视频流GPU解码在ffempg的实现-GPU解码器
Posted 风翼科技
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1.gpu解码器的基本调用流程
要做视频流解码，必须要了解cuda自身的解码流，因为二者是一样的底层实现，不一样的上层调用
那cuda的解码流程是如何的呢
在 https://developer.nvidia.com/nvidia-video-codec-sdk 下载 Video_Codec_SDK_8.0.14
解压开来
在sampls里面有几个针对不同场景应用的小例子，如果不知道自己该参考哪一个，就需要去看开发文档，doc里面有一个 NVENC_VideoEncoder_API_ProgGuide.pdf 文档
由于我这里使用的是视频流解码，所以最好去查看NvTranscoder这个demo.
在NvTranscoder里面主要关注红框中的这几个文件
NvTranscoder.cpp实现了主函数
VideoDecoder.cpp实现了解码
FrameQueue.cpp实现了gpu解码后的数据回调
先看NvTranscoder.cpp的主要代码（比较冗余，有兴趣可以全部看）
int main(int argc, char* argv[]) { #if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64) typedef HMODULE CUDADRIVER; #else typedef void *CUDADRIVER; #endif CUDADRIVER hHandleDriver = 0; __cu(cuInit(0, __CUDA_API_VERSION, hHandleDriver)); __cu(cuvidInit(0)); EncodeConfig encodeConfig = { 0 }; encodeConfig.endFrameIdx = INT_MAX; encodeConfig.bitrate = 5000000; encodeConfig.rcMode = NV_ENC_PARAMS_RC_CONSTQP; encodeConfig.gopLength = NVENC_INFINITE_GOPLENGTH; encodeConfig.codec = NV_ENC_H264; encodeConfig.fps = 0; encodeConfig.qp = 28; encodeConfig.i_quant_factor = DEFAULT_I_QFACTOR; encodeConfig.b_quant_factor = DEFAULT_B_QFACTOR; encodeConfig.i_quant_offset = DEFAULT_I_QOFFSET; encodeConfig.b_quant_offset = DEFAULT_B_QOFFSET; encodeConfig.presetGUID = NV_ENC_PRESET_DEFAULT_GUID; encodeConfig.pictureStruct = NV_ENC_PIC_STRUCT_FRAME; NVENCSTATUS nvStatus = CNvHWEncoder::ParseArguments(&encodeConfig, argc, argv); if (nvStatus != NV_ENC_SUCCESS) { PrintHelp(); return 1; } if (!encodeConfig.inputFileName || !encodeConfig.outputFileName) { PrintHelp(); return 1; } encodeConfig.fOutput = fopen(encodeConfig.outputFileName, "wb"); if (encodeConfig.fOutput == NULL) { PRINTERR("Failed to create \\"%s\\"\\n", encodeConfig.outputFileName); return 1; } //init cuda CUcontext cudaCtx; CUdevice device; __cu(cuDeviceGet(&device, encodeConfig.deviceID)); __cu(cuCtxCreate(&cudaCtx, CU_CTX_SCHED_AUTO, device)); CUcontext curCtx; CUvideoctxlock ctxLock; __cu(cuCtxPopCurrent(&curCtx)); __cu(cuvidCtxLockCreate(&ctxLock, curCtx)); CudaDecoder* pDecoder = new CudaDecoder; FrameQueue* pFrameQueue = new CUVIDFrameQueue(ctxLock); pDecoder->InitVideoDecoder(encodeConfig.inputFileName, ctxLock, pFrameQueue, encodeConfig.width, encodeConfig.height); int decodedW, decodedH, decodedFRN, decodedFRD, isProgressive; pDecoder->GetCodecParam(&decodedW, &decodedH, &decodedFRN, &decodedFRD, &isProgressive); if (decodedFRN <= 0 || decodedFRD <= 0) { decodedFRN = 30; decodedFRD = 1; } if(encodeConfig.width <= 0 || encodeConfig.height <= 0) { encodeConfig.width = decodedW; encodeConfig.height = decodedH; } float fpsRatio = 1.f; if (encodeConfig.fps <= 0) { encodeConfig.fps = decodedFRN / decodedFRD; } else { fpsRatio = (float)encodeConfig.fps * decodedFRD / decodedFRN; } encodeConfig.pictureStruct = (isProgressive ? NV_ENC_PIC_STRUCT_FRAME : 0); pFrameQueue->init(encodeConfig.width, encodeConfig.height); VideoEncoder* pEncoder = new VideoEncoder(ctxLock); assert(pEncoder->GetHWEncoder()); nvStatus = pEncoder->GetHWEncoder()->Initialize(cudaCtx, NV_ENC_DEVICE_TYPE_CUDA); if (nvStatus != NV_ENC_SUCCESS) return 1; encodeConfig.presetGUID = pEncoder->GetHWEncoder()->GetPresetGUID(encodeConfig.encoderPreset, encodeConfig.codec); printf("Encoding input : \\"%s\\"\\n", encodeConfig.inputFileName); printf(" output : \\"%s\\"\\n", encodeConfig.outputFileName); printf(" codec : \\"%s\\"\\n", encodeConfig.codec == NV_ENC_HEVC ? "HEVC" : "H264"); printf(" size : %dx%d\\n", encodeConfig.width, encodeConfig.height); printf(" bitrate : %d bits/sec\\n", encodeConfig.bitrate); printf(" vbvMaxBitrate : %d bits/sec\\n", encodeConfig.vbvMaxBitrate); printf(" vbvSize : %d bits\\n", encodeConfig.vbvSize); printf(" fps : %d frames/sec\\n", encodeConfig.fps); printf(" rcMode : %s\\n", encodeConfig.rcMode == NV_ENC_PARAMS_RC_CONSTQP ? "CONSTQP" : encodeConfig.rcMode == NV_ENC_PARAMS_RC_VBR ? "VBR" : encodeConfig.rcMode == NV_ENC_PARAMS_RC_CBR ? "CBR" : encodeConfig.rcMode == NV_ENC_PARAMS_RC_VBR_MINQP ? "VBR MINQP (deprecated)" : encodeConfig.rcMode == NV_ENC_PARAMS_RC_CBR_LOWDELAY_HQ ? "CBR_LOWDELAY_HQ" : encodeConfig.rcMode == NV_ENC_PARAMS_RC_CBR_HQ ? "CBR_HQ" : encodeConfig.rcMode == NV_ENC_PARAMS_RC_VBR_HQ ? "VBR_HQ" : "UNKNOWN"); if (encodeConfig.gopLength == NVENC_INFINITE_GOPLENGTH) printf(" goplength : INFINITE GOP \\n"); else printf(" goplength : %d \\n", encodeConfig.gopLength); printf(" B frames : %d \\n", encodeConfig.numB); printf(" QP : %d \\n", encodeConfig.qp); printf(" preset : %s\\n", (encodeConfig.presetGUID == NV_ENC_PRESET_LOW_LATENCY_HQ_GUID) ? "LOW_LATENCY_HQ" : (encodeConfig.presetGUID == NV_ENC_PRESET_LOW_LATENCY_HP_GUID) ? "LOW_LATENCY_HP" : (encodeConfig.presetGUID == NV_ENC_PRESET_HQ_GUID) ? "HQ_PRESET" : (encodeConfig.presetGUID == NV_ENC_PRESET_HP_GUID) ? "HP_PRESET" : (encodeConfig.presetGUID == NV_ENC_PRESET_LOSSLESS_HP_GUID) ? "LOSSLESS_HP" : "LOW_LATENCY_DEFAULT"); printf("\\n"); nvStatus = pEncoder->GetHWEncoder()->CreateEncoder(&encodeConfig); if (nvStatus != NV_ENC_SUCCESS) return 1; nvStatus = pEncoder->AllocateIOBuffers(&encodeConfig); if (nvStatus != NV_ENC_SUCCESS) return 1; unsigned long long lStart, lEnd, lFreq; NvQueryPerformanceCounter(&lStart); //start decoding thread #ifdef _WIN32 HANDLE decodeThread = CreateThread(NULL, 0, DecodeProc, (LPVOID)pDecoder, 0, NULL); #else pthread_t pid; pthread_create(&pid, NULL, DecodeProc, (void*)pDecoder); #endif //start encoding thread int frmProcessed = 0; int frmActual = 0; while(!