Record CSI-Camera to h264 video

gst-launch-1.0 nvarguscamerasrc ! 'video/x-raw(memory:NVMM), width=1920, height=1080,format=NV12, framerate=30/1' ! nvvidconv ! 'video/x-raw(memory:NVMM), format=(string)I420' ! nvv4l2h264enc preset-level=4 MeasureEncoderLatency=1 ! 'video/x-h264, stream-format=(string)byte-stream, alignment=(string)au' ! filesink location=file.h264 -e 

gst-launch-1.0 filesrc location=file.h264 ! h264parse ! nvv4l2decoder ! nvvidconv ! nveglglessink -e

TLT+DeepStream on ICDAR-2013

到 ICDAR-2013 的網站下載圖片和標註

ICDAR-2013 在 Robust Reading Competition 網站

要下載前要註冊

選 Challenges/Focused Scene Text

2013 的文字比較正，標註只有兩點

2015 的文字有各種角度，標註有四點

產生 kitti 資料時，直接使用訓練效果不好

轉換圖形時採用不同策略，一圖拆成多圖

截圖時不要破壞文字

TLT 有測試過 detectnet_v2 (resnet18, resnet50, darknet19), object_detection yolov3 (darknet19)

detectnet_v2 之 resnet18 precision: 14.6133 %

雖然 precision 不高，但是 tlt-infer 可以正確抓到文字

detectnet_v2 之 darknet19 precision: 18.7146 %

但 detectnet_v2 之 darknet19 失敗，tlt-infer 可以無法正確抓到文字

yolov3 之 darknet19 AP: 0.769

效果比 detectnet_v2 好

最看重 TLT 的功能是 tlt-prune, 神經網路被裁剪後

節省記憶體，加快速度

unprune Mem:2.5G   PREF:8.33

0.5        Mem:2.1G    PREF:28.83

0.7        Mem:2.1G    PREF:30.00

DeepStream 之 nvinfer 的 config-file-path 設定檔

tlt-encoded-model=yolo_darknet19_pruned_70.etlt

model-engine-file=yolo_darknet19_pruned_70.engine

第一次啟動會很慢，因為在產生 yolo_darknet19_pruned_70.etlt_b1_gpu0_fp16.engine 檔

$ mv yolo_darknet19_pruned_70.etlt_b1_gpu0_fp16.engine yolo_darknet19_pruned_70.engine

之後會直接使用 yolo_darknet19_pruned_70.engine

以下是測試歷程記錄

Build TensorRT OSS on Jetson

參考 TensorRT Open Source Software (OSS)

更新 CMake
$ wget http://www.cmake.org/files/v3.13/cmake-3.13.0.tar.gz
$ tar xpvf cmake-3.13.0.tar.gz cmake-3.13.0
$ cd cmake-3.13.0
$ ./bootstrap --system-curl
$ make -j4

$ sudo ln -s /home/nano/Data/cmake-3.13.0/cmake /usr/local/bin/cmake

$ git clone -b release/7.1 https://github.com/nvidia/TensorRT

$ cd TensorRT/

$ git submodule update --init --recursive

$ export TRT_SOURCE=`pwd`

$ cd $TRT_SOURCE

$ mkdir -p build && cd build

$ /usr/local/bin/cmake .. -DGPU_ARCHS=53 \

-DTRT_LIB_DIR=/usr/lib/aarch64-linux-gnu/ \

-DCMAKE_C_COMPILER=/usr/bin/gcc \

-DCMAKE_CUDA_COMPIILER=/usr/local/cuda-10.2/bin/nvcc \

-DTRT_BIN_DIR=`pwd`/out

$ make nvinfer_plugin -j$(nproc)$ mkdir backup
$ sudo mv /usr/lib/aarch64-linux-gnu/libnvinfer_plugin.so.7.1.3 backup
$ sudo cp libnvinfer_plugin.so.7.1.3 /usr/lib/aarch64-linux-gnu/libnvinfer_plugin.so.7.1.3
$ sudo ldconfig

由此下載 tlt-converter

$ mkdir tlt-converter

$ mv tlt_7.1.zip tlt-converter

$ cd tlt-converter

$ unzip tlt_7.1.zip

$ vi ~/.bashrc 加入
export TRT_LIB_PATH=”/usr/lib/aarch64-linux-gnu”
export TRT_INC_PATH=”/usr/include/aarch64-linux-gnu”

jetson nano install tensorflow

$ sudo apt-get update

$ sudo apt-get install libhdf5-serial-dev hdf5-tools libhdf5-dev zlib1g-dev zip libjpeg8-dev liblapack-dev libblas-dev gfortran

$ sudo apt-get install python3-pip

$ sudo pip3 install -U pip testresources setuptools==49.6.0

$ sudo apt-get install virtualenv

$ make envs

$ cd envs

$ sudo pip3 install -U numpy==1.16.1 future==0.18.2 mock==3.0.5 h5py==2.10.0 keras_preprocessing==1.1.1 keras_applications==1.0.8 gast==0.2.2 futures protobuf pybind11

$ python3 -m virtualenv -p python3 tensorflow-2.3.1

$ source tensorflow-2.3.1/bin/activate

$ pip3 install --extra-index-url https://developer.download.nvidia.com/compute/redist/jp/v44 tensorflow==2.3.1+nv20.11

