13、ffmpeg使用nvidia显卡对OAK深度相机进行解码和编码

基本思想：简单使用nvidia的硬件解码进行oak相机的编码和解码学习

一、在本机rtx3060配置好显卡驱动和cuda之后进行下面操作50、ubuntu18.04&20.04+CUDA11.1+cudnn11.3+TensorRT7.2/8.6+Deepsteam5.1+vulkan环境搭建和YOLO5部署_ubuntu18.04安装vulkan_sxj731533730的博客-CSDN博客

二、配置环境和编译库

ubuntu@ubuntu:~$ sudo apt-get install libtool automake autoconf nasm yasm
ubuntu@ubuntu:~$ sudo apt-get install libx264-dev
ubuntu@ubuntu:~$ sudo apt-get install libx265-dev
ubuntu@ubuntu:~$ sudo apt-get install libmp3lame-dev
ubuntu@ubuntu:~$ sudo apt-get install libvpx-dev
ubuntu@ubuntu:~$ sudo apt-get install libfaac-devubuntu@ubuntu:~$ git clone https://git.videolan.org/git/ffmpeg/nv-codec-headers.git
ubuntu@ubuntu:~$ cd nv-codec-headers
ubuntu@ubuntu:~$ make
ubuntu@ubuntu:~$ sudo make installubuntu@ubuntu:~$ git clone https://github.com/FFmpeg/FFmpeg
ubuntu@ubuntu:~$ cd FFmpeg/
ubuntu@ubuntu:~$ mkdir build
ubuntu@ubuntu:~$ cd build/ubuntu@ubuntu:~/FFmpeg$./configure  --prefix=/usr/local --enable-gpl --enable-nonfree --enable-libfreetype --enable-libmp3lame --enable-libvpx --enable-libx264 --enable-libx265 --enable-gpl --enable-version3 --enable-nonfree --enable-shared --enable-ffmpeg --enable-ffplay --enable-ffprobe --enable-libx264 --enable-nvenc --enable-cuda --enable-cuvid --enable-libnpp --extra-cflags=-I/usr/local/cuda/include --extra-ldflags=-L/usr/local/cuda/lib64
ubuntu@ubuntu:~/FFmpeg$ sudo ldconfig
ubuntu@ubuntu:~$

三、使用oak相机进行h264解码测试

cmakelists.txt

cmake_minimum_required(VERSION 3.16)
project(depthai)
set(CMAKE_CXX_STANDARD 11)
find_package(OpenCV REQUIRED)
#message(STATUS ${OpenCV_INCLUDE_DIRS})
#添加头文件
include_directories(${OpenCV_INCLUDE_DIRS})
include_directories(${CMAKE_SOURCE_DIR}/utility)
#链接Opencv库
find_package(depthai CONFIG REQUIRED)
add_executable(depthai main.cpp utility/utility.cpp)
target_link_libraries(depthai ${OpenCV_LIBS}  depthai::opencv -lavformat -lavcodec -lswscale -lavutil -lz)

