办网站如何备案,小型办公室装修,国内网站搭建平台,seo管理是什么自从毕业后开始进入了华为曻腾生态圈#xff0c;现在越来越多的公司开始走国产化路线了#xff0c;现在国内做AI芯片的厂商比如#xff1a;寒武纪、地平线等#xff0c;虽然我了解的不多#xff0c;但是相对于瑞芯微这样的AI开发板来说#xff0c;华为曻腾的生态比瑞芯微… 自从毕业后开始进入了华为曻腾生态圈现在越来越多的公司开始走国产化路线了现在国内做AI芯片的厂商比如寒武纪、地平线等虽然我了解的不多但是相对于瑞芯微这样的AI开发板来说华为曻腾的生态比瑞芯微好太多了参考文档非常多学习资料也有很多也容易上手开发。
华为曻腾官网昇腾AI应用案例-昇腾社区 (hiascend.com) 直接步入正题现在的目标检测已经很成熟了所以越来越多的公司会用到基于检测的跟踪算法这样不仅起到了单一检测功能还有跟踪目标或者计数的功能 现在应用较广泛的目标检测算法从最开始的yolov5一直到现在的yolov8虽然只是简单的看了一下算法的原理整体来说yolo的更新还是针对神经网络在GPU上的优化加速而对比曻腾NPUyolov5的速度还是在其他yolo算法中速度最快的一个 目标跟踪算法以前是sortyolo,deepsortyolo,bytetrack,fairmot等算法本章主要介绍如何利用华为的ACL语言ffmpeg推流进行整个业务的开发流程大家可以借鉴下面的开发代码首先你要具备基本的ACL语言知识以及yolov5的后处理逻辑跟踪方面直接借鉴开源作者的卡尔曼滤波进行预测更新即可参考主函数代码如下
//1.先测试yolov5_nms可以泡桐
//使用dvppaipp编解码再使用opencv进行#includeiostream#includeacl/acl.h
#include opencv2/opencv.hpp
#include opencv2/imgproc/types_c.h
#include acllite/AclLiteUtils.h
#include acllite/AclLiteError.h
#include acllite/AclLiteResource.h
#include acllite/AclLiteModel.h
#include acllite/AclLiteImageProc.h
#include AclLiteVideoProc.h
#include AclLiteVideoCapBase.h
#include BYTETracker.h
#include chrono
externC {#include libavutil/mathematics.h#include libavutil/time.h#include libavcodec/avcodec.h#include libavformat/avformat.h#include libswscale/swscale.h#include libavutil/imgutils.h#include libavutil/opt.h
};
using namespace std;
using namespace cv;
typedef struct box {float x;float y;float w;float h;float score;size_t classIndex;size_t index; // index of output buffer
} box;
namespace{int a 0;
}
int main()
{//1.定义初始化变量dvpp\model\acl\rtsp解码接口capAclLiteResource aclDev;aclrtRunMode g_runMode_;AclLiteVideoProc* cap_;AclLiteImageProc g_dvpp_;AclLiteModel g_model_;string streamName_;streamName_ rtsp://admin:ascend66610.1.16.108/LiveMedia/ch1/Media1;//ffmpeg初始化AVFormatContext* g_fmtCtx;AVCodecContext* g_codecCtx;AVStream* g_avStream;AVCodec* g_codec;AVPacket* g_pkt;AVFrame* g_yuvFrame;uint8_t* g_yuvBuf;AVFrame* g_rgbFrame;uint8_t* g_brgBuf;int g_yuvSize;int g_rgbSize;struct SwsContext* g_imgCtx;
//参数初始化
//rtsp初始化g_avStream NULL;g_codec NULL;g_codecCtx NULL;g_fmtCtx NULL;g_pkt NULL;g_imgCtx NULL;g_yuvSize 0;g_rgbSize 0;int picWidth 416;int picHeight 416;string rtsp_url rtsp://192.168.3.38:8554/stream;int channelId 0;string g_outFile rtsp_url to_string(channelId);
//rtsp初始化avformat_network_init();if (avformat_alloc_output_context2(g_fmtCtx, NULL, g_avFormat.c_str(), g_outFile.c_str()) 0) {ACLLITE_LOG_ERROR(Cannot alloc output file context);return ACLLITE_ERROR;}av_opt_set(g_fmtCtx-priv_data, rtsp_transport, tcp, 0);av_opt_set(g_fmtCtx-priv_data, tune, zerolatency, 0);av_opt_set(g_fmtCtx-priv_data, preset, superfast, 0);//获取编码器的ID返回一个编码器g_codec avcodec_find_encoder(AV_CODEC_ID_H264);if (g_codec NULL) {ACLLITE_LOG_ERROR(Cannot find any endcoder);return ACLLITE_ERROR;}g_codecCtx avcodec_alloc_context3(g_codec);if (g_codecCtx NULL) {ACLLITE_LOG_ERROR(Cannot alloc context);return ACLLITE_ERROR;}//创建流g_avStream avformat_new_stream(g_fmtCtx, g_codec);if (g_avStream NULL) {ACLLITE_LOG_ERROR(failed create new video stream);return ACLLITE_ERROR;}//设置帧率g_avStream-time_base AVRational{1, g_frameRate};//设置编码参数AVCodecParameters* param g_fmtCtx-streams[g_avStream-index]-codecpar;param-codec_type