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La conservation du net art au musée. Les stratégies à l’œuvre
26 mai 2011
Mis à jour : Juillet 2013
Langue : français
Type : Texte
Autres articles (112)
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Dans le thème par défaut spipeo de MédiaSPIP, les actualités sont affichées en bas de la page principale sous les éditoriaux.
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Sur d’autres sites (5999)
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How to incorporate screencasting into a rails project
13 mars 2015, par ruby_newbieI am working on a personal project and I want to incorporate screencasting with it. I want the screencast to be able to record the entire screen not just the page in a web browser so I think JS is out as a solution. I have searched and found a few clues but nothing concrete as to how i can make it happen short of learning Java. Here is what I have tried :
Rmov :https://rubygems.org/gems/rmov I cant get bundler to run bundle with this gem but this has the exact functionality I want. I think it has to do with quicktime being 32 bit but I am not sure. I opened an issue on Github in hopes to resolve it.
I saw this post : http://devblog.avdi.org/2013/01/21/my-screencasting-process/ which links to this script : https://github.com/avdi/Xcast/blob/master/Xcast
but I am failing on the require ’highline/system_extensions’ line (require cannot load such file).I found this : http://rvideo.rubyforge.org/ but I am still confused as to how to implement it. FFMPEG seems promising though and like it may be the tool I am looking for.
Does anyone know of a tool that would allow me to do this or a good tutorial that explains this process in detail ? Any help is appreciated and let me know if you need any more info that I can provide.
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How HSBC and ING are transforming banking with AI
9 novembre 2024, par Daniel Crough — Banking and Financial Services, Featured Banking ContentWe recently partnered with FinTech Futures to produce an exciting webinar discussing how analytics leaders from two global banks are using AI to protect customers, streamline operations, and support environmental goals.
Watch the on-demand webinar : Advancing analytics maturity.
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</script>Meet the expert panel
Roshini Johri heads ESG Analytics at HSBC, where she leads AI and remote sensing applications supporting the bank’s net zero goals. Her expertise spans climate tech and financial services, with a focus on scalable analytics solutions.
Marco Li Mandri leads Advanced Analytics Strategy at ING, where he focuses on delivering high-impact solutions and strengthening analytics foundations. His background combines analytics, KYC operations, and AI strategy.
Carmen Soini Tourres works as a Web Analyst Consultant at Matomo, helping financial organisations optimise their digital presence whilst maintaining privacy compliance.Key findings from the webinar
The discussion highlighted four essential elements for advancing analytics capabilities :
1. Strong data foundations matter most
“It doesn’t matter how good the AI model is. It is garbage in, garbage out,”
Johri explained. Banks need robust data governance that works across different regulatory environments.
2. Transform rather than tweak
Li Mandri emphasised the need to reconsider entire processes :
“We try to look at the banking domain and processes and try to re-imagine how they should be done with AI.”
3. Bridge technical and business understanding
Both leaders stressed the value of analytics translators who understand both technology and business needs.
“We’re investing in this layer we call product leads,”
Li Mandri explained. These roles combine technical knowledge with business acumen – a rare but vital skill set.
4. Consider production costs early
Moving from proof-of-concept to production requires careful planning. As Johri noted :
“The scale of doing things in production is quite massive and often doesn’t get accounted for in the cost.”
This includes :
- Ongoing monitoring requirements
- Maintenance needs
- Regulatory compliance checks
- Regular model updates
Real-world applications
ING’s approach demonstrates how banks can transform their operations through thoughtful AI implementation. Li Mandri shared several areas where the bank has successfully deployed analytics solutions, each benefiting both the bank and its customers.
Customer experience enhancement
The bank’s implementation of AI-powered instant loan processing shows how analytics can transform traditional banking.
“We know AI can make loans instant for the customer, that’s great. Clicking one button and adding a loan, that really changes things,”
Li Mandri explained. This goes beyond automation – it represents a fundamental shift in how banks serve their customers.
The system analyses customer data to make rapid lending decisions while maintaining strong risk assessment standards. For customers, this means no more lengthy waiting periods or complex applications. For the bank, it means more efficient resource use and better risk management.
The bank also uses AI to personalise customer communications.
“We’re using that to make certain campaigns more personalised, having a certain tone of voice,”
noted Li Mandri. This particularly resonates with younger customers who expect relevant, personalised interactions from their bank.
Operational efficiency transformation
ING’s approach to Know Your Customer (KYC) processes shows how AI can transform resource-heavy operations.
“KYC is a big area of cost for the bank. So we see massive value there, a lot of scale,”
Li Mandri explained. The bank developed an AI-powered system that :
- Automates document verification
- Flags potential compliance issues for human review
- Maintains consistent standards across jurisdictions
- Reduces processing time while improving accuracy
This implementation required careful consideration of regulations across different markets. The bank developed monitoring systems to ensure their AI models maintain high accuracy while meeting compliance standards.
In the back office, ING uses AI to extract and process data from various documents, significantly reducing manual work. This automation lets staff focus on complex tasks requiring human judgment.
Sustainable finance initiatives
ING’s commitment to sustainable banking has driven innovative uses of AI in environmental assessment.
