Wednesday/Jan/20 17:24
to stop the “Desktop Sharing” panel from crashing
$ sudo vi /usr/share/glib-2.0/schemas/org.gnome.Vino.gschema.xml
Enable remote access to the desktop
If true, allows remote access to the desktop via the RFB
protocol. Users on remote machines may then connect to the
desktop using a VNC viewer.
false
$ sudo glib-compile-schemas /usr/share/glib-2.0/schemas
export DISPLAY=:0
gsettings set org.gnome.Vino enabled true
gsettings set org.gnome.Vino prompt-enabled false
gsettings set org.gnome.Vino require-encryption false
$ /usr/lib/vino/vino-server
OR
$ sudo apt-get install xrdp cmake git
https://github.com/JetsonHacksNano/CSI-Camera
sudo apt-get install v4l-utils
gst-launch-1.0 nvarguscamerasrc ! 'video/x-raw(memory:NVMM),width=3820, height=2464, framerate=21/1, format=NV12' ! nvvidconv flip-method=0 ! 'video/x-raw,width=960, height=616' ! nvvidconv ! nvegltransform ! nveglglessink -e
https://developer.nvidia.com/embedded/twodaystoademo
$ git clone https://github.com/dusty-nv/jetson-inference
$ cd jetson-inference
$ git submodule update --init
$ mkdir build
$ cd build
$ cmake ../
$ make
$ sudo make install
$ cd aarch64/bin
https://github.com/dusty-nv/jetson-inference/blob/master/docs/detectnet-console-2.md
$ ./detectnet-console ~/dog-simba.jpeg ~/out.jpeg coco-dog
https://github.com/dusty-nv/jetson-inference/blob/master/docs/detectnet-camera-2.md
$ ./detectnet-camera coco-dog
https://www.jetsonhacks.com/2019/04/25/jetson-nano-run-on-usb-drive/
https://medium.com/@jerry_liang/deploy-gpu-enabled-kubernetes-pod-on-nvidia-jetson-nano-ce738e3bcda9
https://developer.nvidia.com/embedded/community/jetson-projects
VINO : Enable VNC Server Remotely
#!/bin/sh
systemctl disable xrdp.service
mkdir /root/.config/autostart
touch /root/.config/autostart/vino-server.desktop
echo "[Desktop Entry]" >> /root/.config/autostart/vino-server.desktop
echo "Type=Application" >> /root/.config/autostart/vino-server.desktop
echo "Name=Vino VNC server" >> /root/.config/autostart/vino-server.desktop
echo "Exec=/usr/lib/vino/vino-server" >> /root/.config/autostart/vino-server.desktop
echo "NoDisplay=true" >> /root/.config/autostart/vino-server.desktop
dbus-launch gsettings set org.gnome.Vino require-encryption false
dbus-launch gsettings set org.gnome.Vino prompt-enabled false
dbus-launch gsettings set org.gnome.Vino notify-on-connect false
dbus-launch gsettings set org.gnome.Vino authentication-methods "['vnc']"
dbus-launch gsettings set org.gnome.Vino vnc-password $(echo -n "password"|base64)
dbus-launch gsettings set org.gnome.desktop.lockdown disable-user-switching true
dbus-launch gsettings set org.gnome.desktop.lockdown disable-lock-screen true
dbus-launch gsettings set org.gnome.desktop.lockdown disable-log-out true
dbus-launch gsettings set org.gnome.desktop.interface enable-animations false
dbus-launch gsettings set org.gnome.desktop.session session-name gnome
sed -i 's/# AutomaticLoginEnable = true/ AutomaticLoginEnable = true/g' /etc/gdm3/daemon.conf
sed -i 's/# AutomaticLogin = root/ AutomaticLogin = root/g' /etc/gdm3/daemon.conf
reboot
exit 0
https://github.com/dusty-nv/jetson-inference/blob/master/README.md#two-days-to-a-demo-training--inference
https://github.com/dusty-nv/jetson-inference/blob/master/docs/digits-setup.md
ubuntu-18.04.2-server-amd64.iso
https://docs.nvidia.com/sdk-manager/download-run-sdkm/index.html
scp sdkmanager_0.9.11-3405_amd64.deb htpc:
$ sudo apt install ./sdkmanager_0.9.11-3405_amd64.deb
$ sudo apt install libxss1 libnss3
https://github.com/dusty-nv/jetson-inference/blob/master/docs/digits-setup.md
https://github.com/NVIDIA/nvidia-docker#quick-start
## https://ngc.nvidia.com/catalog/containers/nvidia:digits
## https://devblogs.nvidia.com/gpu-containers-runtime/
OR manual below
https://github.com/dusty-nv/jetson-inference/blob/master/docs/digits-native.md
sudo add-apt-repository ppa:graphics-drivers
$ sudo apt install nvidia-410
$ sudo reboot
$ lsmod | grep nvidia
$ cd /usr/local/cuda/samples
$ sudo make "-j$(nproc)"
$ cd bin/x86_64/linux/release/
$ ./deviceQuery
$ ./bandwidthTest --memory=pinned
https://developer.nvidia.com/cudnn
ahlawat@htpc:~$ ls -al libcudnn7*
-rw-r--r-- 1 ahlawat ahlawat 151792832 May 19 20:12 libcudnn7_7.5.1.10-1+cuda10.0_amd64.deb
