共计 11061 个字符，预计需要花费 28 分钟才能阅读完成。
在我之前写的一篇文章《SkeyeRTSPLive 传统视频监控互联网 + 实现利器解决方案》中提到 RTSP 转 RTMP 的转流过程，简化流程就是通过 SkeyeRTSPClient 拉 RTSP 流，获取音视频编码数据，而后再通过 SkeyeRTMPPusher 推出去，流程非常简单；而后再理论开发过程中，咱们发现其实这个过程并没有设想中那么简略；首先，RTSP 协定反对多种音视频编码格局，如音频反对 AAC,G711，G726, 等，视频反对 H264，H625，MJPEG, MPEG 等等各种格局，而 SkeyeRTMPPusher 推流只反对 H264（已扩大反对 H265）格局，这时，音频咱们能够通过 SkeyeAACEncoder 将音频转码成 AAC 格局，而视频咱们能够通过 SkeyeVideoDecoder 解码成原始数据，而后再通过 SkeyeVideoEncoder 将原始数据转码成 RTMP 推送指定的格局，本文，咱们将重点讲述 SkeyeVideoDecoder 基于 Nvidia(英伟达)独立显卡的解码流程。
SkeyeVideoDecoder 基 Nvidia 独立显卡的硬解码库 SkeyeNvDecoder
SkeyeNvDecoder 库是基于 Nvidia 独立显卡驱动的硬件解码程序，该解码程序效率十分高效且具备弱小的并行解码效能力，其解码效率比 ffmpeg 软件解码效率提到至多 5 - 6 倍，最新的 RTX 系列显卡其解码效率甚至比软解码高 10-12 倍，轻松解码多路 4K 乃至 8K 高清视频无压力，本文采纳的是截止目前（20190714）最新的显卡驱动，CUDA 版本须要 10.0 或者以上版本反对。
1. 接口申明如下：
#ifndef SKEYENVDECODERAPI_H
#define SKEYENVDECODERAPI_H
#include <string>
//++ typedefine start
#ifndef SKEYENVDECODER_HANDLE
#define SKEYENVDECODER_HANDLE void*
#endif//SKEYENVDECODER_HANDLE
typedef enum _OutputFormat //native= 默认解码器输入为 NV12 格局
{native = 0, bgrp, rgbp, bgra, rgba, bgra64, rgba64}OutputFormat;
typedef enum _SKEYENvDecoder_CodecType {
SKEYENvDecoder_Codec_MPEG1 = 0, /**< MPEG1 */
SKEYENvDecoder_Codec_MPEG2, /**< MPEG2 */
SKEYENvDecoder_Codec_MPEG4, /**< MPEG4 */
SKEYENvDecoder_Codec_VC1, /**< VC1 */
SKEYENvDecoder_Codec_H264, /**< H264 */
SKEYENvDecoder_Codec_JPEG, /**< JPEG */
SKEYENvDecoder_Codec_H264_SVC, /**< H264-SVC */
SKEYENvDecoder_Codec_H264_MVC, /**< H264-MVC */
SKEYENvDecoder_Codec_HEVC, /**< HEVC */
SKEYENvDecoder_Codec_VP8, /**< VP8 */
SKEYENvDecoder_Codec_VP9, /**< VP9 */
SKEYENvDecoder_Codec_NumCodecs, /**< Max codecs */
} SKEYENvDecoder_CodecType;
typedef enum _SKEYENvDecoder_YUVType {
// Uncompressed YUV
SKEYENvDecoder_YUV420 = (('I' << 24) | ('Y' << 16) | ('U' << 8) | ('V')), /**< Y,U,V (4:2:0) */
SKEYENvDecoder_YV12 = (('Y' << 24) | ('V' << 16) | ('1' << 8) | ('2')), /**< Y,V,U (4:2:0) */
SKEYENvDecoder_NV12 = (('N' << 24) | ('V' << 16) | ('1' << 8) | ('2')), /**< Y,UV (4:2:0) */
SKEYENvDecoder_YUYV = (('Y' << 24) | ('U' << 16) | ('Y' << 8) | ('V')), /**< YUYV/YUY2 (4:2:2) */
SKEYENvDecoder_UYVY = (('U' << 24) | ('Y' << 16) | ('V' << 8) | ('Y')) /**< UYVY (4:2:2) */
} SKEYENvDecoder_YUVType;
#ifdef __cplusplus
extern "C"
{
#endif
int SKEYENvDecoder_Initsize(std::string &erroStr);
// 除非应用低提早模式，否则请不要应用此标记 bLowLatency，然而应用此标记很难取得硬件解码器 100% 的利用率。SKEYENVDECODER_HANDLE NvDecoder_Create(NvDecoder_CodecType codec, int videoW, int videoH, bool bLowLatency, OutputFormat eOutputFormat, int& errCode, std::string &erroStr);
