网站开发项目报告建筑行业网站模板

1、FFmpeg支持多种硬件加速类型，用于编解码视频，以提升性能和效率。以下是FFmpeg支持的主要硬件加速类型：

NVIDIA NVENC/NVDEC：利用NVIDIA显卡进行视频编码（NVENC）和解码（NVDEC）。
QSV：利用Intel处理器中的集成图形进行视频加速。
AMD VCE  VDA：利用AMD显卡进行视频编码和解码。
VAAPI：适用于Intel和AMD硬件，通过通用的API接口进行硬件加速。
VDPAU ：主要用于NVIDIA显卡的硬件解码加速。
DXVA2 ：适用于Windows平台，利用DirectX进行视频加速。
OpenMAX IL ：用于移动设备和嵌入式系统的视频加速。
Vulkan：一种跨平台的图形和计算API，也可以用于视频加速

int CH264CodecConvert::OpenH264Encoder()
{const AVCodec* codec = avcodec_find_encoder(AV_CODEC_ID_H264);//codec = avcodec_find_encoder_by_name("h264_nvenc");if (!codec){fileLogger->error("查找H264编码器失败");return -1;}m_outAvCodecContex = avcodec_alloc_context3(codec);if (!m_outAvCodecContex){fileLogger->error("H264编码器分配上下文失败");return -2;}
// 	m_outAvCodecContex->thread_count = 4;
// 	m_outAvCodecContex->thread_type = FF_THREAD_FRAME;m_outAvCodecContex->width = 1920;m_outAvCodecContex->height = 1080;m_outAvCodecContex->time_base = { 1, 25 };//多少帧一个I帧//m_outAvCodecContex->gop_size = 25;//去掉B帧//m_outAvCodecContex->max_b_frames = 0;//m_outAvCodecContex->pix_fmt = AV_PIX_FMT_YUV420P;//AV_PIX_FMT_CUDA;//从GPU出来的帧没法转成yuv420，因为网上也有说法是GPU出来只出NV12//解码 > cuda > resize > nv12 > 编码 > yuv420//修改编码encctx->pix_fmt = AV_PIX_FMT_NV12，//顺便encctx->sw_pix_fmt = AV_PIX_FMT_YUV420P(个人认为这个是转换后的格式)av_opt_set(m_outAvCodecContex->priv_data, "preset", "ultrafast", 0);
//av_opt_set(m_outAvCodecContex->priv_data, "tune", "fastdecode", 0);
//av_opt_set(m_outAvCodecContex->priv_data, "profile", "high", 0);m_outAvCodecContex->pix_fmt = AV_PIX_FMT_NV12;m_outAvCodecContex->sw_pix_fmt = AV_PIX_FMT_YUV420P;if (avcodec_open2(m_outAvCodecContex, codec, NULL) < 0){fileLogger->error("打开H264编码器失败");return -3;}m_bIsOpenEncoder = true;return 0;
}enum AVPixelFormat CH264CodecConvert::get_hw_format(AVCodecContext *ctx, const enum AVPixelFormat *pix_fmts) {const enum AVPixelFormat *p;for (p = pix_fmts; *p != -1; p++) {if (*p == ePixFmt_)return *p;}fprintf(stderr, "Failed to get HW surface format.\n");return AV_PIX_FMT_NONE;
}int CH264CodecConvert::hw_decoder_init(AVCodecContext *ctx, const enum AVHWDeviceType type) {int err = 0;if ((err = av_hwdevice_ctx_create(&pDeviceCtx, type,nullptr, nullptr, 0)) < 0) {fprintf(stderr, "Failed to create specified HW device.\n");return err;}ctx->hw_device_ctx = av_buffer_ref(pDeviceCtx);return err;
}int CH264CodecConvert::InitHardDecode(const std::string& HWType)
