生活紀錄

2023年6月2日星期五

DeepStream 之 nvdspreprocess 使用注意事項

nvdspreprocess 使用在 PGIE(Primary Gst Inference Engine)

g_object_set(G_OBJECT(pgie), "input-tensor-meta", 1, NULL);

or PGIE 的設定檔

input-tensor-from-meta=1

nvdspreprocess 的設定檔

# 需搭配 pgie_config.txt 的 model

# 0=NCHW, 1=NHWC, 2=CUSTOM

network-input-order=0

network-input-shape=2;3;384;1248

processing-width=1248

processing-height=384

tensor-name=Input

# 需搭配 pgie_config.txt 的 net-scale-factor

pixel-normalization-factor=1.0

2023年5月4日星期四

Nvidia TAO Computer Vision Sample Workflows

參考: Nvidia TAO(Train, Adapt, and Optimize)

user@host:~$ pip3 install --upgrade pip

Traceback (most recent call last):

File "/home/user/.local/bin/pip3", line 7, in <module>

from pip._internal.cli.main import main

ModuleNotFoundError: No module named 'pip._internal'

user@host:~$ python3 -m pip --version

pip 9.0.1 from /usr/lib/python3/dist-packages (python 3.6)

user@host:~$ python3 -m pip install --upgrade pip

Collecting pip

Cache entry deserialization failed, entry ignored

Using cached https://files.pythonhosted.org/packages/a4/6d/6463d49a933f547439d6b5b98b46af8742cc03ae83543e4d7688c2420f8b/pip-21.3.1-py3-none-any.whl

Installing collected packages: pip

Successfully installed pip-21.3.1

user@host:~$ pip3 install virtualenv

user@host:~$ pip3 install virtualenvwrapper

user@host:~$ mkdir .virtualenvs

user@host:~$ vi .bashrc

export WORKON_HOME=$HOME/.virtualenvs

export VIRTUALENVWRAPPER_PYTHON=/usr/bin/python3

source $HOME/.local/bin/virtualenvwrapper.sh

user@host:~$ source .bashrc

user@host:~$ mkvirtualenv tao -p /usr/bin/python3

(tao) user@host:~$ deactivate

user@host:~$ lsvirtualenv

user@host:~$ workon tao

(tao) user@host:~$ pip3 install nvidia-pyindex

(tao) user@host:~$ pip3 install nvidia-tao

(tao) user@host:~$ pip3 install jupyter

(tao) user@host:~$ tao info

到 https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tao/resources/cv_samples 網站

右上角 Download 選 WGET 或 CLI, 會將命令拷貝至剪貼簿，如下命令，並執行

ngc registry resource download-version "nvidia/tao/cv_samples:v1.4.1"

wget --content-disposition https://api.ngc.nvidia.com/v2/resources/nvidia/tao/cv_samples/versions/v1.4.1/zip -O cv_samples_v1.4.1.zip

(tao) user@host:~/Data/tao$ unzip -u cv_samples_v1.4.1.zip -d ./cv_samples_v1.4.1 && rm -rf cv_samples_v1.4.1.zip

user@host:~/Data/tao$ cp -ar cv_samples_v1.4.1/yolo_v4_tiny/ yolo_v4_tiny_1.4.1

(tao) user@host:~/Data/tao$ cd cv_samples_v1.4.1/

(tao) user@host:~/Data/tao/cv_samples_v1.4.1$

(tao) user@host:~/Data/tao/cv_samples_v1.4.1$ jupyter notebook --ip 0.0.0.0 --port 8888 --allow-root

依據命令返回說明，開啟網頁

進入 yolo_v4_tiny, 點選 yolo_v4_tiny.ipynb

修改下列環境變數到你真實的位置

%env LOCAL_PROJECT_DIR=YOUR_LOCAL_PROJECT_DIR_PATH

%env LOCAL_PROJECT_DIR=/home/user/Data/tao/yolo_v4_tiny_1.4.1

檢查工具版本

(tao) user@host:~/Data/tao/yolo_v4_tiny_1.4.1$ python3 --version

(tao) user@host:~/Data/tao/yolo_v4_tiny_1.4.1$ docker version

(tao) user@host:~/Data/tao/yolo_v4_tiny_1.4.1$ apt list -a nvidia-container-toolkit