int NvDecoder_Decode(NVDECODER_HANDLE handle, const uint8_t *pData, int nSize, uint8_t ***pppFrame, int* pnFrameLen, int *pnFrameReturned);
void SKEYENvDecoder_Release(NVDECODER_HANDLE handle) ;
int NvDecoder_Uninitsize();
#ifdef __cplusplus
}
#endif
#endif // SKEYENVDECODERAPI_H
2. SkeyeNvDecoder 解码库调用流程
-
第一步，初始化注册解码器
留神，注册解码器函数全局只需调用一；int SKEYENvDecoder_Initsize(string &erroStr) { try {if (!isInitsized) { // 显卡只初始化一次 ck(cuInit(0)); int nGpu = 0; ck(cuDeviceGetCount(&nGpu)); for (int i = 0; i < nGpu; i++) { CUdevice cuDevice = 0; ck(cuDeviceGet(&cuDevice, i)); char szDeviceName[128]; ck(cuDeviceGetName(szDeviceName, sizeof(szDeviceName), cuDevice)); LOG(INFO) << "Find Gpu:" << szDeviceName << std::endl; CUcontext cuContext = NULL; ck(cuCtxCreate(&cuContext, CU_CTX_SCHED_BLOCKING_SYNC, cuDevice)); m_ctxV.push_back({cuContext,szDeviceName}); } isInitsized = true; m_curIndex = 0; } if (m_ctxV.empty()) {return -1;} } catch (const std::exception& ex) {erroStr = ex.what(); std::cout << ex.what(); return -2; } return 1; } - 第二步，创立解码器实例
SKEYENVDECODER_HANDLE SKEYENvDecoder_Create(NvDecoder_CodecType codec, int videoW, int videoH, bool bLowLatency, OutputFormat eOutputFormat, int& errCode, string &erroStr)
{//if (!isInitsized || !m_ctxV.size()) {
// return NULL;
//}
try {ck(cuInit(0));
int nGpu = 0;
ck(cuDeviceGetCount(&nGpu));
CUcontext cuContext = NULL;
m_curIndex++;
m_curIndex = (m_curIndex) % nGpu;
for (int i = 0; i < nGpu; i++)
{if (m_curIndex == i)
{
CUdevice cuDevice = 0;
ck(cuDeviceGet(&cuDevice, i));
char szDeviceName[128];
ck(cuDeviceGetName(szDeviceName, sizeof(szDeviceName), cuDevice));
LOG(INFO) << "Find Gpu:" << szDeviceName << std::endl;
ck(cuCtxCreate(&cuContext, CU_CTX_SCHED_BLOCKING_SYNC, cuDevice));
}
}
//std::pair<CUcontext, std::string> &v = m_ctxV.at(m_curIndex++ % m_ctxV.size());
//std::cout << "Use Contex in" << v.second << std::endl;
const char *aszChromaFormat[] = { "4:0:0", "4:2:0", "4:2:2", "4:4:4"};
cudaVideoCodec aeCodec[] = { cudaVideoCodec_JPEG, cudaVideoCodec_MPEG1, cudaVideoCodec_MPEG2, cudaVideoCodec_MPEG4, cudaVideoCodec_H264, cudaVideoCodec_HEVC,
cudaVideoCodec_HEVC, cudaVideoCodec_HEVC, cudaVideoCodec_HEVC, cudaVideoCodec_HEVC, cudaVideoCodec_HEVC, cudaVideoCodec_VC1, cudaVideoCodec_VP8,
cudaVideoCodec_VP9, cudaVideoCodec_VP9, cudaVideoCodec_VP9 };