$ python3 -m virtualenv -p python3 tensorflow-1.15.4

$ source tensorflow-1.15.4/bin/activate

$ pip3 install --extra-index-url https://developer.download.nvidia.com/compute/redist/jp/v44 tensorflow==1.15.4+nv20.11

xpra 常用命令

啟動 xterm, select to copy, shift+insert or middle-click to paste

開啟選項 ctrl+middle-click

設定 buffer size -sl

顯示 scrollbar -sb

黑筆白字 -fg white -bg black

>Xpra.exe start ssh://user@ip/session --exit-with-children=yes --start-child="xterm -fa Monospace -fs 16 -xrm 'XTerm*selectToClipboard: true' -sl 1000 -sb -fg white -bg black"

>Xpra.exe start ssh://user@ip/session --exit-with-children=yes --start-child=/opt/google/chrome/chrome

>Xpra.exe start ssh://user@ip/session --exit-with-children=yes --start-child=/usr/bin//chromium-browser

>Xpra.exe stop ssh://user@ip/session

>Xpra.exe attach ssh://user@ip/session

>Xpra.exe detach ssh://user@ip/session

連上目前的桌面，如 vnc

>Xpra.exe shadow ssh://user@ip/1

>Xpra.exe shadow ssh://user@ip

$ xpra list

$ xpra start :session

$ DISPLAY=:session gedit

xpra in jsetson nano

參考 Jetson Nano平台通过Xpra运行图形程序

以下部分步驟，直接跳過避不開的錯誤

$ sudo apt-get install libx11-dev libxtst-dev libxcomposite-dev libxdamage-dev \

    libxkbfile-dev python-all-dev

$ sudo apt-get install libgtk-3-dev python3-dev python3-cairo-dev python-gi-dev cython3

$ sudo apt-get install xauth x11-xkb-utils

$ sudo apt-get install libx264-dev libvpx-dev yasm

$ sudo apt-get install libavformat-dev libavcodec-dev libswscale-dev

$ sudo apt-get install libturbojpeg-dev

$ sudo apt-get install libwebp-dev

$ sudo apt-get install uglifyjs brotli libjs-jquery libjs-jquery-ui gnome-backgrounds

$ sudo apt-get install python3-opengl python3-numpy python3-pil

$ sudo apt-get install python3-rencode python3-lz4 python3-dbus python3-cryptography \

    python3-netifaces python3-yaml

$ sudo apt-get install python3-setproctitle python3-xdg python3-pyinotify python3-opencv

$ sudo apt-get install libpam-dev quilt xserver-xorg-dev xutils-dev \

    xserver-xorg-video-dummy xvfb keyboard-configuration

$ sudo apt-get install python-kerberos python-gssapi

$ sudo apt-get install python-avahi

$ sudo apt-get install gstreamer1.0-pulseaudio gstreamer1.0-alsa \

    gstreamer1.0-plugins-base gstreamer1.0-plugins-good \

    gstreamer1.0-plugins-ugly python-gst-1.0

$ sudo apt-get install cups-filters cups-common cups-pdf python3-cups

$ sudo apt-get install openssh-client sshpass python3-paramiko

$ sudo apt-get install dh-systemd

$ wget https://www.xpra.org/src/xpra-4.0.4.tar.xz

$ tar -xf xpra-4.0.4.tar.xz

$ cd xpra-4.0.4

$ sudo ./setup.py install

$ vi setup.py

將第一行改成 python3

$ sudo ./setup.py install

$ sudo mkdir /usr/local/share/xpra/www/js/lib

$ sudo ./setup.py install

LXDE 桌面 lightdm, VNC Server, 中文輸入

$ sudo dpkg-reconfigure lightdm

$ sudo apt update

為避免 lightdm 黑畫面，無法登入，需要鎖住 systemd 不要升級

$ sudo apt-mark hold systemd

若有一天問題解決，解開封鎖

$ sudo apt-mark unhold systemd

$ sudo apt upgrade

$ sudo apt install x11vnc

$ sudo x11vnc -storepasswd

$ sudo vi /etc/systemd/system/x11vnc.service

# Description: Custom Service Unit file

# File: /etc/systemd/system/x11vnc.service

[Unit]

Description="x11vnc"

Requires=display-manager.service

After=display-manager.service

[Service]

ExecStart=/usr/bin/x11vnc -loop -nopw -xkb -repeat -noxrecord -noxfixes -noxdamage -forever -rfbport 5900 -display :0 -auth guess -rfbauth /home/nano/.vnc/passwd

ExecStop=/usr/bin/killall x11vnc

Restart=on-failure

RestartSec=2

[Install]

WantedBy=multi-user.target

$ sudo systemctl enable x11vnc.service

$ sudo systemctl start x11vnc.service

$ xrandr -q

$ sudo vi /etc/X11/xorg.conf

Section "Monitor"

    Identifier "DSI-0"

    Option "Ignore"

EndSection

Section "Screen"

    Identifier "Default Screen"

    Monitor "Configured Monitor"

    Device "Default Device"

    SubSection "Display"

        Depth 24

        Virtual 1280 800

    EndSubSection

EndSection

$ sudo apt-get install fcitx fcitx-chewing

Start up/Preferences/Language Support

Keyboard input method system: fcitx

Reboot

Start up/Preferences/Fcitx Configuration

按 + 並取消打勾 Only Show Current Language

加入 Chewing