(tao) user@host:~/Data/tao/yolo_v4_tiny_1.4.1$ apt list -a nvidia-docker2

(tao) user@host:~/Data/tao/yolo_v4_tiny_1.4.1$ nvidia-smi

(tao) user@host:~/Data/tao/yolo_v4_tiny_1.4.1$ docker login nvcr.io

到 https://catalog.ngc.nvidia.com/ 搜尋 object

可找到 TAO Pretrained Object Detection

進入，點選右上 Download, 選 CLI，將命令拷貝

可由命令查到真實位置

ngc registry model download-version "nvidia/tao/pretrained_object_detection:cspdarknet_tiny"

參考 https://catalog.ngc.nvidia.com/orgs/nvidia/containers/deepstream

user@host:~/Data/V2Pdetect$ docker run --gpus all -it --rm --net=host --privileged -v /tmp/.X11-unix:/tmp/.X11-unix -e DISPLAY=$DISPLAY -w /opt/nvidia/deepstream/deepstream-6.2 nvcr.io/nvidia/deepstream:6.2-devel

查詢已安裝套件的版本

參考 https://docs.nvidia.com/metropolis/deepstream/dev-guide/text/DS_Quickstart.html?highlight=compatibility#platform-and-os-compatibility

其中 nvidia driver 的版本, docker 是使用 host 的 driver

root@host:/opt/nvidia/deepstream/deepstream-6.2# pip list

root@host:/opt/nvidia/deepstream/deepstream-6.2# dpkg -l|grep nvinfer

root@host:/opt/nvidia/deepstream/deepstream-6.2# dpkg -l|grep cudnn

root@host:/opt/nvidia/deepstream/deepstream-6.2# cat /etc/os-release

root@host:/opt/nvidia/deepstream/deepstream-6.2# update-alternatives --display cuda

root@host:/opt/nvidia/deepstream/deepstream-6.2# nvidia-smi

root@host:/opt/nvidia/deepstream/deepstream-6.2# ./install.sh

root@host:/opt/nvidia/deepstream/deepstream-6.2# ./user_additional_install.sh

user@host:~/Data/DeepStream/deepstream_tao_apps$ git clone https://github.com/NVIDIA-AI-IOT/deepstream_tao_apps.git

user@host:~/Data/DeepStream/deepstream_tao_apps$ cd deepstream_tao_apps

user@host:~/Data/DeepStream/deepstream_tao_apps/deepstream_tao_apps$ git show-ref

user@host:~/Data/DeepStream/deepstream_tao_apps/deepstream_tao_apps$ cd ..

user@host:~/Data/DeepStream/deepstream_tao_apps$ mv deepstream_tao_apps deepstream_tao_apps-tao4.0_ds6.2ga

user@host:~/Data/DeepStream/deepstream_tao_apps$ cd deepstream_tao_apps-tao4.0_ds6.2ga/

user@host:~/Data/V2Pdetect$ docker run --gpus all -it --rm --net=host --privileged \

-v /tmp/.X11-unix:/tmp/.X11-unix \

-v /etc/localtime:/etc/localtime \

-v /home/user/Data/DeepStream/deepstream_tap_apps/deepstream_tao_apps-tao4.0_ds6.2ga/:/home/deepstream_tao_apps \

-v /home/user/Data/V2Pdetect/multi_rtsp:/home/multi_rtsp \

-e DISPLAY=$DISPLAY \

-w /opt/nvidia/deepstream/deepstream-6.2 \

nvcr.io/nvidia/deepstream:6.2-devel

root@host:/opt/nvidia/deepstream/deepstream-6.2# cd /home/deepstream_tao_apps/

root@host:/home/deepstream_tao_apps# ./download_models.sh

root@host:/home/deepstream_tao_apps# ls models/yolov4-tiny/

root@host:/home/deepstream_tao_apps# cd post_processor/

root@host:/home/deepstream_tao_apps/post_processor# make

Makefile:25: *** "CUDA_VER is not set". Stop.

root@host:/home/deepstream_tao_apps/post_processor# dpkg -l | grep CUDA

root@host:/home/deepstream_tao_apps/post_processor# export CUDA_VER=11.8

root@host:/home/deepstream_tao_apps/post_processor# cd ../apps/tao_detection/

root@host:/home/deepstream_tao_apps/apps/tao_detection# make

自己準備個 sample_720p.h264，以便測試

root@host:/home/deepstream_tao_apps/apps/tao_detection# ./ds-tao-detection -c ../../configs/yolov4-tiny_tao/pgie_yolov4_tiny_tao_config.txt -i file:///home/deepstream_tao_apps/sample/streams/sample_720p.h264 -d

root@host:/home/deepstream_tao_apps/apps/tao_detection# ./ds-tao-detection -c ../../configs/yolov4-tiny_tao/pgie_yolov4_tiny_tao_config.txt -i rtsp://root:passwd@192.168.0.107:554/live1s1.sdp -d