main.cpp

#include <stdio.h>
#include <string>
#include <iostream>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>extern "C"
{
#include <libavformat/avformat.h>
#include <libavcodec/avcodec.h>
#include <libavutil/imgutils.h>
#include <libswscale/swscale.h>
}#include "utility.hpp"#include "depthai/depthai.hpp"using namespace std::chrono;int main(int argc, char **argv) {dai::Pipeline pipeline;//定义auto cam = pipeline.create<dai::node::ColorCamera>();cam->setBoardSocket(dai::CameraBoardSocket::RGB);cam->setResolution(dai::ColorCameraProperties::SensorResolution::THE_1080_P);cam->setVideoSize(1920, 1080);auto Encoder = pipeline.create<dai::node::VideoEncoder>();Encoder->setDefaultProfilePreset(cam->getVideoSize(), cam->getFps(),dai::VideoEncoderProperties::Profile::H264_MAIN);cam->video.link(Encoder->input);cam->setFps(60);//定义输出auto xlinkoutpreviewOut = pipeline.create<dai::node::XLinkOut>();xlinkoutpreviewOut->setStreamName("out");Encoder->bitstream.link(xlinkoutpreviewOut->input);//结构推送相机dai::Device device(pipeline);//取帧显示auto outqueue = device.getOutputQueue("out", cam->getFps(), false);//maxsize 代表缓冲数据// auto videoFile = std::ofstream("video.h265", std::ios::binary);int width = 1920;int height = 1080;//const AVCodec *pCodec = avcodec_find_decoder(AV_CODEC_ID_H264);const AVCodec *pCodec = avcodec_find_decoder_by_name("h264_cuvid");AVCodecContext *pCodecCtx = avcodec_alloc_context3(pCodec);AVDictionary* decoderOptions = nullptr;av_dict_set(&decoderOptions, "threads", "auto", 0);av_dict_set(&decoderOptions, "gpu", "cuda", 0);int ret = avcodec_open2(pCodecCtx, pCodec, &decoderOptions);if (ret < 0) {//打开解码器printf("Could not open codec.\n");return -1;}if (pCodecCtx != nullptr) {// 打印解码器支持的格式printf("Supported Formats:\n");const AVPixelFormat *pixFmt = pCodec->pix_fmts;while (*pixFmt != AV_PIX_FMT_NONE) {printf("- %s\n", av_get_pix_fmt_name(*pixFmt));pixFmt++;}}AVFrame *picture = av_frame_alloc();picture->width = width;picture->height = height;picture->format = AV_PIX_FMT_NV12;ret = av_frame_get_buffer(picture, 1);if (ret < 0) {printf("av_frame_get_buffer error\n");return -1;}AVFrame *pFrame = av_frame_alloc();pFrame->width = width;pFrame->height = height;pFrame->format = AV_PIX_FMT_NV12;ret = av_frame_get_buffer(pFrame, 1);if (ret < 0) {printf("av_frame_get_buffer error\n");return -1;}AVFrame *pFrameRGB = av_frame_alloc();pFrameRGB->width = width;pFrameRGB->height = height;pFrameRGB->format = AV_PIX_FMT_RGB24;ret = av_frame_get_buffer(pFrameRGB, 1);if (ret < 0) {printf("av_frame_get_buffer error\n");return -1;}int picture_size = av_image_get_buffer_size(AV_PIX_FMT_NV12, width, height,1);//计算这个格式的图片，需要多少字节来存储uint8_t *out_buff = (uint8_t *) av_malloc(picture_size * sizeof(uint8_t));av_image_fill_arrays(picture->data, picture->linesize, out_buff, AV_PIX_FMT_NV12, width,height, 1);//这个函数 是缓存转换格式，可以不用 以为上面已经设置了AV_PIX_FMT_YUV420PSwsContext *img_convert_ctx = sws_getContext(width, height, AV_PIX_FMT_NV12,width, height, AV_PIX_FMT_RGB24, 4,NULL, NULL, NULL);AVPacket *packet = av_packet_alloc();auto startTime = steady_clock::now();int counter = 0;float fps = 0;while (true) {auto h265Packet = outqueue->get<dai::ImgFrame>();//videoFile.write((char *) (h265Packet->getData().data()), h265Packet->getData().size());packet->data = (uint8_t *) h265Packet->getData().data();    //这里填入一个指向完整H264数据帧的指针packet->size = h265Packet->getData().size();        //这个填入H265 数据帧的大小packet->stream_index = 0;ret = avcodec_send_packet(pCodecCtx, packet);if (ret < 0) {printf("avcodec_send_packet \n");continue;}av_packet_unref(packet);int got_picture = avcodec_receive_frame(pCodecCtx, pFrame);av_frame_is_writable(pFrame);if (got_picture < 0) {printf("avcodec_receive_frame \n");continue;}sws_scale(img_convert_ctx, pFrame->data, pFrame->linesize, 0,height,pFrameRGB->data, pFrameRGB->linesize);cv::Mat mRGB(cv::Size(width, height), CV_8UC3);mRGB.data = (unsigned char *) pFrameRGB->data[0];cv::Mat mBGR;cv::cvtColor(mRGB, mBGR, cv::COLOR_RGB2BGR);counter++;auto currentTime = steady_clock::now();auto elapsed = duration_cast<duration<float>>(currentTime - startTime);if (elapsed > seconds(1)) {fps = counter / elapsed.count();counter = 0;startTime = currentTime;}std::stringstream fpsStr;fpsStr << "NN fps: " << std::fixed << std::setprecision(2) << fps;printf("fps %f\n",fps);cv::putText(mBGR, fpsStr.str(), cv::Point(32, 24), cv::FONT_HERSHEY_TRIPLEX, 0.4,cv::Scalar(0, 255, 0));cv::imshow("demo", mBGR);cv::waitKey(1);}return 0;
}