int anBitDepthMinus8[] = { 0, 0, 0, 0, 0, 0, 2, 4, 0, 2, 4, 0, 0, 0, 2, 4};
cudaVideoChromaFormat aeChromaFormat[] = { cudaVideoChromaFormat_420, cudaVideoChromaFormat_420, cudaVideoChromaFormat_420, cudaVideoChromaFormat_420,
cudaVideoChromaFormat_420, cudaVideoChromaFormat_420, cudaVideoChromaFormat_420, cudaVideoChromaFormat_420, cudaVideoChromaFormat_444, cudaVideoChromaFormat_444,
cudaVideoChromaFormat_444, cudaVideoChromaFormat_420, cudaVideoChromaFormat_420, cudaVideoChromaFormat_420, cudaVideoChromaFormat_420, cudaVideoChromaFormat_420 };
CUVIDDECODECAPS videoDecodeCaps = {};
videoDecodeCaps.eCodecType = (cudaVideoCodec)codec;
videoDecodeCaps.eChromaFormat = cudaVideoChromaFormat_420;
videoDecodeCaps.nBitDepthMinus8 = 0;
for (int i = 0; i < sizeof(aeCodec) / sizeof(aeCodec[0]); i++)
{if (aeCodec[i] == codec)
{videoDecodeCaps.eChromaFormat = aeChromaFormat[i];
videoDecodeCaps.nBitDepthMinus8 = anBitDepthMinus8[i];
break;
}
}
errCode = cuvidGetDecoderCaps(&videoDecodeCaps);
if (CUDA_SUCCESS == errCode) { // 判断显卡是否反对 1080p 解码
LOG(INFO) << "cuvid Decoder Caps nMaxWidth" << videoDecodeCaps.nMaxWidth << "nMaxHeigth" << videoDecodeCaps.nMaxHeight << std::endl;
if (!videoDecodeCaps.bIsSupported) {
erroStr = "Codec not supported on this GPU Decoder";
errCode = -1;
}
else
{
// 判断是否反对指定格局分辨率视频解码
if (videoDecodeCaps.nMaxWidth >= videoW && videoDecodeCaps.nMaxHeight >= videoH)
{
NvDecoder* pDecoder = new NvDecoder(/*v.first*/cuContext, videoW, videoH, eOutputFormat== native?false:true,
(cudaVideoCodec)codec, NULL, bLowLatency, eOutputFormat);
pDecoder->Start();
return pDecoder;
}
else
{
erroStr = "Width and height not supported on this GPU Decoder";
errCode = -2;
}
}
}
}
catch (std::exception &e)
{erroStr = e.what();
}
return NULL;
}- 第三步，调用解码函数解码
int SKEYENvDecoder_Decode(SKEYENVDECODER_HANDLE handle, const uint8_t *pData, int nSize, uint8_t ***pppFrame, int* pnFrameLen, int *pnFrameReturned)
{if (!handle)
return -1;
NvDecoder* pDecoder = (NvDecoder*)handle;
int anSize[] = { 0, 3, 3, 4, 4, 8, 8};
//std::unique_ptr<uint8_t[]> pImage(new uint8_t[nFrameSize]);
std::vector<uint8_t *>* vecOutBuffer = pDecoder->GetFrameBufferVector();
size_t nFrameSize = pDecoder->GetOutFrameSize();
*pnFrameLen = nFrameSize;
int nFrameReturned = 0, nFrame = 0;
uint8_t **ppFrame = NULL;
bool bLowLatency = pDecoder->IsSetLowLatency();
bool bSuc = pDecoder->Decode(pData, nSize, &ppFrame, &nFrameReturned, CUVID_PKT_ENDOFPICTURE/*bLowLatency?CUVID_PKT_ENDOFPICTURE : 0*/);