AVMEDIA_TYPE_VIDEO;param-width picWidth;param-height picHeight;avcodec_parameters_to_context(g_codecCtx, param);//参数绑定设置g_codecCtx-pix_fmt AV_PIX_FMT_NV12;g_codecCtx-time_base AVRational{1, g_frameRate};g_codecCtx-bit_rate g_bitRate;g_codecCtx-gop_size g_gopSize;g_codecCtx-max_b_frames 0;if (g_codecCtx-codec_id AV_CODEC_ID_H264) {g_codecCtx-qmin 10;g_codecCtx-qmax 51;g_codecCtx-qcompress (float)0.6;}if (g_codecCtx-codec_id AV_CODEC_ID_MPEG1VIDEO)g_codecCtx-mb_decision 2;//初始化codeif (avcodec_open2(g_codecCtx, g_codec, NULL) 0) {ACLLITE_LOG_ERROR(Open encoder failed);return ACLLITE_ERROR;}//g_codecCtx参数传递给codecparavcodec_parameters_from_context(g_avStream-codecpar, g_codecCtx);//指定输出数据的形式av_dump_format(g_fmtCtx, 0, g_outFile.c_str(), 1);//写文件头int ret1 avformat_write_header(g_fmtCtx, NULL);if (ret1 ! AVSTREAM_INIT_IN_WRITE_HEADER) {ACLLITE_LOG_ERROR(Write file header fail);return ACLLITE_ERROR;}g_pkt av_packet_alloc();//传输数据初始化g_rgbFrame av_frame_alloc();g_yuvFrame av_frame_alloc();g_rgbFrame-width g_codecCtx-width;g_yuvFrame-width g_codecCtx-width;g_rgbFrame-height g_codecCtx-height;g_yuvFrame-height g_codecCtx-height;g_rgbFrame-format AV_PIX_FMT_BGR24;g_yuvFrame-format g_codecCtx-pix_fmt;g_rgbSize av_image_get_buffer_size(AV_PIX_FMT_BGR24, g_codecCtx-width, g_codecCtx-height, 1);g_yuvSize av_image_get_buffer_size(g_codecCtx-pix_fmt, g_codecCtx-width, g_codecCtx-height, 1);g_brgBuf (uint8_t*)av_malloc(g_rgbSize);g_yuvBuf (uint8_t*)av_malloc(g_yuvSize);//内存分配int ret2 av_image_fill_arrays(g_rgbFrame-data, g_rgbFrame-linesize,g_brgBuf, AV_PIX_FMT_BGR24,g_codecCtx-width, g_codecCtx-height, 1);ret2 av_image_fill_arrays(g_yuvFrame-data, g_yuvFrame-linesize,g_yuvBuf, g_codecCtx-pix_fmt,g_codecCtx-width, g_codecCtx-height, 1);g_imgCtx sws_getContext(g_codecCtx-width, g_codecCtx-height, AV_PIX_FMT_BGR24,g_codecCtx-width, g_codecCtx-height, g_codecCtx-pix_fmt,SWS_BILINEAR, NULL, NULL, NULL);//2.类变量初始化AclLiteError ret aclDev.Init();if (ret) {ACLLITE_LOG_ERROR(Init resource failed, error %d, ret);return ACLLITE_ERROR;}if (ACLLITE_OK ! OpenVideoCapture()) {return ACLLITE_ERROR;}ret g_dvpp_.Init();if (ret) {ACLLITE_LOG_ERROR(Dvpp init failed, error %d, ret);return ACLLITE_ERROR;}cap_ nullptr;ret g_model_.Init();if (ret) {ACLLITE_LOG_ERROR(Model init failed, error %d, ret);return ACLLITE_ERROR;}//3.创建模型img_info的输入以及数据拷贝操作g_runMode_ g_aclDev_.GetRunMode();const float imageInfo[4] {(float)g_modelInputWidth, (float)g_modelInputHeight,(float)g_modelInputWidth, (float)g_modelInputHeight};g_imageInfoSize_ sizeof(imageInfo);g_imageInfoBuf_ CopyDataToDevice((void *)imageInfo, g_imageInfoSize_,g_runMode_, MEMORY_DEVICE);if (g_imageInfoBuf_ nullptr) {ACLLITE_LOG_ERROR(Copy image info to device failed);return ACLLITE_ERROR;}//4.获取视频源cap_ new AclLiteVideoProc(streamName_);//5.视频流解码以及dvpp硬件-resizeint i 0;while(true){//6.获取解码图片在device侧的YUV420图片存放在ImageDta结构体中
// struct ImageData {
// acldvppPixelFormat format;
// uint32_t width 0;
// uint32_t height 0;
// uint32_t alignWidth 0;
// uint32_t alignHeight 0;
// uint32_t size 0;
// std::shared_ptruint8_t data nullptr;
// };