测试结果

四、使用oak进行解码测试

cmakelists.txt

cmake_minimum_required(VERSION 3.16)
project(depthai)
set(CMAKE_CXX_STANDARD 11)
find_package(OpenCV REQUIRED)
#message(STATUS ${OpenCV_INCLUDE_DIRS})
#添加头文件
include_directories(${OpenCV_INCLUDE_DIRS})
include_directories(${CMAKE_SOURCE_DIR}/utility)
#链接Opencv库
find_package(depthai CONFIG REQUIRED)
add_executable(depthai main.cpp utility/utility.cpp)
target_link_libraries(depthai ${OpenCV_LIBS}  depthai::opencv -lavformat -lavcodec -lswscale -lavutil -lz)

main.cpp

#include <iostream>
#include <stdio.h>
#include <string>
#include <iostream>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>extern "C"
{
#include <libavformat/avformat.h>
#include <libavcodec/avcodec.h>
#include <libavutil/imgutils.h>
#include <libswscale/swscale.h>
}#include "fstream"#include "utility.hpp"#include "depthai/depthai.hpp"using namespace std;int main() {int WIDTH = 1920;int HEIGHT = 1080;AVPacket pack;int vpts = 0;uint8_t *in_data[AV_NUM_DATA_POINTERS] = {0};SwsContext *sws_context =NULL;// AVCodecContext *codec_context = nullptr;int in_size[AV_NUM_DATA_POINTERS] = {0};std::ofstream videoFile;// 2.初始化格式转换上下文int fps = 25;sws_context = sws_getCachedContext(sws_context,WIDTH, HEIGHT, AV_PIX_FMT_BGR24,    // 源格式WIDTH, HEIGHT, AV_PIX_FMT_YUV420P,  // 目标格式SWS_BICUBIC,    // 尺寸变化使用算法0, 0, 0);if (NULL == sws_context) {cout << "sws_getCachedContext error" << endl;return -1;}// 3.初始化输出的数据结构AVFrame *yuv = av_frame_alloc();yuv->format = AV_PIX_FMT_YUV420P;yuv->width = WIDTH;yuv->height = HEIGHT;yuv->pts = 0;// 分配yuv空间int ret_code = av_frame_get_buffer(yuv, 32);if (0 != ret_code) {cout << "  yuv init fail" << endl;return -1;}// 4.初始化编码上下文// 4.1找到编码器// const AVCodec *codec = avcodec_find_encoder(AV_CODEC_ID_H264);const AVCodec *codec = avcodec_find_encoder_by_name("h264_nvenc");//nvenc nvenc_h264 h264_nvenc// const AVCodec * codec = avcodec_find_encoder_by_name("nvenc");if (NULL == codec) {cout << "Can't find h264 encoder." << endl;return -1;}// 4.2创建编码器上下文AVCodecContext *codec_context = avcodec_alloc_context3(codec);if (NULL == codec_context) {cout << "avcodec_alloc_context3 failed." << endl;return -1;}// 4.3配置编码器参数// vc->flags           |= AV_CODEC_FLAG_GLOBAL_HEADER;codec_context->codec_id = codec->id;codec_context->thread_count = 16;// 压缩后每秒视频的bit流 5Mcodec_context->bit_rate = 5 * 1024 * 1024;codec_context->width = WIDTH;codec_context->height = HEIGHT;codec_context->time_base = {1, fps};codec_context->framerate = {fps, 1};// 画面组的大小，多少帧一个关键帧codec_context->gop_size = 50;codec_context->max_b_frames = 0;codec_context->pix_fmt = AV_PIX_FMT_YUV420P;codec_context->qmin = 10;codec_context->qmax = 51;AVDictionary *codec_options = nullptr;//(baseline | high | high10 | high422 | high444 | main)
//    av_dict_set(&codec_options, "profile", "baseline", 0);
//    av_dict_set(&codec_options, "preset", "superfast", 0);
//    av_dict_set(&codec_options, "tune", "zerolatency", 0);AVDictionary* decoderOptions = nullptr;av_dict_set(&decoderOptions, "threads", "auto", 0);av_dict_set(&decoderOptions, "gpu", "cuda", 0);//
//    if (codec->id == AV_CODEC_ID_H264) {
//        av_dict_set(&codec_options, "preset", "medium", 0);
//        av_dict_set(&codec_options, "tune", "zerolatency", 0);
//        av_dict_set(&codec_options, "rc", "cbr", 0);
//    }// 4.4打开编码器上下文ret_code = avcodec_open2(codec_context, codec, &codec_options);if (0 != ret_code) {return -1;}videoFile = std::ofstream("video.h264", std::ios::binary);dai::Pipeline pipeline;//定义左相机auto mono = pipeline.create<dai::node::ColorCamera>();mono->setBoardSocket(dai::CameraBoardSocket::RGB);//定义输出auto xlinkOut = pipeline.create<dai::node::XLinkOut>();xlinkOut->setStreamName("rgb");//相机和输出链接mono->video.link(xlinkOut->input);;//结构推送相机dai::Device device(pipeline);//取帧显示auto queue = device.getOutputQueue("rgb", 1);//maxsize 代表缓冲数据while (1) {auto image = queue->get<dai::ImgFrame>();auto frame = image->getCvFrame();memset(&pack, 0, sizeof(pack));in_data[0] = frame.data;// 一行（宽）数据的字节数in_size[0] = frame.cols * frame.elemSize();int h = sws_scale(sws_context, in_data, in_size, 0, frame.rows,yuv->data, yuv->linesize);if (h <= 0) { return -1; }// h264编码yuv->pts = vpts;vpts++;int ret_code = avcodec_send_frame(codec_context, yuv);if (0 != ret_code) { return -1; }ret_code = avcodec_receive_packet(codec_context, &pack);if (0 != ret_code || pack.buf != nullptr) {//cout << "avcodec_receive_packet." << endl;} else {cout << "avcodec_receive_packet contiune." << endl;return -1;}//写入文件videoFile.write((char *) (pack.data), pack.size);}return 0;
}