if (!bSuc)
return -2;
//if (!nFrame && nFrameReturned > 0)
//LOG(INFO) << "nFrameReturned =" <<nFrameReturned;//pDecoder->GetVideoInfo();
for (int i = 0; i < nFrameReturned; i++)
{if (native != pDecoder->GetSetOutputFormat())
{if (i >= (*vecOutBuffer).size())
{(*vecOutBuffer).push_back(new uint8_t[nFrameSize]);
}
}
if (pDecoder->GetBitDepth() == 8)
{switch (pDecoder->GetSetOutputFormat())
{
case native:
//GetImage((CUdeviceptr)ppFrame[i], (*vecOutBuffer)[i], pDecoder->GetWidth(), pDecoder->GetHeight() + (pDecoder->GetChromaHeight() * pDecoder->GetNumChromaPlanes()));
break;
case bgrp:
if (pDecoder->GetOutputFormat() == cudaVideoSurfaceFormat_YUV444)
YUV444ToColorPlanar<BGRA32>((uint8_t *)ppFrame[i], pDecoder->GetWidth(), (uint8_t*)pDecoder->GetDeviceImagePtr(), pDecoder->GetWidth(), pDecoder->GetWidth(), pDecoder->GetHeight());
else
Nv12ToColorPlanar<BGRA32>((uint8_t *)ppFrame[i], pDecoder->GetWidth(), (uint8_t*)pDecoder->GetDeviceImagePtr(), pDecoder->GetWidth(), pDecoder->GetWidth(), pDecoder->GetHeight());
GetImage(pDecoder->GetDeviceImagePtr(), (*vecOutBuffer)[i], pDecoder->GetWidth(), 3 * pDecoder->GetHeight());
break;
case rgbp:
if (pDecoder->GetOutputFormat() == cudaVideoSurfaceFormat_YUV444)
YUV444ToColorPlanar<RGBA32>((uint8_t *)ppFrame[i], pDecoder->GetWidth(), (uint8_t*)pDecoder->GetDeviceImagePtr(), pDecoder->GetWidth(), pDecoder->GetWidth(), pDecoder->GetHeight());
else
Nv12ToColorPlanar<RGBA32>((uint8_t *)ppFrame[i], pDecoder->GetWidth(), (uint8_t*)pDecoder->GetDeviceImagePtr(), pDecoder->GetWidth(), pDecoder->GetWidth(), pDecoder->GetHeight());
GetImage(pDecoder->GetDeviceImagePtr(), (*vecOutBuffer)[i], pDecoder->GetWidth(), 3 * pDecoder->GetHeight());
break;
case bgra:
if (pDecoder->GetOutputFormat() == cudaVideoSurfaceFormat_YUV444)
YUV444ToColor32<BGRA32>((uint8_t *)ppFrame[i], pDecoder->GetWidth(), (uint8_t*)pDecoder->GetDeviceImagePtr(), 4 * pDecoder->GetWidth(), pDecoder->GetWidth(), pDecoder->GetHeight());
else
Nv12ToColor32<BGRA32>((uint8_t *)ppFrame[i], pDecoder->GetWidth(), (uint8_t*)pDecoder->GetDeviceImagePtr(), 4 * pDecoder->GetWidth(), pDecoder->GetWidth(), pDecoder->GetHeight());
GetImage(pDecoder->GetDeviceImagePtr(), (*vecOutBuffer)[i], 4 * pDecoder->GetWidth(), pDecoder->GetHeight());
break;
case rgba:
if (pDecoder->GetOutputFormat() == cudaVideoSurfaceFormat_YUV444)
