Function postpreprocess

yolox_example/main.cpp:200–279

}

static void postpreprocess(
        const float* output_ptr, std::vector<OutputInfo>& output_infos, float scale,
        const int img_w, const int img_h) {
    std::vector<OutputInfo> valid_output_info;
    std::vector<BaseAnchor> base_anchors;

    // get base anchor
    for (auto stride : {8, 16, 32}) {
        int num_anchor = INPUT_W / stride;
        for (int g1 = 0; g1 < num_anchor; g1++) {
            for (int g0 = 0; g0 < num_anchor; g0++) {
                base_anchors.push_back((BaseAnchor){g0, g1, stride});
            }
        }
    }
    // get valid output information
    const int num_class = 80;
    const int num_anchors = base_anchors.size();
    for (int anchor_idx = 0; anchor_idx < num_anchors; anchor_idx++) {
        const int grid0 = base_anchors[anchor_idx].grid0;
        const int grid1 = base_anchors[anchor_idx].grid1;
        const int stride = base_anchors[anchor_idx].stride;

        const int basic_pos = anchor_idx * 85;

        float x_center = (output_ptr[basic_pos + 0] + grid0) * stride;
        float y_center = (output_ptr[basic_pos + 1] + grid1) * stride;
        float w = exp(output_ptr[basic_pos + 2]) * stride;
        float h = exp(output_ptr[basic_pos + 3]) * stride;
        float x0 = x_center - w * 0.5f;
        float y0 = y_center - h * 0.5f;

        float box_objectness = output_ptr[basic_pos + 4];
        for (int class_idx = 0; class_idx < num_class; class_idx++) {
            float box_cls_score = output_ptr[basic_pos + 5 + class_idx];
            float box_prob = box_objectness * box_cls_score;
            if (box_prob > BBOX_CONF_THRESH) {
                OutputInfo obj;
                obj.rect.x = x0;
                obj.rect.y = y0;
                obj.rect.width = w;
                obj.rect.height = h;
                obj.label = class_idx;
                obj.prob = box_prob;

                valid_output_info.push_back(obj);
            }

        }  // class loop

    }  // point anchor loop

    qsort_descent_inplace(valid_output_info);

    std::vector<int> picked_output;
    nms_sorted_bboxes(valid_output_info, picked_output, NMS_THRESH);
    int count = picked_output.size();
    output_infos.resize(count);