使用ffplay 播放h264文件，感觉有问题，cpu占比还是比较高，待研究手册

五、使用nvidia进行转码 ,需要opencv进行cuda编译26、ubuntu环境下编译OPENCV的NVCODEC SDK版本进行硬件解码视频和播放测试_sxj731533730的博客-CSDN博客

cmakelist.txt

cmake_minimum_required(VERSION 3.16)
project(A)
set(CMAKE_CXX_STANDARD 11)
find_package(OpenCV REQUIRED)
#message(STATUS ${OpenCV_INCLUDE_DIRS})
#添加头文件
if(WIN32)enable_language(CUDA)
endif(WIN32)# include and link dirs of cuda and tensorrt, you need adapt them if yours are different
# cuda
include_directories(/usr/local/cuda/include)
link_directories(/usr/local/cuda/lib64)
include_directories(${OpenCV_INCLUDE_DIRS})
include_directories(${CMAKE_SOURCE_DIR}/utility)
include_directories(${CMAKE_SOURCE_DIR})
#链接Opencv库
find_package(depthai CONFIG REQUIRED)cuda_add_executable(A main.cpp utility/utility.cpp yuv2bgr.cu)
target_link_libraries(A ${OpenCV_LIBS}  depthai::opencv -lavformat -lavcodec -lswscale -lavutil -lz)
target_link_libraries(A nvinfer)
target_link_libraries(A nvonnxparser)
target_link_libraries(A cudart)
target_link_libraries(A nvinfer_plugin)