“We have this ambition to be a sustainable bank. If you want to be a sustainable finance customer, that requires a lot of work to understand who the company is, always comparing against its peers.”
The bank developed AI models that :
- Analyse company sustainability metrics
- Compare environmental performance against industry benchmarks
- Assess transition plans for high-emission industries
- Monitor ongoing compliance with sustainability commitments
This system helps staff evaluate the environmental impact of potential deals quickly and accurately.
“We are using AI there to help our frontline process customers to see how green that deal might be and then use that as a decision point,”
Li Mandri noted.
HSBC’s innovative approach
Under Johri’s leadership, HSBC has developed several groundbreaking uses of AI and analytics, particularly in environmental monitoring and operational efficiency. Their work shows how banks can use advanced technology to address complex global challenges while meeting regulatory requirements.
Environmental monitoring through advanced technology
HSBC uses computer vision and satellite imagery analysis to measure environmental impact with new precision.
“This is another big research area where we look at satellite images and we do what is called remote sensing, which is the study of a remote area,”
Johri explained.
The system provides several key capabilities :
- Analysis of forest coverage and deforestation rates
- Assessment of biodiversity impact in specific regions
- Monitoring of environmental changes over time
- Measurement of environmental risk in lending portfolios
“We can look at distant images of forest areas and understand how much percentage deforestation is being caused in that area, and we can then measure our biodiversity impact more accurately,”
Johri noted. This technology enables HSBC to :
- Make informed lending decisions
- Monitor environmental commitments of borrowers
- Support sustainability-linked lending programmes
- Provide accurate environmental impact reporting
Transforming document analysis
HSBC is tackling one of banking’s most time-consuming challenges : processing vast amounts of documentation.
“Can we reduce the onus of human having to go and read 200 pages of sustainability reports each time to extract answers ?”
Johri asked. Their solution combines several AI technologies to make this process more efficient while maintaining accuracy.
The bank’s approach includes :
- Natural language processing to understand complex documents
- Machine learning models to extract relevant information
- Validation systems to ensure accuracy
- Integration with existing compliance frameworks
“We’re exploring solutions to improve our reporting, but we need to do it in a safe, robust and transparent way.”
This careful balance between efficiency and accuracy exemplifies HSBC’s approach to AI.
Building future-ready analytics capabilities
Both banks emphasise that successful analytics requires a comprehensive, long-term approach. Their experiences highlight several critical considerations for financial institutions looking to advance their analytics capabilities.
Developing clear governance frameworks
“Understanding your AI risk appetite is crucial because banking is a highly regulated environment,”
Johri emphasised. Banks need to establish governance structures that :
- Define acceptable uses for AI
- Establish monitoring and control mechanisms
- Ensure compliance with evolving regulations
- Maintain transparency in AI decision-making
Creating solutions that scale
Li Mandri stressed the importance of building systems that grow with the organisation :
“When you try to prototype a model, you have to take care about the data safety, ethical consideration, you have to identify a way to monitor that model. You need model standard governance.”
Successful scaling requires :
- Standard approaches to model development
- Clear evaluation frameworks
- Simple processes for model updates
- Strong monitoring systems
- Regular performance reviews
Investing in people and skills
Both leaders highlighted how important skilled people are to analytics success.
“Having a good hiring strategy as well as creating that data literacy is really important,”
Johri noted. Banks need to :
- Develop comprehensive training programmes
- Create clear career paths for analytics professionals
- Foster collaboration between technical and business teams
- Build internal expertise in emerging technologies
Planning for the future
Looking ahead, both banks are preparing for increased regulation and growing demands for transparency. Key focus areas include :
- Adapting to new privacy regulations
- Making AI decisions more explainable
- Improving data quality and governance
- Strengthening cybersecurity measures
Practical steps for financial institutions
The experiences shared by HSBC and ING provide valuable insights for financial institutions at any stage of their analytics journey. Their successes and challenges outline a clear path forward.
Key steps for success
Financial institutions looking to enhance their analytics capabilities should :
- Start with strong foundations
- Invest in clear data governance frameworks
- Set data quality standards
- Build thorough documentation processes
- Create transparent data tracking
- Think strategically about AI implementation
- Focus on transformative rather than small changes
- Consider the full costs of AI projects
- Build solutions that can grow
- Balance innovation with risk management
- Invest in people and processes
- Develop internal analytics expertise
- Create clear paths for career growth
- Foster collaboration between technical and business teams
- Build a culture of data literacy
- Plan for scale
- Establish monitoring systems
- Create governance frameworks
- Develop standard approaches to model development
- Stay flexible for future regulatory changes
Learn more
Want to hear more insights from these industry leaders ? Watch the complete webinar recording on demand. You’ll learn :
- Detailed technical insights from both banks
- Extended Q&A with the speakers
- Additional case studies and examples
- Practical implementation advice
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.
Watch the on-demand webinar : Advancing analytics maturity.
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Getting and decoding video by RTP H264
29 novembre 2023, par AlekseiKraevParsing RTP H264.
WINAPI C. A queue from C++ has been applied, I repent.