將 tao 產生的 labels.txt, yolov4_cspdarknet_tiny_epoch_080.etlt 拷貝到 deepstream_tao_apps 下

並合併 nvinfer_config.txt 和 pgie_yolov4_tiny_tao_config.txt

root@host:/home/deepstream_tao_apps/apps/tao_detection# ./ds-tao-detection -c ../../configs/yolov4-tiny_tao/pgie_light.txt -i file:///home/deepstream_tao_apps/sample/streams/sample_720p.h264 -d

root@host:/home/multi_rtsp# apt-get update

root@host:/home/multi_rtsp# apt-get install libopencv-dev

root@host:/home/multi_rtsp# apt-get install libclutter-gst-3.0-dev

2023年3月29日星期三

檢查 memory leak

安裝 valgrind

$ sudo apt update

$ sudo apt install snapd

$ sudo snap install valgrind --classic

$ gcc -g -o debug_prog debug_prog.c

$ g++ -g -o debug_prog debug_prog.c

開啟兩個 terminal

$ valgrind --vgdb=yes --vgdb-error=0 --tool=memcheck --leak-check=full ./debug_prog

$ gdb ./debug_prog

(gdb) target remote | vgdb

(gdb) break linenum

(gdb) next

(gdb) step

(gdb) monitor leak_check full reachable any

(gdb) kill

(gdb) quit

若只是單純檢查 memory leak

$ valgrind --tool=memcheck --leak-check=full ./debug_prog

suppression 一些錯誤

$ valgrind --tool=memcheck --leak-check=full --gen-suppressions=all ./debug_prog

...

{

<insert_a_suppression_name_here>

Memcheck:Leak

match-leak-kinds: definite

fun:malloc

fun:g_malloc

obj:/usr/lib/x86_64-linux-gnu/libglib-2.0.so.0.5600.4

fun:call_init

fun:_dl_init

obj:/lib/x86_64-linux-gnu/ld-2.27.so

}

...

利用上個命令的輸出，產生 local.supp 檔

$ valgrind --tool=memcheck --leak-check=full --supressions=./local.supp ./debug_prog

$ valgrind --tool=memcheck --leak-check=full --gen-suppressions=all --log-file=supp.log --supressions=./local.supp ./debug_prog

$ cat ./supp.log | ./suppressions.sh > local.supp

$ valgrind --tool=memcheck --leak-check=full --supressions=./local.supp --supressions=./gtk.supp ./debug_prog

suppressions.sh 若產生下列錯誤

awk: 34: unexpected character '&'

需改變 awk 的版本為 gawk

$ awk -W version

$ sudo apt-get update

$ sudo apt-get install gawk

去除 definitely loss

== 16,384 bytes in 1 blocks are definitely lost in loss record 1,443 of 1,448

== at 0x4C330C5: malloc (vg_replace_malloc.c:393)

== by 0x6A0BBD8: g_malloc (gmem.c:99)

== by 0x6A1674B: g_quark_init (gquark.c:62)

== by 0x40108D2: call_init (dl-init.c:72)

== by 0x40108D2: _dl_init (dl-init.c:119)

== by 0x40010C9: ??? (in /lib/x86_64-linux-gnu/ld-2.27.so)

下載 gst.supp 和 glib.supp gtk.supp

https://gitlab.freedesktop.org/gstreamer/common/-/blob/master/gst.supp

https://github.com/GNOME/glib/blob/main/tools/glib.supp

https://gist.github.com/pendingchaos/81feddb95c06aeb58e2f

Makefile 的

CFLAGS+= -g -O0

安裝 libglib 的 debug symbols 版本

$ echo "deb http://ddebs.ubuntu.com $(lsb_release -cs) main restricted universe multiverse

deb http://ddebs.ubuntu.com $(lsb_release -cs)-updates main restricted universe multiverse

deb http://ddebs.ubuntu.com $(lsb_release -cs)-proposed main restricted universe multiverse" | \

sudo tee -a /etc/apt/sources.list.d/ddebs.list

$ sudo apt install ubuntu-dbgsym-keyring

$ sudo apt update

$ sudo apt install libglib2.0-bin-dbgsym libglib2.0-0-dbgsym libglib2.0-dev-bin-dbgsym

export G_DEBUG=gc-friendly

export G_SLICE=always-malloc

valgrind -v --time-stamp=yes --tool=memcheck --leak-check=full \

--gen-suppressions=all --log-file=supp.log \

--suppressions=./glib.supp \

--suppressions=./gst.supp \

--suppressions=./gtk.supp \

./main

常用觀測記憶體使用狀態命令

$ while true; do echo -n `date +"%Y/%m/%d %H:%M:%S"`" " | tee -a aaa.log ; grep "VmRSS" /proc/26885/status | tee -a aaa.log ; sleep 60 ; done