main.cpp

#include <stdio.h>
#include <string>
#include <iostream>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>extern "C"
{
#include <libavformat/avformat.h>
#include <libavcodec/avcodec.h>
#include <libavutil/imgutils.h>
#include <libswscale/swscale.h>
}#include <cuda_runtime.h>
#include "utility.hpp"
#include "yuv2bgr.h"
#include "depthai/depthai.hpp"using namespace std::chrono;int main(int argc, char **argv) {dai::Pipeline pipeline;//定义auto cam = pipeline.create<dai::node::ColorCamera>();cam->setBoardSocket(dai::CameraBoardSocket::RGB);cam->setResolution(dai::ColorCameraProperties::SensorResolution::THE_1080_P);cam->setVideoSize(1920, 1080);auto Encoder = pipeline.create<dai::node::VideoEncoder>();Encoder->setDefaultProfilePreset(cam->getVideoSize(), cam->getFps(),dai::VideoEncoderProperties::Profile::H264_MAIN);cam->video.link(Encoder->input);cam->setFps(60);//定义输出auto xlinkoutpreviewOut = pipeline.create<dai::node::XLinkOut>();xlinkoutpreviewOut->setStreamName("out");Encoder->bitstream.link(xlinkoutpreviewOut->input);//结构推送相机dai::Device device(pipeline);//取帧显示auto outqueue = device.getOutputQueue("out", cam->getFps(), false);//maxsize 代表缓冲数据// auto videoFile = std::ofstream("video.h265", std::ios::binary);int width = 1920;int height = 1080;//const AVCodec *pCodec = avcodec_find_decoder(AV_CODEC_ID_H264);const AVCodec *pCodec = avcodec_find_decoder_by_name("h264_cuvid");AVCodecContext *pCodecCtx = avcodec_alloc_context3(pCodec);AVDictionary* decoderOptions = nullptr;av_dict_set(&decoderOptions, "threads", "auto", 0);av_dict_set(&decoderOptions, "gpu", "cuda", 0);int ret = avcodec_open2(pCodecCtx, pCodec, &decoderOptions);if (ret < 0) {//打开解码器printf("Could not open codec.\n");return -1;}if (pCodecCtx != nullptr) {// 打印解码器支持的格式printf("Supported Formats:\n");const AVPixelFormat *pixFmt = pCodec->pix_fmts;while (*pixFmt != AV_PIX_FMT_NONE) {printf("- %s\n", av_get_pix_fmt_name(*pixFmt));pixFmt++;}}AVFrame *picture = av_frame_alloc();picture->width = width;picture->height = height;picture->format = AV_PIX_FMT_NV12;ret = av_frame_get_buffer(picture, 1);if (ret < 0) {printf("av_frame_get_buffer error\n");return -1;}AVFrame *pFrame = av_frame_alloc();pFrame->width = width;pFrame->height = height;pFrame->format = AV_PIX_FMT_NV12;ret = av_frame_get_buffer(pFrame, 1);if (ret < 0) {printf("av_frame_get_buffer error\n");return -1;}AVFrame *pFrameRGB = av_frame_alloc();pFrameRGB->width = width;pFrameRGB->height = height;pFrameRGB->format = AV_PIX_FMT_RGB24;ret = av_frame_get_buffer(pFrameRGB, 1);if (ret < 0) {printf("av_frame_get_buffer error\n");return -1;}int picture_size = av_image_get_buffer_size(AV_PIX_FMT_NV12, width, height,1);//计算这个格式的图片，需要多少字节来存储uint8_t *out_buff = (uint8_t *) av_malloc(picture_size * sizeof(uint8_t));av_image_fill_arrays(picture->data, picture->linesize, out_buff, AV_PIX_FMT_NV12, width,height, 1);//这个函数 是缓存转换格式，可以不用 以为上面已经设置了AV_PIX_FMT_YUV420PSwsContext *img_convert_ctx = sws_getContext(width, height, AV_PIX_FMT_NV12,width, height, AV_PIX_FMT_RGB24, 4,NULL, NULL, NULL);AVPacket *packet = av_packet_alloc();auto startTime = steady_clock::now();int counter = 0;float fps = 0;bool is_first_frame=false;int bufsize0, bufsize1, resolution;cv::cuda::GpuMat reqMat,resMat;while (true) {auto h265Packet = outqueue->get<dai::ImgFrame>();//videoFile.write((char *) (h265Packet->getData().data()), h265Packet->getData().size());packet->data = (uint8_t *) h265Packet->getData().data();    //这里填入一个指向完整H264数据帧的指针packet->size = h265Packet->getData().size();        //这个填入H265 数据帧的大小packet->stream_index = 0;ret = avcodec_send_packet(pCodecCtx, packet);if (ret < 0) {// printf("avcodec_send_packet \n");continue;}av_packet_unref(packet);int got_picture = avcodec_receive_frame(pCodecCtx, pFrame);av_frame_is_writable(pFrame);if (got_picture < 0) {// printf("avcodec_receive_frame \n");continue;}if (!is_first_frame) {bufsize0 = pFrame->height * pFrame->linesize[0];bufsize1 = pFrame->height * pFrame->linesize[1] / 2;resolution = pFrame->height * pFrame->width;//硬解码reqMat.create(pFrame->height, pFrame->width, CV_8UC3);resMat.create(pFrame->height, pFrame->width, CV_8UC3);resMat.step = pFrameRGB->linesize[0];is_first_frame = true;}cudaMemcpy(reqMat.data, pFrame->data[0], bufsize0,  cudaMemcpyHostToDevice);cudaMemcpy(reqMat.data + bufsize0, pFrame->data[1], bufsize1, cudaMemcpyHostToDevice);cvtColor(reqMat.data, resMat.data, resolution, pFrame->height, pFrame->width, pFrame->linesize[0]);//        sws_scale(img_convert_ctx, pFrame->data, pFrame->linesize, 0,
//                  height,
//                  pFrameRGB->data, pFrameRGB->linesize);cv::Mat mBGR(width, height, CV_8UC3);resMat.download(mBGR);//        cv::Mat mRGB(cv::Size(width, height), CV_8UC3);
//        mRGB.data = (unsigned char *) pFrameRGB->data[0];
//        cv::Mat mBGR;
//        cv::cvtColor(mRGB, mBGR, cv::COLOR_RGB2BGR);counter++;auto currentTime = steady_clock::now();auto elapsed = duration_cast<duration<float>>(currentTime - startTime);if (elapsed > seconds(1)) {fps = counter / elapsed.count();counter = 0;startTime = currentTime;}std::stringstream fpsStr;fpsStr << "NN fps: " << std::fixed << std::setprecision(2) << fps;//printf("fps %f\n",fps);cv::putText(mBGR, fpsStr.str(), cv::Point(32, 24), cv::FONT_HERSHEY_TRIPLEX, 0.4,cv::Scalar(0, 255, 0));cv::imshow("demo", mBGR);cv::waitKey(1);}return 0;
}