{pCodec_ = avcodec_find_decoder(AV_CODEC_ID_HEVC);if (!pCodec_) {std::cout << "avcodec_find_decoder Failed" << std::endl;return -1;}enum AVHWDeviceType type;type = av_hwdevice_find_type_by_name(HWType.c_str());if (type == AV_HWDEVICE_TYPE_NONE){std::cout << "UnKnown HW Device Type" << std::endl;while ((type = av_hwdevice_iterate_types(type)) != AV_HWDEVICE_TYPE_NONE){std::cout << type << std::endl;}return -1;}for (int i = 0; ; i++){const AVCodecHWConfig *config = avcodec_get_hw_config(pCodec_, i);if (!config){std::cout << "avcodec_get_hw_config Failed" << i << std::endl;return -1;}if (config->methods & AV_CODEC_HW_CONFIG_METHOD_HW_DEVICE_CTX &&config->device_type == type){ePixFmt_ = config->pix_fmt;break;}}m_inAvCodecContex = avcodec_alloc_context3(pCodec_);if (!m_inAvCodecContex) {std::cout << "avcodec_alloc_context3 Failed" << std::endl;return -1;}m_inAvCodecContex->thread_count = 4;m_inAvCodecContex->thread_type = FF_THREAD_FRAME;m_inAvCodecContex->get_format = get_hw_format;if (hw_decoder_init(m_inAvCodecContex, type) < 0) {return -1;}if (avcodec_open2(m_inAvCodecContex, pCodec_, nullptr) < 0){std::cout << "avcodec_open2 Failed" << std::endl;return -1;}bHWDecode_ = true;return 0;
}void CH264CodecConvert::TransferCodec(const std::uint8_t* pszData, std::int32_t nDataLen)
{if (!m_bIsOpenDecoder){//cuda dxva2 d3d11va d3d12vaInitHardDecode("d3d12va");m_bIsOpenDecoder = true;}AVFrame* frame = NULL;if (!(frame = av_frame_alloc()))return;AVPacket inpkt;av_init_packet(&inpkt);inpkt.data = (std::uint8_t*)pszData;inpkt.size = nDataLen;// 硬解码AVFrame* tmpFrame = nullptr, *swFrame = nullptr;int nRet = avcodec_send_packet(m_inAvCodecContex, &inpkt); // 将AVPacket发送至解码器中if (!(tmpFrame = av_frame_alloc()) || !(swFrame = av_frame_alloc())){av_frame_free(&frame);return;}while (avcodec_receive_frame(m_inAvCodecContex, tmpFrame) >= 0){if (!m_bIsOpenEncoder)OpenH264Encoder();if (!m_bIsOpenEncoder)continue;// 判断解码帧格式if (tmpFrame->format == ePixFmt_){/* 将GPU中的数据移交到CPU中 */if (av_hwframe_transfer_data(swFrame, tmpFrame, 0) < 0){std::cout << "Error transferring the data to system memory" << std::endl;av_frame_free(&tmpFrame);av_frame_free(&swFrame);av_frame_free(&frame);return;}frame = swFrame;}else{frame = tmpFrame;}AVPacket outpkt;av_init_packet(&outpkt);frame->pts = m_nPTS++;avcodec_send_frame(m_outAvCodecContex, frame);while (avcodec_receive_packet(m_outAvCodecContex, &outpkt) == 0){std::shared_ptr<std::string> packet = std::make_shared<std::string>();packet->append((char*)outpkt.data, outpkt.size);{std::unique_lock<std::mutex> lock(m_mutexQueuePacket);m_queuePacket.push(packet);}av_packet_unref(&outpkt);}}av_packet_unref(&inpkt);av_frame_free(&tmpFrame);av_frame_free(&swFrame);
}

问题记录:

1.

根据文章https://blog.csdn.net/qq_23282479/article/details/118993650

改用了GPU硬解码，出现了这个问题。软解是没问题的

原本是 解码>cuda>yuv420>编码>yuv420

从GPU出来的帧没法转成yuv420，因为网上也有说法是GPU出来只出NV12

解码>cuda>nv12>编码>yuv420

	m_outAvCodecContex->pix_fmt = AV_PIX_FMT_NV12;m_outAvCodecContex->sw_pix_fmt = AV_PIX_FMT_YUV420P;

这样就正常显示了

2.视频出现闪频

m_inAvCodecContex->thread_count = 4;
m_inAvCodecContex->thread_type = FF_THREAD_FRAME;

开启了多线程解码后解决了这个问题