-rw-r--r-- 1 ahlawat ahlawat 140165264 May 19 20:12 libcudnn7-dev_7.5.1.10-1+cuda10.0_amd64.deb
-rw-r--r-- 1 ahlawat ahlawat 5173724 May 19 20:12 libcudnn7-doc_7.5.1.10-1+cuda10.0_amd64.deb
ahlawat@htpc:~$
$ sudo apt install libcudnn*
Install required CMake version
https://github.com/clab/dynet/issues/1457#issuecomment-423931508
NEEDS upgrading to CMake to 3.12.2
wget http://www.cmake.org/files/v3.12/cmake-3.12.2.tar.gz
tar -xvzf cmake-3.12.2.tar.gz
cd cmake
./configure
make "-j$(nproc)"
sudo make install
sudo update-alternatives --install /usr/bin/cmake cmake /usr/local/bin/cmake 1 --force
https://github.com/NVIDIA/DIGITS/blob/digits-6.0/docs/BuildDigits.md
sudo apt install --no-install-recommends git graphviz python-dev python-flask python-flaskext.wtf python-gevent python-h5py python-numpy python-pil python-pip python-scipy python-tk
Protobuf
sudo apt install autoconf automake libtool curl make g++ git python-dev python-setuptools unzip
export PROTOBUF_ROOT=~/protobuf
git clone https://github.com/google/protobuf.git $PROTOBUF_ROOT -b '3.2.x'
cd $PROTOBUF_ROOT
./autogen.sh
./configure
make "-j$(nproc)"
sudo make install
sudo ldconfig
cd python
sudo python setup.py install --cpp_implementation
Caffe
sudo apt install --no-install-recommends build-essential cmake git gfortran libatlas-base-dev libboost-filesystem-dev libboost-python-dev libboost-system-dev libboost-thread-dev libgflags-dev libgoogle-glog-dev libhdf5-serial-dev libleveldb-dev liblmdb-dev libopencv-dev libsnappy-dev python-all-dev python-dev python-h5py python-matplotlib python-numpy python-opencv python-pil python-pip python-pydot python-scipy python-skimage python-sklearn
# example location - can be customized
export CAFFE_ROOT=~/caffe
git clone https://github.com/NVIDIA/caffe.git $CAFFE_ROOT -b 'caffe-0.15'
sudo pip install -r $CAFFE_ROOT/python/requirements.txt
cd $CAFFE_ROOT
mkdir build
cd build
cmake ..
https://devtalk.nvidia.com/default/topic/1037599/jetson-tx2/installation-of-caffe-error/
nano -w ../cmake/Dependencies.cmake
1. --- list(APPEND Caffe_LINKER_LIBS ${HDF5_LIBRARIES})
2. +++ list(APPEND Caffe_LINKER_LIBS ${HDF5_LIBRARIES} ${HDF5_HL_LIBRARIES})
make -j"$(nproc)"
sudo make install
$ nano -w ~/.bashrc
export CAFFE_ROOT=/home/ahlawat/caffe
export PYTHONPATH=/home/ahlawat/caffe/python:$PYTHONPATH
Torch
https://github.com/nagadomi/waifu2x/issues/253#issuecomment-445448928
git clone https://github.com/nagadomi/distro.git ~/torch --recursive
cd ~/torch
./install-deps
./clean.sh
./update.sh
./install.sh -b
$ nano -w ~/.bashrc
export TORCH_ROOT=~/torch
export PATH=$PATH:~/torch/install/bin
$ source ~/.bashrc
Tensorflow
https://www.tensorflow.org/install/gpu
wget https://developer.nvidia.com/compute/cuda/10.0/Prod/local_installers/cuda-repo-ubuntu1804-10-0-local-10.0.130-410.48_1.0-1_amd64
sudo apt install cuda-repo-ubuntu1804-10-0-local-10.0.130-410.48_1.0-1_amd64.deb
sudo apt-key add /var/cuda-repo-10-0-local-10.0.130-410.48/7fa2af80.pub
sudo apt update
sudo apt install cuda
sudo pip install tensorflow-gpu
Finally Digits
DIGITS_ROOT=~/digits
git clone https://github.com/NVIDIA/DIGITS.git $DIGITS_ROOT
sudo pip install -r $DIGITS_ROOT/requirements.txt
sudo pip install -e $DIGITS_ROOT
### if ERROR sudo pip install numpy --upgrade
cd digits
./digits-devserver
-rw-r--r-- 1 ahlawat ahlawat 65483980 May 19 15:18 sdkmanager_0.9.11-3405_amd64.deb
-rw-r--r-- 1 ahlawat ahlawat 151792832 May 19 20:12 libcudnn7_7.5.1.10-1+cuda10.0_amd64.deb
-rw-r--r-- 1 ahlawat ahlawat 140165264 May 19 20:12 libcudnn7-dev_7.5.1.10-1+cuda10.0_amd64.deb
-rw-r--r-- 1 ahlawat ahlawat 5173724 May 19 20:12 libcudnn7-doc_7.5.1.10-1+cuda10.0_amd64.deb
-rw-rw-r-- 1 ahlawat ahlawat 1660647860 Sep 12 2018 cuda-repo-ubuntu1804-10-0-local-10.0.130-410.48_1.0-1_amd64.deb
-rw-rw-r-- 1 ahlawat ahlawat 8388114 Sep 7 2018 cmake-3.12.2.tar.gz
https://docs.nvidia.com/deeplearning/digits/digits-release-notes/rel_19-01.html#rel_19-01
The container also includes the following:
• Ubuntu 16.04 including Python 2.7
• NVIDIA CUDA 10.0.130 including CUDA® Basic Linear Algebra Subroutines library™ (cuBLAS) 10.0.130
• NVIDIA CUDA® Deep Neural Network library™ (cuDNN) 7.4.2
• NCCL 2.3.7 (optimized for NVLink™ )
• OpenMPI 3.1.3
• NVCaffe 0.17.2
• TensorFlow 1.12.0
• TensorRT 5.0.2