yuv2bgr.h ：摘自https://github.com/chinahbcq/ffmpeg_hw_decode.git

/**  *  Copyright (c) 2017 LGPL, Inc. All Rights Reserved*  @author Chen Qian ([e-mail])*  @date 2017.04.22 14:32:02*  @brief gpu颜色空间转换*/
#ifdef __cplusplus
extern "C"{
#endifint cvtColor(unsigned char *d_req,unsigned char *d_res,int resolution,int height, int width, int linesize);#ifdef __cplusplus
}
#endif

yuv2bgr.cu ：摘自https://github.com/chinahbcq/ffmpeg_hw_decode.git

/**  *  Copyright (c) 2017 LGPL, Inc. All Rights Reserved*  @author Chen Qian ([e-mail])*  @date 2017.04.22 14:32:13*  @brief gpu颜色空间转换*/
#include <stdio.h>
// For the CUDA runtime routines (prefixed with "cuda_")
#include <cuda_runtime.h>
#include <cuda_profiler_api.h>
#include <curand.h>
#include "yuv2bgr.h"__global__ void
cvtNV12_BGR(unsigned char *A, unsigned char *B, const int height,const int width,const int linesize)
{int IDX = blockDim.x * blockIdx.x + threadIdx.x;long len = width * height;if (IDX < len) {int j = IDX % width;int i = (IDX - j) / width;int bgr[3];int yIdx, uvIdx, idx;int y,u,v;yIdx = i * linesize + j;uvIdx = linesize * height + (i / 2) * linesize + j - j % 2;y = A[yIdx];u = A[uvIdx];v = A[uvIdx + 1];bgr[0] = y + 1.772 * (u-128);bgr[1] = y - 0.34414 * (u -128) - 0.71414 * (v-128);bgr[2] = y + 1.402 * (v - 128); for (int k = 0; k < 3; k++) {idx = (i * width + j) * 3 + k;if (bgr[k] >=0 && bgr[k] < 255) {B[idx] = bgr[k];} else {B[idx] = bgr[k] < 0 ? 0 : 255;}	}	}
}int cvtColor(unsigned char *d_req,unsigned char *d_res,int resolution,int height,int width,int linesize) {int threadsPerBlock = 256;int blocksPerGrid =(resolution + threadsPerBlock - 1) / threadsPerBlock;cvtNV12_BGR<<<blocksPerGrid, threadsPerBlock>>>(d_req, d_res, height, width, linesize);return 0;
}

测试效果图，但是cpu还是占比比较高，还是待调查

关掉cv::show显示这个函数就瞬间降低了cpu的使用率-100%，mmp

结合实际项目实时推流画面，因为追踪使用纯cpu，耗cpu使用率 

参考：https://github.com/chinahbcq/ffmpeg_hw_decode.git 

另一位佬给的参考链接，没开始看：GitHub - shouxieai/hard_decode_trt: Yolov5 inference on NVDec hardware decoder