(pFrameQueue->isEndOfDecode() && pFrameQueue->isEmpty()) ) { CUVIDPARSERDISPINFO pInfo; if(pFrameQueue->dequeue(&pInfo)) { CUdeviceptr dMappedFrame = 0; unsigned int pitch; CUVIDPROCPARAMS oVPP = { 0 }; oVPP.progressive_frame = pInfo.progressive_frame; oVPP.second_field = 0; oVPP.top_field_first = pInfo.top_field_first; oVPP.unpaired_field = (pInfo.progressive_frame == 1 || pInfo.repeat_first_field <= 1); cuvidMapVideoFrame(pDecoder->GetDecoder(), pInfo.picture_index, &dMappedFrame, &pitch, &oVPP); EncodeFrameConfig stEncodeConfig = { 0 }; NV_ENC_PIC_STRUCT picType = (pInfo.progressive_frame || pInfo.repeat_first_field >= 2 ? NV_ENC_PIC_STRUCT_FRAME : (pInfo.top_field_first ? NV_ENC_PIC_STRUCT_FIELD_TOP_BOTTOM : NV_ENC_PIC_STRUCT_FIELD_BOTTOM_TOP)); stEncodeConfig.dptr = dMappedFrame; stEncodeConfig.pitch = pitch; stEncodeConfig.width = encodeConfig.width; stEncodeConfig.height = encodeConfig.height; int dropOrDuplicate = MatchFPS(fpsRatio, frmProcessed, frmActual); for (int i = 0; i <= dropOrDuplicate; i++) { pEncoder->EncodeFrame(&stEncodeConfig, picType); frmActual++; } frmProcessed++; cuvidUnmapVideoFrame(pDecoder->GetDecoder(), dMappedFrame); pFrameQueue->releaseFrame(&pInfo); } } pEncoder->EncodeFrame(NULL, NV_ENC_PIC_STRUCT_FRAME, true); #ifdef _WIN32 WaitForSingleObject(decodeThread, INFINITE); #else pthread_join(pid, NULL); #endif if (pEncoder->GetEncodedFrames() > 0) { NvQueryPerformanceCounter(&lEnd); NvQueryPerformanceFrequency(&lFreq); double elapsedTime = (double)(lEnd - lStart)/(double)lFreq; printf("Total time: %fms, Decoded Frames: %d, Encoded Frames: %d, Average FPS: %f\\n", elapsedTime * 1000, pDecoder->m_decodedFrames, pEncoder->GetEncodedFrames(), (float)pEncoder->GetEncodedFrames() / elapsedTime); } pEncoder->Deinitialize(); delete pDecoder; delete pEncoder; delete pFrameQueue; cuvidCtxLockDestroy(ctxLock); __cu(cuCtxDestroy(cudaCtx)); return 0; }
下面这个是我的主要流程精简版
int main(int argc, char* argv[]) { #if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64) typedef HMODULE CUDADRIVER; #else typedef void *CUDADRIVER; #endif CUDADRIVER hHandleDriver = 0; __cu(cuInit(0, __CUDA_API_VERSION, hHandleDriver));//初始化cuda环境,必须的 __cu(cuvidInit(0)); //初始化解码器 //init cuda CUcontext cudaCtx; CUdevice device; __cu(cuDeviceGet(&device, deviceID)); //得到显卡操作对象，deviceID是显卡的id，一般说来如果一张显卡，id就是0，两张就是0,1 __cu(cuCtxCreate(&cudaCtx, CU_CTX_SCHED_AUTO, device)); //创建对应显卡的运行环境 CUcontext curCtx; CUvideoctxlock ctxLock; __cu(cuCtxPopCurrent(&curCtx));//弹出当前CPU线程的里面的可用的cuda环境，也就是上面创建的环境 __cu(cuvidCtxLockCreate(&ctxLock, curCtx));//为gpu上锁 CudaDecoder* pDecoder = new CudaDecoder;//创建cuda解码对象（重点查看） FrameQueue* pFrameQueue = new CUVIDFrameQueue(ctxLock);//创建解码输出队列 pDecoder->InitVideoDecoder(encodeConfig.inputFileName, ctxLock, pFrameQueue, encodeConfig.width, encodeConfig.height);//初始化解码器（重点查看） pFrameQueue->init(encodeConfig.width, encodeConfig.height);//初始化解码输出队列 //启动解码线程 #ifdef _WIN32 HANDLE decodeThread = CreateThread(NULL, 0, DecodeProc, (LPVOID)pDecoder, 0, NULL); #else pthread_t pid; pthread_create(&pid, NULL, DecodeProc, (void*)pDecoder); #endif //start encoding thread int frmProcessed = 0; int frmActual = 0; //从解码输出队列里面拉取解出来的数据 while(!