lock();
        dets = get_network_boxes(m_net, im.w, im.h, m_thresh, m_hier_thresh, 0, 1, &nboxes);
        if (nboxes > 100) {
//            dataMtx.unlock();
            return objInfos;
        }
        if (m_nms) do_nms_sort(dets, nboxes, l.classes, m_nms);
//        dataMtx.unlock();
    }

    //  draw_detections(im, dets, nboxes, m_thresh, names, alphabet, l.classes);
    for (int i = 0; i < nboxes; i++) {
        YoloObjInfo objInfo;
        std::vector<float> vec(80);
        memcpy(&vec[0], dets[i].prob, sizeof(float) * 80);
        int type = -1;
        for (int j = 0; j < l.classes; ++j) {
//#todo new func in list out bool
            if (j != 0) {
                continue;
            }
//#todo get score
            if (dets[i].prob[j] > 0.0f) {
                if (type < 0) {
                    type = j;
                    objInfo.prob = dets[i].prob[j];
                } else {
                }
            } else {
            }
        }
        if (type >= 0) {
//                if(type != 0){
//                    continue;
//                }
            objInfo.type = type;
            objInfo.rcObj.left = (dets[i].bbox.x - dets[i].bbox.w / 2.);
            objInfo.rcObj.top = (dets[i].bbox.y - dets[i].bbox.h / 2.);
            objInfo.rcObj.right = (dets[i].bbox.x + dets[i].bbox.w / 2.);
            objInfo.rcObj.bottom = (dets[i].bbox.y + dets[i].bbox.h / 2.);
            objInfos.push_back(objInfo);
        }
    }
    free_detections(dets, nboxes);
//    show_image(im, "Video");
//    cv::waitKey(10);
    free_image(im);
    free_image(sized);
    //printf("all time use %f seconds.\n", what_time_is_it_now()-bttime);
    return objInfos;
}

image DnDetect::DnDetect::matToImg(cv::Mat &RefImg) {
    CV_Assert(RefImg.depth() == CV_8U);

    int h = RefImg.rows;
    int w = RefImg.cols;
    int channels = RefImg.channels();
    image im = make_image(w, h, 3);
    int count = 0;
    switch (channels) {
        case 1: {
            cv::MatIterator_<unsigned char> it, end;
            for (it = RefImg.begin<unsigned char>(), end = RefImg.end<unsigned char>(); it != end; ++it) {
                im.data[count] = im.data[w * h + count] = im.data[w * h * 2 + count] = (float) (*it) / 255.0;
                ++count;
            }
            break;
        }
        case 3: {
            float *desData = im.data;
            uchar *srcData = RefImg.data;

            int size = w * h;
            int size2 = size * 2;
            for (int i = 0; i < size; i++) {
                *(desData) = *(srcData + 2) / 255.0f;
                *(desData + size) = *(srcData + 1) / 255.0f;
                *(desData + size2) = *(srcData) / 255.0f;

                desData++;
                srcData += 3;
            }
            break;
        }

        default:
            printf("Channel number not supported.\n");
            break;
    }
    return im;
}

int DnDetect::DnDetect::init(void *arg) {
    DnDetect *p = (DnDetect *) arg;

    p->m_thresh = appPref.getFloatData("thresh.detect");
    cuda_set_device(appPref.getIntData("gpu.index"));

    char *datacfg = "cfg/coco.data";
    char *cfgfile = "cfg/yolov3.cfg";
    char *weightfile = "./yolov3.weights";

    double loadtime = what_time_is_it_now();
    list *options = read_data_cfg(datacfg);
    char *name_list = option_find_str(options, "names", "data/names.list");
    p->names = get_labels(name_list);

    p->alphabet = load_alphabet();
    p->m_net = load_network(cfgfile, weightfile, 0);
    set_batch_network(p->m_net, 1);
    printf("load mod use %f seconds.\n", what_time_is_it_now() - loadtime);

    srand(2222222);
    p->m_bInitThd = true;
    return 0;
}