详解opencv rtsp 硬件解码

#include <iostream>
#include "opencv2/opencv_modules.hpp"
#if defined(HAVE_OPENCV_CUDACODEC)
#include <string>
#include <vector>
#include <algorithm>
#include <numeric>
#include <opencv2/opencv.hpp>
#include <opencv2/core.hpp>
#include <opencv2/core/opengl.hpp>
#include <opencv2/cudacodec.hpp>
#include <opencv2/highgui.hpp>
#if _DEBUG
#pragma comment(lib,"opencv_world460.lib")
#else 
#pragma comment(lib,"opencv_world460.lib")
#endif
int main()
{
    cv::cuda::printCudaDeviceInfo(cv::cuda::getDevice());
    int count = cv::cuda::getCudaEnabledDeviceCount();
    printf("GPU Device Count : %d \n", count);
    const std::string fname("rtsp://127.0.0.1/101-640.mkv"); //视频文件
   // const std::string fname("test_222.mp4"); //视频文件
   // cv::namedWindow("CPU", cv::WINDOW_NORMAL);
    cv::namedWindow("GPU", cv::WINDOW_OPENGL);
    cv::cuda::setGlDevice();
    cv::Mat frame;
    cv::VideoCapture reader(fname);
    cv::cuda::GpuMat d_frame;
    cv::Ptr<cv::cudacodec::VideoReader> d_reader = cv::cudacodec::createVideoReader(fname);
    cv::TickMeter tm;
    std::vector<double> cpu_times;
    std::vector<double> gpu_times;
    int gpu_frame_count = 0, cpu_frame_count = 0;
#if 0
    for (;;)
    {
        tm.reset(); tm.start();
        if (!reader.read(frame))
            break;
        tm.stop();
        cpu_times.push_back(tm.getTimeMilli());
        cpu_frame_count++;
        cv::imshow("CPU", frame);
        if (cv::waitKey(1) > 0)
            break;
    }
#endif
    for (;;)
    {
        tm.reset();
        tm.start();
        if (!d_reader->nextFrame(d_frame))
            break;
        tm.stop();
        //d_frame.step = d_frame.cols * d_frame.channels();
        //cv::cuda::GpuMat gpuMat_Temp = d_frame.clone();
        gpu_times.push_back(tm.getTimeMilli());
        gpu_frame_count++;
        if (gpu_frame_count > 2)
        {
            cv::Mat test;
            d_frame.download(test);
            d_frame.release();
            // cv::cvtColor(test, test, cv::COLOR_BGRA2BGR);
             //cv::imwrite("./test1.jpg", test);
            cv::imshow("GPU", test);
        }
        if (cv::waitKey(1) > 0)
            break;
    }
    if (!cpu_times.empty() && !gpu_times.empty())
    {
        std::cout << std::endl << "Results:" << std::endl;
        std::sort(cpu_times.begin(), cpu_times.end());
        std::sort(gpu_times.begin(), gpu_times.end());
        double cpu_avg = std::accumulate(cpu_times.begin(), cpu_times.end(), 0.0) / cpu_times.size();
        double gpu_avg = std::accumulate(gpu_times.begin(), gpu_times.end(), 0.0) / gpu_times.size();
        std::cout << "CPU : Avg : " << cpu_avg << " ms FPS : " << 1000.0 / cpu_avg << " Frames " << cpu_frame_count << std::endl;
        std::cout << "GPU : Avg : " << gpu_avg << " ms FPS : " << 1000.0 / gpu_avg << " Frames " << gpu_frame_count << std::endl;
    }
    return 0;
}