RTP is generated using FFMPEG with the following command :
ffmpeg.exe -f gdigrab -framerate 25 -i desktop -s 853x480 -b:v 120000 -c:v libx264 -f rtp rtp ://127.0.0.1:8080


Parsing the incoming RTP/h264 stream and converting it to an RGB matrix.


video_H264_decode.h


#pragma once
#ifndef _VIDEO_H264_DECODE_SEND_H // Блокируем повторное включение этого модуля
#define _VIDEO_H264_DECODE_SEND_H
//******************************************************************************
// Section include
//******************************************************************************
#include "main.h"
#include 
//******************************************************************************
// Constants
//******************************************************************************

//******************************************************************************
// Type
//******************************************************************************
typedef struct {
 unsigned char* data;
 int size;
}RTPData_DType;

typedef struct 
{
 union
 {
 struct
 {
 char V:2; //Версия
 char P:1; //заполнение
 char X:1; //расширение
 char CC:4; //количество CSRC

 char M:1; //маркер (флаг последнего пакета AU),
 char PT:7; //полезная нагрузка (тип данных носителя полезной нагрузки RTP, H264 = 96)

 short sequence_number; //Порядковый номер: порядковый номер пакета RTP, увеличенный на 1.
 int time_stamp; //временная метка выборки медиа. 
 int SSRC; //Пакет данных имеет одинаковое происхождение.
 };
 unsigned char data[12];
 };
}RTPHeader_DType;
//******************************************************************************
// Global var
//******************************************************************************

//******************************************************************************
// Local function prototype
//******************************************************************************
UCHAR rtp_H264_recive_init(void);
UCHAR RTPStop(void);
//******************************************************************************
// Macros
//******************************************************************************
#define BYTE2_SWAP(X) ((((short)(X) & 0xff00) >> 8) |(((short)(X) & 0x00ff) << 8))
#endif
//******************************************************************************
// ENF OF FILE
//******************************************************************************


video_H264_decode.c


//******************************************************************************
//include
//******************************************************************************
#include "main.h"
/*#include "video_H264_decode.h"
#include 
#include 
#include <chrono>
#include 