(pFrameQueue->isEndOfDecode() && pFrameQueue->isEmpty()) ) { CUVIDPARSERDISPINFO pInfo; if(pFrameQueue->dequeue(&pInfo)) { CUdeviceptr dMappedFrame = 0; unsigned int pitch; CUVIDPROCPARAMS oVPP = { 0 }; oVPP.progressive_frame = pInfo.progressive_frame; oVPP.second_field = 0; oVPP.top_field_first = pInfo.top_field_first; oVPP.unpaired_field = (pInfo.progressive_frame == 1 || pInfo.repeat_first_field <= 1); //获取数据在GPU中的地址dMappedFrame，大小为pitch个 cuvidMapVideoFrame(pDecoder->GetDecoder(), pInfo.picture_index, &dMappedFrame, &pitch, &oVPP); //因为解码后的数据地址还是在GPU中，所有需要找到 unsigned int nv12_size = pitch * (pDecoder->iHeight + pDecoder->iHeight/2); // 12bpp //从GPU内存拷贝到pa->pFrameBuffer（CPU的内存地址） oResult = cuMemcpyDtoH(pa->pFrameBuffer, dMappedFrame, nv12_size); //释放GPU中的内存 cuvidUnmapVideoFrame(pDecoder->GetDecoder(), dMappedFrame); pFrameQueue->releaseFrame(&pInfo); } } #ifdef _WIN32 WaitForSingleObject(decodeThread, INFINITE); #else pthread_join(pid, NULL); #endif delete pDecoder; delete pFrameQueue; cuvidCtxLockDestroy(ctxLock); __cu(cuCtxDestroy(cudaCtx)); return 0; }
其中的解码器的流程调用是重点关注的
new解码器
CudaDecoder::CudaDecoder() : m_videoSource(NULL), m_videoParser(NULL), m_videoDecoder(NULL), m_ctxLock(NULL), m_decodedFrames(0), m_bFinish(false) { }
初始化解码器，这里创建了三个对象，一个是源，一个是解码器，一个是解析器，
//初始化Gpu解码器 void CudaDecoder::InitVideoDecoder(const char* videoPath, CUvideoctxlock ctxLock, FrameQueue* pFrameQueue, int targetWidth, int targetHeight) { assert(videoPath);//数据流地址 assert(ctxLock); assert(pFrameQueue); m_pFrameQueue = pFrameQueue; CUresult oResult; m_ctxLock = ctxLock; //init video source CUVIDSOURCEPARAMS oVideoSourceParameters; memset(&oVideoSourceParameters, 0, sizeof(CUVIDSOURCEPARAMS)); oVideoSourceParameters.pUserData = this; oVideoSourceParameters.pfnVideoDataHandler = HandleVideoData; oVideoSourceParameters.pfnAudioDataHandler = NULL; oResult = cuvidCreateVideoSource(&m_videoSource, videoPath, &oVideoSourceParameters);//创建数据源对象，目的是在回调里面得到数据包，然后在回调里面可以用m_videoParser处理，只支持文件 if (oResult != CUDA_SUCCESS) { fprintf(stderr, "cuvidCreateVideoSource failed\\n"); fprintf(stderr, "Please check if the path exists, or the video is a valid H264 file\\n"); exit(-1); } //init video decoder CUVIDEOFORMAT oFormat; cuvidGetSourceVideoFormat(m_videoSource, &oFormat, 0); if (oFormat.codec != cudaVideoCodec_H264 && oFormat.codec != cudaVideoCodec_HEVC) { fprintf(stderr, "The sample only supports H264/HEVC input video!\\n"); exit(-1); } if (oFormat.chroma_format != cudaVideoChromaFormat_420) { fprintf(stderr, "The sample only supports 4:2:0 chroma!\\n"); exit(-1); } CUVIDDECODECREATEINFO oVideoDecodeCreateInfo; memset(&oVideoDecodeCreateInfo, 0, sizeof(CUVIDDECODECREATEINFO)); oVideoDecodeCreateInfo.CodecType = oFormat.codec; oVideoDecodeCreateInfo.ulWidth = oFormat.coded_width; oVideoDecodeCreateInfo.ulHeight = oFormat.coded_height; oVideoDecodeCreateInfo.ulNumDecodeSurfaces = 8; if ((oVideoDecodeCreateInfo.CodecType == cudaVideoCodec_H264) || (oVideoDecodeCreateInfo.CodecType == cudaVideoCodec_H264_SVC) || (oVideoDecodeCreateInfo.CodecType == cudaVideoCodec_H264_MVC)) { // assume worst-case of 20 decode surfaces for H264 oVideoDecodeCreateInfo.ulNumDecodeSurfaces = 20; } if (oVideoDecodeCreateInfo.CodecType == cudaVideoCodec_VP9) oVideoDecodeCreateInfo.ulNumDecodeSurfaces = 12; if (oVideoDecodeCreateInfo.CodecType == cudaVideoCodec_HEVC) { // ref HEVC spec: A.4.1 General tier and level limits int MaxLumaPS = 35651584; // currently assuming level 6.2, 8Kx4K int MaxDpbPicBuf = 6; int PicSizeInSamplesY = oVideoDecodeCreateInfo.ulWidth * oVideoDecodeCreateInfo.ulHeight; int MaxDpbSize; if (PicSizeInSamplesY <= (MaxLumaPS>>2)) MaxDpbSize = MaxDpbPicBuf * 4; else if (PicSizeInSamplesY <= (MaxLumaPS>>1)) MaxDpbSize = MaxDpbPicBuf * 2; else if (PicSizeInSamplesY <= ((3*MaxLumaPS)>>2)) MaxDpbSize = (MaxDpbPicBuf * 4) / 3; else MaxDpbSize = MaxDpbPicBuf; MaxDpbSize = MaxDpbSize < 16 ? MaxDpbSize : 16; oVideoDecodeCreateInfo.ulNumDecodeSurfaces = MaxDpbSize + 4; } oVideoDecodeCreateInfo.ChromaFormat = oFormat.chroma_format; oVideoDecodeCreateInfo.OutputFormat = cudaVideoSurfaceFormat_NV12;//设置输出格式为NV12 oVideoDecodeCreateInfo.DeinterlaceMode = cudaVideoDeinterlaceMode_Weave; if (targetWidth <= 0 || targetHeight <= 0) { oVideoDecodeCreateInfo.ulTargetWidth = oFormat.display_area.right - oFormat.display_area.left; oVideoDecodeCreateInfo.ulTargetHeight = oFormat.display_area.bottom - oFormat.display_area.top; } else { oVideoDecodeCreateInfo.ulTargetWidth = targetWidth;//输出长宽 oVideoDecodeCreateInfo.ulTargetHeight = targetHeight; } oVideoDecodeCreateInfo.display_area.left = 0; oVideoDecodeCreateInfo.display_area.right = (short)oVideoDecodeCreateInfo.ulTargetWidth; oVideoDecodeCreateInfo.display_area.top = 0; oVideoDecodeCreateInfo.display_area.bottom = (short)oVideoDecodeCreateInfo.ulTargetHeight; oVideoDecodeCreateInfo.ulNumOutputSurfaces = 2; oVideoDecodeCreateInfo.ulCreationFlags = cudaVideoCreate_PreferCUVID; oVideoDecodeCreateInfo.vidLock = m_ctxLock; oResult = cuvidCreateDecoder(&m_videoDecoder, &oVideoDecodeCreateInfo);//创建解码器 if (oResult != CUDA_SUCCESS) { fprintf(stderr, "cuvidCreateDecoder() failed, error code: %d\\n", oResult); exit(-1); } m_oVideoDecodeCreateInfo = oVideoDecodeCreateInfo; //init video parser CUVIDPARSERPARAMS oVideoParserParameters; memset(&oVideoParserParameters, 0, sizeof(CUVIDPARSERPARAMS)); oVideoParserParameters.CodecType = oVideoDecodeCreateInfo.CodecType; oVideoParserParameters.ulMaxNumDecodeSurfaces = oVideoDecodeCreateInfo.ulNumDecodeSurfaces; oVideoParserParameters.ulMaxDisplayDelay = 1; oVideoParserParameters.pUserData = this; oVideoParserParameters.pfnSequenceCallback = HandleVideoSequence;//数据源拉取出来的回调 oVideoParserParameters.pfnDecodePicture = HandlePictureDecode; oVideoParserParameters.pfnDisplayPicture = HandlePictureDisplay;//解码后的数据回调 oResult = cuvidCreateVideoParser(&m_videoParser, &oVideoParserParameters);//创建解析器 目的是协助解析包，可以回调得到每帧的格式，回调得到预解码的数据，回调得到最后图片数据 if (oResult != CUDA_SUCCESS) { fprintf(stderr, "cuvidCreateVideoParser failed, error code: %d\\n", oResult); exit(-1); } }
