Deepstream6.0保存推理时间图片

场景：在检测识别到的图像内容时，保存一张图片。

首先看官方的获取图像的代码。

      NvBufSurfaceMap (surface, -1, -1, NVBUF_MAP_READ);
      // NvBufSurfaceSyncForCpu(surface, 0, 0);
      NvBufSurfacePlaneParams *pParams = &GLOBAL_SURF->surfaceList[frame_meta->batch_id].planeParams;
      unsigned int offset = 0;
      for(unsigned int num_planes=0; num_planes < pParams->num_planes; num_planes++){
        if(num_planes>0)
          offset += pParams->height[num_planes-1]*(pParams->bytesPerPix[num_planes-1]*pParams->width[num_planes-1]);
        for (unsigned int h = 0; h < pParams->height[num_planes]; h++) {
          memcpy((void *)(src_data+offset+h*pParams->bytesPerPix[num_planes]*pParams->width[num_planes]),
              (void *)((char *)GLOBAL_SURF->surfaceList[frame_meta->batch_id].mappedAddr.addr[num_planes]+h*pParams->pitch[num_planes]),
              pParams->bytesPerPix[num_planes]*pParams->width[num_planes]
                );
        }
      }
      NvBufSurfaceUnMap (surface, -1, -1);

和

// cudaMemcpy((void *)src_data,
      //            (void *)surface->surfaceList[frame_meta->batch_id].dataPtr,
      //            surface->surfaceList[frame_meta->batch_id].dataSize,
      //            cudaMemcpyDeviceToHost);

注意事项：

1、如果你是DGPU，用cudaMemcopy

2、在jetson里面，没有独立的显存不能使用cudaMemcopy，建议使用第一种方式

3、注意通道，在deepstream5.0里面都是yuv的格式，在6.0里面都是RGBA，需要注意通道

      cv::Mat frame = cv::Mat(frame_height , frame_width, CV_8UC4, src_data, frame_step);
      cv::Mat out_mat = cv::Mat(cv::Size(frame_width, frame_height), CV_8UC3);
        cv::cvtColor(frame, out_mat, CV_RGBA2BGR);

yuv格式的，其他博客很多人有就不加了

二、整段代码参考：

static GstPadProbeReturn
tiler_src_pad_buffer_probe (GstPad * pad, GstPadProbeInfo * info,
    gpointer u_data)
{
    GstBuffer *buf = (GstBuffer *)info->data;
    GstMapInfo in_map_info;
    NvBufSurface *surface = NULL;
    guint num_rects = 0; 
    NvDsObjectMeta *obj_meta = NULL;
    guint vehicle_count = 0;
    guint person_count = 0;
    NvDsMetaList * l_frame = NULL;
    NvDsMetaList * l_obj = NULL;
    //NvDsDisplayMeta *display_meta = NULL;
    NvDsBatchMeta *batch_meta = gst_buffer_get_nvds_batch_meta (buf);

    for (l_frame = batch_meta->frame_meta_list; l_frame != NULL; l_frame = l_frame->next){
          NvDsFrameMeta *frame_meta = (NvDsFrameMeta *) (l_frame->data);
    // printf("src name:%s\n", src[frame_meta->source_id]);
    // printf("batch id:%d, source is:%d\n", frame_meta->batch_id, frame_meta->source_id);
      for (l_obj = frame_meta->obj_meta_list; l_obj != NULL; l_obj = l_obj->next){
        obj_meta = (NvDsObjectMeta *) (l_obj->data);
        if (obj_meta->class_id == PGIE_CLASS_ID_PERSON){
            obj_meta->rect_params.border_color.alpha = 0;
            obj_meta->text_params.display_text = NULL;
        }
      }
      if (!gst_buffer_map (buf, &in_map_info, GST_MAP_READ)){
          g_print ("gst_buffer_map() error!");
          gst_buffer_unmap(buf, &in_map_info);
          return;
      }
      surface =  (NvBufSurface *) in_map_info.data;
      void* src_data = (char *)malloc(surface->surfaceList[frame_meta->batch_id].dataSize);
      if (src_data == NULL) {
        g_print("Error: failed to malloc src_data \n");
      }
      cudaMemcpy((void *)src_data,
                (void *)surface->surfaceList[frame_meta->batch_id].dataPtr,
                surface->surfaceList[frame_meta->batch_id].dataSize,
                cudaMemcpyDeviceToHost);
      printf("%d", surface->memType);
      printf("%p\n", src_data);
      char *text = "test hhhhh";
      add_text(60, 180, text, batch_meta, frame_meta);
      add_rect(60, 180, 200, 200, batch_meta, frame_meta);
    }
    return GST_PAD_PROBE_OK;
}

保存图片：

      gint frame_width = (gint)surface->surfaceList[frame_meta->batch_id].width;
      gint frame_height = (gint)surface->surfaceList[frame_meta->batch_id].height;
      size_t frame_step = surface->surfaceList[frame_meta->batch_id].pitch;
      
      gint img_width = frame_width / 2;
      gint img_height = frame_height / 2;
 
      cv::Mat frame = cv::Mat(frame_height , frame_width, CV_8UC4, src_data, frame_step);
      cv::Mat out_mat = cv::Mat(cv::Size(frame_width, frame_height), CV_8UC3);
	    cv::cvtColor(frame, out_mat, CV_RGBA2BGR);

      //cv::Size dsize = cv::Size(round(0.5 * frame_width), round(0.5 * frame_height));
      cv::Size dsize = cv::Size(img_width, img_height);
      cv::Mat new_mat;
      cv::resize(out_mat, new_mat, dsize, 0, 0, cv::INTER_AREA);
      
      // char *img_data = (char *)malloc(img_width * img_height * 3);
      // memcpy(img_data, new_mat.data, img_width * img_height * 3);

      // FILE *fp = fopen("1.txt","w");
      //         fwrite(img_data,1,640*360*3,fp);
      //         fclose(fp);
      //         cv::imwrite("1.png", new_mat);

参考的nvidia社区的内容如下

Access frame pointer in deepstream-app - DeepStream SDK - NVIDIA Developer Forums