#pragma comment(lib, "ws2_32.lib")
#include */
#include <iostream>
#include <queue>

extern "C" {
#include "libavformat/avformat.h"
#include "libavfilter/avfilter.h"
#include "libavdevice/avdevice.h"
#include "libswscale/swscale.h"
#include "libswresample/swresample.h"
#include "libpostproc/postprocess.h"
#include "libavcodec/avcodec.h"
}

#pragma comment(lib,"avcodec.lib")
#pragma comment(lib,"avdevice.lib")
#pragma comment(lib,"avfilter.lib")
#pragma comment(lib,"avformat.lib")
#pragma comment(lib,"avutil.lib")
#pragma comment(lib,"postproc.lib")
#pragma comment(lib,"swresample.lib")
#pragma comment(lib,"swscale.lib")

#pragma warning(disable: 4996)
//******************************************************************************
// Section for determining the variables used in the module
//******************************************************************************
//------------------------------------------------------------------------------
// Global
//------------------------------------------------------------------------------

//------------------------------------------------------------------------------
// Local
//------------------------------------------------------------------------------
const int inteval = 0x01000000;
BOOL FlagRTPActive = TRUE;

HANDLE hMutexRTPRecive;
HANDLE hSemaphoreRTP;
HANDLE hTreadRTPRecive;
HANDLE hTreadRTPDecode;


SOCKET RTPSocket; //socket UDP RTP
RTPData_DType packet;
RTPData_DType FU_buffer = { 0 };

std::queue q;
std::set<int> seq;

AVFormatContext* pAVFormatContext;
AVCodecContext* pAVCodecContext;
const AVCodec* pAVCodec;
AVFrame* pAVFrame;
AVFrame* AVFrameRGG;
SwsContext* pSwsContext;
AVPacket *pAVPacket;
AVCodecParserContext* pAVCodecParserContext;

UINT port;
//******************************************************************************
// Section of prototypes of local functions
//******************************************************************************
DWORD WINAPI rtp_H264_recive_Procedure(CONST LPVOID lpParam);
DWORD WINAPI rtp_decode_Procedure(CONST LPVOID lpParam);
char RTPSocketInit(void);
void RTPPacketParser(void);
char RTPSocketRecive(void);
void Decode_NaluToAVFrameRGG();
//******************************************************************************
// Section of the description of functions
//******************************************************************************
UCHAR rtp_H264_recive_init(void)
{
 hSemaphoreRTP = CreateSemaphore(
 NULL, // default security attributes
 0, // initial count
 1, // maximum count
 NULL); // unnamed semaphore

 hMutexRTPRecive = CreateMutex(
 NULL, // default security attributes
 FALSE, // initially not owned
 NULL); // unnamed mutex

 hTreadRTPRecive = CreateThread(NULL, NULL, rtp_H264_recive_Procedure, NULL, NULL, NULL);
 hTreadRTPDecode = CreateThread(NULL, NULL, rtp_decode_Procedure, NULL, NULL, NULL);

 return 0;
}
//------------------------------------------------------------------------------
UCHAR RTPStop(void)
{
 FlagRTPActive = FALSE;

 if (hSemaphoreRTP) CloseHandle(hSemaphoreRTP);
 if (hMutexRTPRecive) CloseHandle(hMutexRTPRecive);
 if (hTreadRTPRecive) CloseHandle(hTreadRTPRecive);

 closesocket(RTPSocket); 

 return 0;
}
//------------------------------------------------------------------------------
DWORD WINAPI rtp_H264_recive_Procedure(CONST LPVOID lpParam)
{
 while (RTPSocketInit() == 0)
 Sleep(2000);
 
 while (1)
 {
 RTPSocketRecive();
 RTPPacketParser();
 ReleaseSemaphore(hSemaphoreRTP, 1, NULL);
 }
}
//------------------------------------------------------------------------------
DWORD WINAPI rtp_decode_Procedure(CONST LPVOID lpParam)
{
 port = param.Option.VideoPort;

 pAVPacket = av_packet_alloc();
 if (!pAVPacket)
 {
 MessageBox(NULL, L"ERROR Could not allocate pAVPacket", L"Init decoder error", MB_OK | MB_ICONERROR);
 exit(1);
 }
 av_init_packet(pAVPacket);