源对象加载数据后会回调，里面有CUVIDSOURCEDATAPACKET格式的数据包，数据包会给解析器，解析器回传数据给解码器，解码器把数据回传给队列，发往主线程
static int CUDAAPI HandleVideoData(void* pUserData, CUVIDSOURCEDATAPACKET* pPacket) { assert(pUserData); CudaDecoder* pDecoder = (CudaDecoder*)pUserData; CUresult oResult = cuvidParseVideoData(pDecoder->m_videoParser, pPacket); if(oResult != CUDA_SUCCESS) { printf("error!\\n"); } return 1; } static int CUDAAPI HandleVideoSequence(void* pUserData, CUVIDEOFORMAT* pFormat) { assert(pUserData); CudaDecoder* pDecoder = (CudaDecoder*)pUserData; if ((pFormat->codec != pDecoder->m_oVideoDecodeCreateInfo.CodecType) || // codec-type (pFormat->coded_width != pDecoder->m_oVideoDecodeCreateInfo.ulWidth) || (pFormat->coded_height != pDecoder->m_oVideoDecodeCreateInfo.ulHeight) || (pFormat->chroma_format != pDecoder->m_oVideoDecodeCreateInfo.ChromaFormat)) { fprintf(stderr, "NvTranscoder doesn\'t deal with dynamic video format changing\\n"); return 0; } return 1; } static int CUDAAPI HandlePictureDecode(void* pUserData, CUVIDPICPARAMS* pPicParams) { assert(pUserData); CudaDecoder* pDecoder = (CudaDecoder*)pUserData; pDecoder->m_pFrameQueue->waitUntilFrameAvailable(pPicParams->CurrPicIdx); assert(CUDA_SUCCESS == cuvidDecodePicture(pDecoder->m_videoDecoder, pPicParams)); return 1; } static int CUDAAPI HandlePictureDisplay(void* pUserData, CUVIDPARSERDISPINFO* pPicParams) { assert(pUserData); CudaDecoder* pDecoder = (CudaDecoder*)pUserData; pDecoder->m_pFrameQueue->enqueue(pPicParams); pDecoder->m_decodedFrames++; return 1; }
看了以上流程，估计有一个大概的流程在心里了，
必要的gpu初始化------》初始化解码器，解析器，源解释器------》运行-----》处理输出数据
2.自己解码器的调用对接
现在轮到我们自己的需求，我的需求就是实现那个ffmpeg的解码GPU化，先看看官方文档
首先用这个必须有一些要求
NVIDIA Video Codec SDK 8.0 System Requirements * NVIDIA Kepler/Maxwell/Pascal GPU with hardware video accelerators - Refer to the NVIDIA Video SDK developer zone web page (https://developer.nvidia.com/nvidia-video-codec-sdk) for GPUs which support encoding and decoding acceleration. * Windows: Driver version 378.66 or higher * Linux: Driver version 378.13 or higher * CUDA 7.5 Toolkit (optional) [Windows Configuration Requirements] - DirectX SDK is needed. You can download the latest SDK from Microsoft\'s DirectX website - The CUDA 7.5 Toolkit is optional to install (see below on how to get it) - CUDA toolkit is used for building CUDA kernels that can interop with NVENC. The following environment variables need to be set to build the sample applications included with the SDK * For Windows - DXSDK_DIR: pointing to the DirectX SDK root directory [Linux Configuration Requirements] * For Linux - X11 and OpenGL, GLUT, GLEW libraries for video playback and display - The CUDA 7.5 Toolkit is optional to install (see below on how to get it) - CUDA toolkit is used for building CUDA kernels that can interop with NVENC.