import PyNvCodec as nvc
import PytorchNvCodec as pnvc  
   while True:
        # Read data.
        # Amount doesn't really matter, will be updated later on during decode.
        bits = proc.stdout.read(read_size)
        if not len(bits):
            print("Can't read data from pipe")
            break
        else:
            rt += len(bits)
        # Decode
        enc_packet = np.frombuffer(buffer=bits, dtype=np.uint8)
        pkt_data = nvc.PacketData()
        try:
            surf = nvdec.DecodeSurfaceFromPacket(enc_packet, pkt_data)    # 获取流的数据
            # Convert to planar RGB
            rgb_pln = to_rgb.run(surf)   # 转换到rgb_pln
            if rgb_pln.Empty():
                break
            # PROCESS YOUR TENSOR HERE.
            # THIS DUMMY PROCESSING JUST ADDS RANDOM ROTATION.
            src_tensor = surface_to_tensor(rgb_pln)  # 转化为Tensor(),数据存储在GPU中
            dst_tensor = T.RandomRotation(degrees=(-1, 1))(src_tensor)
            surface_rgb = tensor_to_surface(dst_tensor, gpu_id)
            # Convert back to NV12
            dst_surface = to_nv12.run(surface_rgb) # 再转换回码流
            if src_surface.Empty():
                break
        # Handle HW exceptions in simplest possible way by decoder respawn
        except nvc.HwResetException:
            nvdec = nvc.PyNvDecoder(w, h, f, c, g)
            continue

sudo apt-get update 
sudo apt-get install build-essential cmake git pkg-config 
sudo apt-get install libjpeg8-dev libtiff4-dev libjasper-dev libpng12-dev 
sudo apt-get install libgtk2.0-dev 
sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev 
sudo apt-get install libatlas-base-dev gfortran 
//在opencv里面安装gstreamer插件 
sudo apt-get install gstreamer1.0-tools gstreamer1.0-alsa gstreamer1.0-plugins-base gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav 
sudo apt-get install libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev libgstreamer-plugins-good1.0-dev libgstreamer-plugins-bad1.0-dev 
cd /home/opencv 
git clone https://github.com/opencv.git 
cd opencv 
git checkout 4.7.0 
cd /home/opcv 
nkdir build 
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D CUDA_GENERATION=Kepler .. 
make -j4 
sudo make install

int main()
{
   // std::cout << cv::getBuildInformation() << std::endl;
    using std::chrono::steady_clock;
    typedef std::chrono::milliseconds milliseconds_type;
    const int interval = 15;
    std::stringstream ss;
    std::string rtsp_url = "rtsp://127.0.0.1/101-640.mkv";
    size_t latency = 200;
    size_t frame_width = 1920;
    size_t frame_height = 1080;
    size_t framerate = 15;
    ss << "rtspsrc location=" << rtsp_url << " latency=" << latency << " ! application/x-rtp, media=video, encoding-name=H264 "
        << "! rtph264depay ! video/x-h264, clock-rate=90000, width=" << frame_width << ", height=" << frame_height << ", framerate="
        << framerate << "/1 ! nvv4l2decoder ! video/x-raw(memory:NVMM), width=" << frame_width << ", height=" << frame_height
        << ", framerate=" << framerate << "/1 ! nvvideoconvert ! video/x-raw, format=BGRx ! videoconvert ! video/x-raw, format=BGR ! appsink";
    std::cout << ss.str() << std::endl;
    cv::VideoCapture cap = cv::VideoCapture(ss.str(), cv::CAP_GSTREAMER);
    if (!cap.isOpened())
    {
        std::cerr << "error to open camera." << std::endl;
        return -1;
    }
    std::cout << cv::getBuildInformation() << std::endl;
    cv::Mat frame;
    steady_clock::time_point start = steady_clock::now();
    size_t frame_idx = 0;
    while (1)
    {
        bool ret = cap.read(frame);
        if (ret)
        {
            // cv::imwrite("tmp.jpg", frame);
            ++frame_idx;
        }
        if (frame_idx % interval == 0)
        {
            steady_clock::time_point end = steady_clock::now();
            milliseconds_type span = std::chrono::duration_cast<milliseconds_type>(end - start);
            std::cout << "it took " << span.count() / frame_idx << " millisencods." << std::endl;
            start = end;
        }
    }
    return 0;
}