2023年3月21日星期二

deepstream create_pipeline 分析

/opt/nvidia/deepstream/deepstream-6.0/sources/apps/sample_apps/deepstream-app/deepstream_app.c

create_pipeline (AppCtx * appCtx,

bbox_generated_callback bbox_generated_post_analytics_cb,

bbox_generated_callback all_bbox_generated_cb, perf_callback perf_cb,

overlay_graphics_callback overlay_graphics_cb)

{

multi_src_bin = create_multi_source_bin {

sub_bins[] = create_camera_source_bin |

create_uridecode_src_bin |

create_rtsp_src_bin |

create_uridecode_src_bin_audio;

sub_bins[] - nvstreammux;

};

create_common_elements {

secondary_gie_bin = create_secondary_gie_bin {

sub_bins[] = create_secondary_gie {

secondary_gie = nvinfer | nvinferserver

if (num_children == 0) {

queue - secondary_gie - fakesink

} else {

queue - secondary_gie - tee

}

};

tee - queue

tee - sub_bins[]...

};

dsanalytics_bin = create_dsanalytics_bin {

queue - nvdsanalytics

};

tracker_bin = create_tracking_bin { nvtracker };

primary_gie_bin = create_primary_gie_bin {

queue - nvvideoconvert - (nvinfer | nvinferserver)

};

preprocess_bin = create_preprocess_bin {

queue | nvdspreprocess

};

common_elements = nvmsgconv - tee

{ preprocess_bin - primary_gie_bin - tracker_bin -

dsanalytics_bin - secondary_gie_bin - common_elements -

tee

};

secondary_gie_bin(src) -> bbox_generated_post_analytics_cb()

sink_elem = preprocess_bin

src_elem = tee

};

dsexample_bin = create_dsexample_bin {

queue - nvvideoconvert - capsfilter - dsexample

};

demuxer = { nvstreamdemux };

instance_bins[] = create_processing_instance {

osd_bin = create_osd_bin {

queue - nvvideoconvert - queue - nvdsosd

};

sink_bin = create_sink_bin {

sub_bins[] = create_render_bin |

create_encode_file_bin |

create_udpsink_bin |

create_msg_conv_broker_bin

queue - tee - sub_bins[]

};

osd_bin - sink_bin

(sink)osd_bin -> all_bbox_generated_cb()

(sink)osd_bin -> overlay_graphics_cb()

};

demux_instance_bins[] = create_demux_pipeline {

osd_bin = create_osd_bin {

queue - nvvideoconvert - queue - nvdsosd

};

demux_sink_bin = create_demux_sink_bin {

sub_bins[] = create_render_bin |

create_encode_file_bin |

create_udpsink_bin |

create_msg_conv_broker_bin

queue - tee - sub_bins[]

};

osd_bin - demux_sink_bin

};

tiled_display_bin = create_tiled_display_bin {

queue - nvmultistreamtiler

};

if (tiled_display_config.enable) {

multi_src_bin - (sink_elem-src_elem) - dsexample_bin - tiler_tee

tiler_tee - nvstreamdemux - demux_instance_bins[]

tiler_tee - tiled_display_bin - instance_bins[]

} else {

multi_src_bin - (sink_elem-src_elem) - dsexample_bin - demuxer - instance_bins[]

};

2023年3月17日星期五

ubuntu cpu 工作頻率設定

$ sudo apt-get install cpufrequtils

$ cpufreq-info

$ for i in {0..15}

> do

> sudo cpufreq-set -d 800000 -u 3200000 -c $i

> done

$ watch -n1 "grep Hz /proc/cpuinfo | grep -v model"