 /* find the MPEG-1 video decoder */
 pAVCodec = avcodec_find_decoder(AV_CODEC_ID_H264);
 if (!pAVCodec)
 {
 MessageBox(NULL, L"ERROR Codec not found", L"Init decoder error", MB_OK | MB_ICONERROR);
 exit(1);
 }

 pAVCodecParserContext = av_parser_init(pAVCodec->id);
 if (!pAVCodecParserContext)
 {
 MessageBox(NULL, L"ERROR Parser not found", L"Init decoder error", MB_OK | MB_ICONERROR);
 exit(1);
 }

 pAVCodecContext = avcodec_alloc_context3(pAVCodec);
 if (!pAVCodecContext) 
 {
 MessageBox(NULL, L"ERROR Could not allocate video codec context", L"Init decoder error", MB_OK | MB_ICONERROR);
 exit(1);
 }
 
 if (avcodec_open2(pAVCodecContext, pAVCodec, NULL) < 0)
 {
 MessageBox(NULL, L"ERROR Could not open codec", L"Init decoder error", MB_OK | MB_ICONERROR);
 exit(1);
 }

 pAVFrame = av_frame_alloc();
 if (!pAVFrame) 
 {
 MessageBox(NULL, L"ERROR Could not allocate video frame", L"Init decoder error", MB_OK | MB_ICONERROR);
 exit(1);
 } 
 
 while (FlagRTPActive)
 {
 if(port != param.Option.VideoPort)
 closesocket(RTPSocket);

 WaitForSingleObject(hSemaphoreRTP, 500); 
 Decode_NaluToAVFrameRGG();
 }

 avformat_free_context(pAVFormatContext);
 av_frame_free(&pAVFrame);
 avcodec_close(pAVCodecContext);
 av_packet_free(&pAVPacket);

 
 if (hTreadRTPDecode) CloseHandle(hTreadRTPDecode);

 return 0;
}

//------------------------------------------------------------------------------
char RTPSocketInit(void)
{ 
 sockaddr_in RTPSocketAddr;
 
 RTPSocketAddr.sin_family = AF_INET;
 RTPSocketAddr.sin_addr.s_addr = htonl(INADDR_ANY);
 RTPSocketAddr.sin_port = htons(param.Option.VideoPort);

 RTPSocket = socket(AF_INET, SOCK_DGRAM, IPPROTO_UDP);
 if (RTPSocket == INVALID_SOCKET)
 {
 MessageBox(NULL, L"ERROR Invalid RTP Socket", L"UDP Socket", MB_OK | MB_ICONERROR);
 return 0;
 }

 int option = 12000;
 if (setsockopt(RTPSocket, SOL_SOCKET, SO_RCVBUF, (char*)&option, sizeof(option)) < 0)
 {
 printf("setsockopt failed\n");

 }

 /*option = TRUE;
 if (setsockopt(RTPSocket, SOL_SOCKET, SO_CONDITIONAL_ACCEPT, (char*)&option, sizeof(option)) < 0)
 {
 printf("setsockopt failed\n");

 }*/

 if (bind(RTPSocket, (sockaddr*)&RTPSocketAddr, sizeof(RTPSocketAddr)) == SOCKET_ERROR)
 {
 MessageBox(NULL, L"ERROR bind", L"UDP Socket", MB_OK | MB_ICONERROR);
 closesocket(RTPSocket);
 return 0;
 }
 return 1;
}