i;ImageData image;ret cap_-Read(image);ImageData resizedImage;ret g_dvpp_.Resize(resizedImage, image, 640, 640);//7.创建模型输入进行模型推理ret g_model_.CreateInput(resizedImage.data.get(), resizedImage.size,g_imageInfoBuf_, g_imageInfoSize_);if (ret ! ACLLITE_OK) {ACLLITE_LOG_ERROR(Create mode input dataset failed, error:%d, ret);return ACLLITE_ERROR;}std::vectorInferenceOutput inferenceOutput;ret g_model_.Execute(inferenceOutput);if (ret ! ACLLITE_OK) {g_model_.DestroyInput();ACLLITE_LOG_ERROR(Execute model inference failed, error: %d, ret);return ACLLITE_ERROR;}g_model_.DestroyInput();//8.将YUV图像转换为opencv图像ImageData yuvImage;ret CopyImageToLocal(yuvImage, image, g_runMode_);if (ret ACLLITE_ERROR) {ACLLITE_LOG_ERROR(Copy image to host failed);return ACLLITE_ERROR;}cv::Mat yuvimg(yuvImage.height * 3 / 2, yuvImage.width, CV_8UC1, yuvImage.data.get());cv::Mat origImage;cv::cvtColor(yuvimg, origImage, CV_YUV2BGR_NV12);//模型后处理根据目标跟踪需要的输入进行获取xywhfloat* detectData (float *)inferenceOutput[0].data.get();float* boxNum (float *)inferenceOutput[1].data.get();uint32_t totalBox boxNum[0];//获取x,y,w,h std::vectorObject obj;float widthScale (float)(origImage.cols) / 640.0;float heightScale (float)(origImage.rows) / 640.0;vectorbox detectResults;for (uint32_t i 0; i totalBox; i) {box boundBox;boundBox.score float(detectData[totalBox * SCORE i]);boundBox.x detectData[totalBox * TOPLEFTX i] * widthScale;boundBox.y detectData[totalBox * TOPLEFTY i] * heightScale;boundBox.w detectData[totalBox * BOTTOMRIGHTX i] * widthScale;boundBox.h detectData[totalBox * BOTTOMRIGHTY i] * heightScale;boundBox.classIndex (uint32_t)detectData[totalBox * LABEL i];detectResults.emplace_back(boundBox);}for (size_t i 0; i detectResults.size(); i){if (res[i].classId ! class_id){ continue; }obj[i].label detectResults[i].classIndex;obj[i].rect.x detectResults[i].x;obj[i].rect.y detectResults[i].y;obj[i].rect.height detectResults[i].h;obj[i].rect.width detectResults[i].w;obj[i].prob detectResults[i].score;}std::vectorSTrack output_stracks tracker.update(obj);for (size_t i 0; i output_stracks.size(); i){std::vectorfloat tlwh output_stracks[i].tlwh;cv::Scalar __color tracker.get_color(output_stracks[i].track_id);cv::putText(origImage, std::to_string(output_stracks[i].track_id), cv::Point(tlwh[0], tlwh[1] - 10), cv::FONT_ITALIC, 0.75, __color, 2);cv::rectangle(origImage, cv::Rect(tlwh[0], tlwh[1], tlwh[2], tlwh[3]), __color, 2); }//跟踪完成后写推流memcpy(g_brgBuf, origImage.data, g_rgbSize);sws_scale(g_imgCtx,g_rgbFrame-data,g_rgbFrame-linesize,0,g_codecCtx-height,g_yuvFrame-data,g_yuvFrame-linesize);g_yuvFrame-pts i;if (avcodec_send_frame(g_codecCtx, g_yuvFrame) 0) {// coutaendl;while (avcodec_receive_packet(g_codecCtx, g_pkt) 0) {coutavcodec_receive_packetendl;g_pkt-stream_index g_avStream-index;av_packet_rescale_ts(g_pkt, g_codecCtx-time_base, g_avStream-time_base);g_pkt-pos -1;int ret av_interleaved_write_frame(g_fmtCtx, g_pkt);if (ret 0) {ACLLITE_LOG_ERROR(error is: %d, ret);}}}}av_packet_free(g_pkt);avcodec_close(g_codecCtx);if (g_fmtCtx) {avio_close(g_fmtCtx-pb);avformat_free_context(g_fmtCtx);}if (cap_ ! nullptr) {cout cap is not open endl;cap_-Close();delete cap_;}dvpp_.DestroyResource();return 0;
}
跟踪器方面的函数可以搜索开源代码yolov5-bytetrack-main.cpp截取内部跟踪部分检测部分使用华为ACL编写的推理代码进行检测
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