YUV444ToColor32<RGBA32>((uint8_t *)ppFrame[i], pDecoder->GetWidth(), (uint8_t*)pDecoder->GetDeviceImagePtr(), 4 * pDecoder->GetWidth(), pDecoder->GetWidth(), pDecoder->GetHeight());
else
Nv12ToColor32<RGBA32>((uint8_t *)ppFrame[i], pDecoder->GetWidth(), (uint8_t*)pDecoder->GetDeviceImagePtr(), 4 * pDecoder->GetWidth(), pDecoder->GetWidth(), pDecoder->GetHeight());
GetImage(pDecoder->GetDeviceImagePtr(), (*vecOutBuffer)[i], 4 * pDecoder->GetWidth(), pDecoder->GetHeight());
break;
case bgra64:
if (pDecoder->GetOutputFormat() == cudaVideoSurfaceFormat_YUV444)
YUV444ToColor64<BGRA64>((uint8_t *)ppFrame[i], pDecoder->GetWidth(), (uint8_t*)pDecoder->GetDeviceImagePtr(), 8 * pDecoder->GetWidth(), pDecoder->GetWidth(), pDecoder->GetHeight());
else
Nv12ToColor64<BGRA64>((uint8_t *)ppFrame[i], pDecoder->GetWidth(), (uint8_t*)pDecoder->GetDeviceImagePtr(), 8 * pDecoder->GetWidth(), pDecoder->GetWidth(), pDecoder->GetHeight());
GetImage(pDecoder->GetDeviceImagePtr(), (*vecOutBuffer)[i], 8 * pDecoder->GetWidth(), pDecoder->GetHeight());
break;
case rgba64:
if (pDecoder->GetOutputFormat() == cudaVideoSurfaceFormat_YUV444)
YUV444ToColor64<RGBA64>((uint8_t *)ppFrame[i], pDecoder->GetWidth(), (uint8_t*)pDecoder->GetDeviceImagePtr(), 8 * pDecoder->GetWidth(), pDecoder->GetWidth(), pDecoder->GetHeight());
else
Nv12ToColor64<RGBA64>((uint8_t *)ppFrame[i], pDecoder->GetWidth(), (uint8_t*)pDecoder->GetDeviceImagePtr(), 8 * pDecoder->GetWidth(), pDecoder->GetWidth(), pDecoder->GetHeight());
GetImage(pDecoder->GetDeviceImagePtr(), (*vecOutBuffer)[i], 8 * pDecoder->GetWidth(), pDecoder->GetHeight());
break;
}
}
}
nFrame += nFrameReturned;
if (nFrameReturned > 0)
{if (pnFrameReturned)
*pnFrameReturned = nFrameReturned;
if (native != pDecoder->GetSetOutputFormat())
{if (pppFrame && (*vecOutBuffer).size() > 0)
*pppFrame = &(*vecOutBuffer)[0];
}
else
{if (pppFrame && ppFrame)
*pppFrame = ppFrame;
}
}
}- 第四步，进行解码，销毁解码器
void SKEYENvDecoder_Release(SKEYENVDECODER_HANDLE handle)
{if (!handle)
return;
NvDecoder* pDecoder = (NvDecoder*)handle;
pDecoder->Stop();
delete pDecoder;
m_curIndex--;
if (m_curIndex < 0)
m_curIndex = 0;
}- 第五步，登记解码器，开释资源
int SKEYENvDecoder_Uninitsize()
{
isInitsized = false;
for (int nI = 0; nI < m_ctxV.size(); nI++)
{cuCtxDestroy(m_ctxV[nI].first);
}
m_ctxV.clear();
m_curIndex = 0;
return 1;
}
自此，SKEYENvDecoder 的封装就实现了，咱们能够通过其接口调用 Nvidia 的显卡进行硬件解码测试，以下为实在利用成果，硬解 12 路效果图 cpu I5 占比 11，730 显卡点 75-80，如下图所示：
有任何技术问题，欢送大家和我技术交换：
295222688@qq.com
大家也能够退出 SkeyePlayer 流媒体播放器 QQ 群进行探讨：
102644504
正文完