//------------------------------------------------------------------------------
char RTPSocketRecive(void)
{
 static char RecvBuf[2000];
 static int BufLen = 2000;

 int iResult = 0;
 struct sockaddr_in SenderAddr;
 int SenderAddrSize = sizeof(SenderAddr);
 TCHAR szErrorMsg[100];

 iResult = recvfrom(RTPSocket, RecvBuf, BufLen, 0, NULL, NULL);
 if (iResult == SOCKET_ERROR && FlagRTPActive == TRUE)
 {
 StringCchPrintf(szErrorMsg, 100, L"ERROR recvfrom Ошибка:%d", WSAGetLastError());
 MessageBox(NULL, szErrorMsg, L"UDP Socket", MB_OK | MB_ICONERROR);
 return -1;
 }

 packet.data = (unsigned char*)RecvBuf;
 packet.size = iResult;

 return 1;
}

//------------------------------------------------------------------------------
void RTPPacketParser(void)
{
 RTPHeader_DType RTPHeader;
 RTPData_DType NALU;
 unsigned char* buffer = packet.data;
 int pos = 0;
 static int count = 0;
 static short lastSequenceNumber = 0xFFFF;
 short type;
 char payload_header;

 //read rtp header
 memcpy(&RTPHeader, buffer, sizeof(RTPHeader));
 RTPHeader.sequence_number = BYTE2_SWAP(RTPHeader.sequence_number);
 pos += 12; 
 
 if (RTPHeader.X) {
 //profile extension
 short define;
 short length;
 length = buffer[pos + 3];//suppose not so long extension
 pos += 4;
 pos += (length * 4);
 }

 payload_header = buffer[pos];
 type = payload_header & 0x1f; //Тип полезной нагрузки RTP
 pos++;
 
 //STAP-A
 if (type == 24)
 { 
 while (pos < packet.size)
 {
 unsigned short NALU_size;
 memcpy(&NALU_size, buffer + pos, 2);
 NALU_size = BYTE2_SWAP(NALU_size);
 pos += 2;
 char NAL_header = buffer[pos];
 short NAL_type = NAL_header & 0x1f;

 if (NAL_type == 7) 
 {
 count++;
 //cout<<"SPS, sequence number: "</cout<<"PPS, sequence number: "</cout<<"end of sequence, sequence number: "< 0) 
 {
 NALU.data = (unsigned char*) malloc(NALU_size + 4);
 NALU.size = NALU_size + 4;
 memcpy(NALU.data, &inteval, 4);
 memcpy(NALU.data + 4, &buffer[pos], NALU_size);

 WaitForSingleObject(hMutexRTPRecive, INFINITE);
 q.push(NALU);
 ReleaseMutex(hMutexRTPRecive);
 }

 pos += NALU_size;
 }
 }
 //FU-A Fragmentation unit
 else if (type == 28)
 { 
 //FU header
 char FU_header = buffer[pos];
 bool fStart = FU_header & 0x80;
 bool fEnd = FU_header & 0x40;

 //NAL header
 char NAL_header = (payload_header & 0xe0) | (FU_header & 0x1f);
 short NAL_type = FU_header & 0x1f;
 if (NAL_type == 7) 
 {
 count++;
 //SPS
 }
 else if (NAL_type == 8) 
 {
 //PPS
 }
 else if (NAL_type == 10) 
 {
 //end of sequence
 }
 pos++;

 int size = packet.size - pos;
 
 if (count > 0)
 {
 if (fStart) 
 {
 if (FU_buffer.size != 0)
 {
 free(FU_buffer.data);
 FU_buffer.size = 0;
 }
 FU_buffer.data = (unsigned char*)malloc(size + 5);
 if (FU_buffer.data == NULL)
 return;
 FU_buffer.size = size + 5;
 memcpy(FU_buffer.data, &inteval, 4);
 memcpy(FU_buffer.data + 4, &NAL_header, 1);
 memcpy(FU_buffer.data + 5, buffer + pos, size);
 }
 else
 {
 unsigned char* temp = (unsigned char*)malloc(FU_buffer.size + size);
 memcpy(temp, FU_buffer.data, FU_buffer.size);
 memcpy(temp + FU_buffer.size, buffer + pos, size);
 if (FU_buffer.size != 0) free(FU_buffer.data);
 FU_buffer.data = temp;
 FU_buffer.size += size;
 }

 if (fEnd)
 {
 NALU.data = (unsigned char*)malloc(FU_buffer.size);
 NALU.size = FU_buffer.size;
 memcpy(NALU.data, FU_buffer.data, FU_buffer.size);