$ watch sensors

2023年3月9日星期四

lftp in wsl

vi ~/.ssh/config

Host 192.168.5.9

KexAlgorithms +diffie-hellman-group1-sha1

HostKeyAlgorithms ssh-rsa

PubkeyAcceptedKeyTypes ssh-rsa

lftp command

set FTP_USER=digichance

set FTP_PASSWD=sh22463458

set FTP_SITE=114.33.245.149

set FTP_PORT=22

rem set FTP_PORT=7010

set FTP_LOCAL=/cygdrive/D/Photo

set FTP_REMOTE=/d:/temp

set FTP_CMD=lftp.exe

set PATH=%PATH%;C:\lftp-4.9.2.win64-openssl\bin

set PUT=Y

set REMOVE_SOURCE=N

set today=%date:~0,10%

set dy=%today:~0,4%

set dm=%today:~5,2%

set dd=%today:~8,2%

set YES_DAY=%dy%%dm%%dd%

call YesDay.bat %YES_DAY%

echo %YES_DAY%

call YesDay.bat %YES_DAY%

echo %YES_DAY%

if "%REMOVE_SOURCE%"=="Y" (

set REMOVE_CMD=--Remove-source-dirs

) else (

set REMOVE_CMD=

)

if "%PUT%"=="Y" (

set FILE_LIST=-R %FTP_LOCAL%/%1 %1

) else (

set FILE_LIST=%1 %FTP_LOCAL%/%1

)

%FTP_CMD% -c "set sftp:auto-confirm yes;set net:timeout 5;set net:max-retries 3; open -u %FTP_USER%,%FTP_PASSWD% -p %FTP_PORT% sftp://%FTP_SITE%; cd %FTP_REMOTE%; mirror %REMOVE_CMD% %FILE_LIST%; quit"

rem GET YESTERDAY DATE

rem for Windows 2000,XP,2003

rem http://hi.baidu.com/uroot

@echo off

set dt=%1%

rem date format is "YYYYMMDD"

rem set /P dt="Input Date: "

set dy=%dt:~0,4%

set dm=%dt:~4,2%

set dd=%dt:~6,2%

echo %dy%-%dm%-%dd%

if %dm%%dd%==0101 goto L01

if %dm%%dd%==0201 goto L02

if %dm%%dd%==0301 goto L07

if %dm%%dd%==0401 goto L02

if %dm%%dd%==0501 goto L04

if %dm%%dd%==0601 goto L02

if %dm%%dd%==0701 goto L04

if %dm%%dd%==0801 goto L02

if %dm%%dd%==0901 goto L02

if %dm%%dd%==1001 goto L05

if %dm%%dd%==1101 goto L03

if %dm%%dd%==1201 goto L06

if %dd%==02 goto L10

if %dd%==03 goto L10

if %dd%==04 goto L10

if %dd%==05 goto L10

if %dd%==06 goto L10

if %dd%==07 goto L10

if %dd%==08 goto L10

if %dd%==09 goto L10

if %dd%==10 goto L11

set /A dd=dd-1

set dt=%dy%-%dm%-%dd%

goto END

:L10

set /A dd=%dd:~1,1%-1

set dt=%dy%-%dm%-0%dd%

set dd=0%dd%

goto END

:L11

set dt=%dy%-%dm%-09

set dd=09

goto END

:L02

set /A dm=%dm:~1,1%-1

set dt=%dy%-0%dm%-31

set dm=0%dm%

set dd=31

goto END

:L04

set /A dm=dm-1

set dt=%dy%-0%dm%-30

set dm=0%dm%

set dd=30

goto END

:L05

set dt=%dy%-09-30

set dm=09

set dd=30

goto END

:L03

set dt=%dy%-10-31

set dm=10

set dd=31

goto END

:L06

set dt=%dy%-11-30

set dm=11

set dd=30

goto END

:L01

set /A dy=dy-1

set dt=%dy%-12-31

set dm=12

set dd=31

goto END

:L07

set /A "dd=dy%%4"

if not %dd%==0 goto L08

set /A "dd=dy%%100"

if not %dd%==0 goto L09

set /A "dd=dy%%400"

if %dd%==0 goto L09

:L08

set dt=%dy%-02-28

set dm=02

set dd=28

goto END

:L09

set dt=%dy%-02-29

set dm=02

set dd=29

goto END

:END

rem echo %dt%

set YES_DAY=%dy%%dm%%dd%

訂閱：文章 (Atom)

網頁

2023年6月2日 星期五

2023年5月4日 星期四

2023年3月29日 星期三

2023年3月21日 星期二

2023年3月17日 星期五

2023年3月9日 星期四

2023年6月2日星期五

2023年5月4日星期四

2023年3月29日星期三

2023年3月21日星期二

2023年3月17日星期五

2023年3月9日星期四