我看下了我的linux基本满足条件
验证可行性
再看Using_FFmpeg_with_NVIDIA_GPU_Hardware_Acceleration.pdf里面的提示可以直接编译ffmpeg，使用它自带的cuda解码器来测试解码，不过也是有要求的
对号入座，我用的是8.0，所以使用ffmpeg3.4
编译
./configure --enable-shared -–enable-cuda --enable-cuvid --enable-nvenc --enable-nonfree -–enable-libnpp --extra-cflags=-I/usr/local/cuda/include --extra-ldflags=-L/usr/local/cuda/lib64 --prefix=/home/user/mjl/algo/ffmpeg/build make -j 4(建议用四线程，八线程可能出现找不到的错误)
验证
ffmpeg -y -hwaccel cuvid -c:v h264_cuvid -vsync 0 -i input.mp4 -vf scale_npp=1920:1072 -vcodec h264_nvenc output0.264 -vf scale_npp=1280:720 -vcodec h264_nvenc output1.264 报错：Unknown decoder \'h264_cuvid\'
注意一定要在超级管理员权限下面运行，应为只有超级管理员才能访问gpu
正常输出了文件，证明可行
关于它自带的解码器，我一直不是很了解，ffmpeg在初始化的时候统一注册了各种编解码器，但是如何在上层简单的调用，一直不明白，这点可以大家交流
我这里是自己直接对接，也便于控制数据
avformat_network_init(); av_register_all();//1.注册各种编码解码模块，如果3.3及以上版本，里面包含GPU解码模块 std::string tempfile = “xxxx”;//视频流地址 avformat_find_stream_info(format_context_, nullptr）//2.拉取一小段数据流分析，便于得到数据的基本格式 if (AVMEDIA_TYPE_VIDEO == enc->codec_type && video_stream_index_ < 0)//3.筛选出视频流 codec_ = avcodec_find_decoder(enc->codec_id);//4.找到对应的解码器 codec_context_ = avcodec_alloc_context3(codec_);//5.创建解码器对应的结构体 av_read_frame(format_context_, &packet_); //6.读取数据包 avcodec_send_packet(codec_context_, &packet_) //7.发出解码 avcodec_receive_frame(codec_context_, yuv_frame_) //8.接收解码 sws_scale(y2r_sws_context_, yuv_frame_->data, yuv_frame_->linesize, 0, codec_context_->height, rgb_data_, rgb_line_size_) //9.数据格式转换
在第一节中说过，4，7，8，9步骤需要修改
数据还是由ffmpeg拉取，也就是说不需要cuda自带的源获取器，只需要对接解码器和解析器（如果拉取数据也可以用GPU会更好）
而在ffmpeg中出来的数据格式是AVPacket，而cuda解码器需要的格式是CUVIDSOURCEDATAPACKET，所以涉及到格式的转换
开始的时候我在网上资料发现一个 https://www.cnblogs.com/dwdxdy/archive/2013/08/07/3244723.html 这位兄弟的格式转换部分是这样实现的
我试过，不行的，没有任何解码输出！
https://www.cnblogs.com/betterwgo/p/6613641.html 这位兄弟比较全面，但是其中的
void VideoSource::play_thread(LPVOID lpParam) { AVPacket *avpkt; avpkt = (AVPacket *)av_malloc(sizeof(AV以上是关于视频流GPU解码在ffempg的实现-GPU解码器的主要内容，如果未能解决你的问题，请参考以下文章