 WaitForSingleObject(hMutexRTPRecive, INFINITE);
 q.push(NALU);
 ReleaseMutex(hMutexRTPRecive);

 free(FU_buffer.data);
 FU_buffer.size = 0;
 }
 }
 
 }
 else 
 {
 //other type
 short NAL_type = type;
 if (NAL_type == 7) 
 {
 count++;
 //SPS
 }
 else if (NAL_type == 8) 
 {
 //PPS
 }
 else if (NAL_type == 10) 
 {
 //end of sequence
 }

 int size = packet.size - pos + 1;
 if (count > 0)
 {
 NALU.data = (unsigned char*)malloc(size+4);
 NALU.size = size + 4;
 memcpy(NALU.data, &inteval, 4);
 memcpy(NALU.data + 4, &buffer[12], size);

 WaitForSingleObject(hMutexRTPRecive, INFINITE);
 q.push(NALU);
 ReleaseMutex(hMutexRTPRecive);
 }
 }
}

//------------------------------------------------------------------------------
void Decode_NaluToAVFrameRGG()
{
 unsigned char cntNALU;
 int len = 0;
 static int size = 0;
 unsigned char* data = NULL;
 int ret;
 RTPData_DType NALU;

 av_frame_unref(pAVFrame);
 av_packet_unref(pAVPacket);

 while(1)
 {
 WaitForSingleObject(hMutexRTPRecive, INFINITE);
 if (q.empty())
 {
 ReleaseMutex(hMutexRTPRecive);
 break;
 }
 NALU = q.front();
 q.pop();
 ReleaseMutex(hMutexRTPRecive);

 data = NALU.data;
 size = NALU.size;

 while(size)
 { 
 len = av_parser_parse2(pAVCodecParserContext, pAVCodecContext, &pAVPacket->data, &pAVPacket->size,
 (uint8_t*)data, size,
 AV_NOPTS_VALUE, AV_NOPTS_VALUE, AV_NOPTS_VALUE);

 data = len ? data + len : data;
 size -= len;
 
 if (pAVPacket->size)
 {
 ret = avcodec_send_packet(pAVCodecContext, pAVPacket);

 if(ret == AVERROR_EOF)
 MessageBox(NULL, L"the codec has been fully flushed, and there will be no more output frames", L"avcodec_send_packet", MB_OK | MB_ICONERROR);

 if (ret < 0)
 {
 MessageBox(NULL, L"ERROR sending a packet for decoding", L"Decode", MB_OK | MB_ICONERROR);
 //exit(1);
 }

 while (ret >= 0) 
 {
 ret = avcodec_receive_frame(pAVCodecContext, pAVFrame);
 if (ret == AVERROR(EAGAIN) || ret == AVERROR_EOF)
 break;
 else if (ret < 0) {
 MessageBox(NULL, L"ERROR during decoding", L"Decode", MB_OK | MB_ICONERROR);
 //exit(1);
 }
 
 AVFrameRGG = av_frame_alloc(); 
 pSwsContext = sws_getContext(pAVCodecContext->width, pAVCodecContext->height, pAVCodecContext->pix_fmt,
 pAVCodecContext->width, pAVCodecContext->height, AV_PIX_FMT_RGB24, SWS_SPLINE,
 0, 0, 0);

 sws_scale_frame(pSwsContext, AVFrameRGG, pAVFrame);
 
 ImgBufferSet(AVFrameRGG->data[0], pAVCodecContext->height, pAVCodecContext->width, AVFrameRGG->linesize[0]);

 sws_freeContext(pSwsContext);
 av_frame_free(&AVFrameRGG);
 }
 }
 }
 free(NALU.data);
 NALU.size = 0;
 } 
}

</int></queue></iostream></chrono>

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