Setting Up AI Computer   

cat /etc/nv_tegra_release

dmesg |grep SPI

      "32.4.3") JETSON_JETPACK="4.4" ;;

     "32.4.2") JETSON_JETPACK="4.4 DP" ;;

     "32.3.1") JETSON_JETPACK="4.3" ;;

     "32.2.3") JETSON_JETPACK="4.2.3" ;;

     "32.2.1") JETSON_JETPACK="4.2.2" ;;

     "32.2.0" | "32.2") JETSON_JETPACK="4.2.1" ;;

     "32.1.0" | "32.1") JETSON_JETPACK="4.2" ;;

     "31.1.0" | "31.1") JETSON_JETPACK="4.1.1" ;;

     "31.0.2") JETSON_JETPACK="4.1" ;;

     "31.0.1") JETSON_JETPACK="4.0" ;;

     "28.2.1") JETSON_JETPACK="3.3 | 3.2.1" ;;

     "28.2.0" | "28.2") JETSON_JETPACK="3.2" ;;

     "28.1.0" | "28.1") JETSON_JETPACK="3.1" ;;

     "27.1.0" | "27.1") JETSON_JETPACK="3.0" ;;

     "24.2.1") JETSON_JETPACK="3.0 | 2.3.1" ;;

     "24.2.0" | "24.2") JETSON_JETPACK="2.3" ;;

     "24.1.0" | "24.1") JETSON_JETPACK="2.2.1 | 2.2" ;;

     "23.2.0" | "23.2") JETSON_JETPACK="2.1" ;;

     "23.1.0" | "23.1") JETSON_JETPACK="2.0" ;;

     "21.5.0" | "21.5") JETSON_JETPACK="2.3.1 | 2.3" ;;

     "21.4.0" | "21.4") JETSON_JETPACK="2.2 | 2.1 | 2.0 | 1.2 DP" ;;

     "21.3.0" | "21.3") JETSON_JETPACK="1.1 DP" ;;

     "21.2.0" | "21.2") JETSON_JETPACK="1.0 DP" ;;

     *) JETSON_JETPACK="UNKNOWN" ;;

JETSON_JETPACK="4.4" ;;  and above… 

pip3 install numpy ( use this command to install numpy)

There are a few more packages and development tools to install to ensure that we have a robust set-up for our programming environment:

sudo apt-get install build-essential libssl-dev libffi-dev python-dev

Once Python is set up, and pip and other tools are installed, we can set up a virtual environment for our development projects.

sudo apt-get install -y python3-venv

venv module, part of the standard Python 3 library, so that we can create virtual environments

mkdir environments

cd environments

python3 -m venv jk_env // jk_env is created  ,u can give your name 

ls_env

source environments/jk_env/bin/activate

Use virtual environments: use virtual environments for your Python programming needs. You might be familiar with conda, but unfortunately it can’t be installed on ARM. Instead you can use the Python3-venv package that can be installed with:

///DL SDK doc from NVIDIA

https://docs.nvidia.com/deeplearning/sdk/tensorrt-developer-guide/index.html#import_model_python 

// hello world in TF RT

https://docs.nvidia.com/deeplearning/sdk/tensorrt-sample-support-guide/index.html#end_to_end_tensorflow_mnist 

Python Matrices and NumPy Arrays

https://www.programiz.com/python-programming/matrix 

https://stackoverflow.com/questions/28831854/how-do-i-add-python3-kernel-to-jupyter-ipython 

sudo pip3 install ipython>=5.0.0

:~/tmp/pub$ pip3 --version

pip 19.1.1 from /usr/local/lib/python3.4/dist-packages/pip (python 3.4)

/tmp/pub$ pip2 --version

pip 19.1.1 from /usr/local/lib/python2.7/dist-packages/pip (python 2.7)

//following worked well ,,,installed 3.5 version with ease

sudo apt-get install libssl-dev openssl

wget https://www.python.org/ftp/python/3.5.0/Python-3.5.0.tgz 

sudo tar -xzvf Python-3.5.0.tgz

cd Python-3.5.0

./configure

sudo make

sudo make install

//following worked well

jupyter-notebook

//////////// issue on TensorRT

https://devtalk.nvidia.com/default/board/360/container-tensorrt/

https://devtalk.nvidia.com/default/board/304/

//download tensorRT

https://developer.nvidia.com/tensorrt

TensorRT 5.0 Usage Survey

https://developer.nvidia.com/embedded/downloads#?search=Jetson%20Nano

TensorRT 5.1 GA ( general availability RC is release candidate)

Tar File Install Packages For Linux Power

TensorRT-5.1.3.6 for Ubuntu

installation of tensorrT

https://docs.nvidia.com/deeplearning/sdk/tensorrt-install-guide/index.html 

//model

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:<eg:TensorRT-5.1.x.x/lib>

//wrong

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:</home/tmp/jetson/TensorRT-5.1.3.6/lib>

//correct one

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/tmp/jetson/TensorRT-5.1.3.6/lib

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/tmp/jetson/TensorRT-5.1.2.2/lib

sudo pip3 install tensorrt-5.1.3.6-cp35-none-linux_ppc64le.whl

sudo pip3 install tensorrt-5.1.2.2-cp35-none-linux_x86_64.whl

sudo pip3 install uff-0.6.3-py2.py3-none-any.whl

//issue

sudo pip3 install graphsurgeon-0.4.1-py2.py3-none-any.whl

//working

sudo pip3 install graphsurgeon-0.4.0-py2.py3-none-any.whl

///CUDA

https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1404&target_type=clusterlocal 

https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1404&target_type=runfilelocal 

// upgrade from 3.4 to 3.5

sudo apt-get install python3.5

python3 --version

I'm getting

Python 3.4.3

didn't do anything wrong and things are not working as intended. Even after you have installed Python 3.6 from a PPA, the /usr/bin/python3 symlink on your Ubuntu 14.04 system still points to /usr/bin/python3.4, not /usr/bin/python3.6. Therefore, to invoke the Python 3.6 interpreter, you explicitly run python3.6.

how to install jupyter notebook in ubuntu 14.04

Python Prerequisites

sudo apt install python3-pip

sudo apt install ipython3

pip3 install jupyter

Downloading ipywidgets-7.4.2-py2.py3-none-any.whl (111kB): 111kB downloaded

Cleaning up...

Exception:

Traceback (most recent call last):

pip --version

pip 1.5.4 from /usr/lib/python2.7/dist-packages (python 2.7)

sudo pip install --upgrade pip

Not uninstalling pip at /usr/lib/python2.7/dist-packages, owned by OS

//following worked

sudo -H pip install --upgrade pip

sudo pip3 install --upgrade pip

// appear to be worked partly

sudo pip3 install --upgrade setuptools

/// again issues

pip3 install jupyter

Setting up Jupyter with Python 3 on Ubuntu

https://datawookie.netlify.com/blog/2017/06/setting-up-jupyter-with-python-3-on-ubuntu/

// tried with sudo ,..but still not ok

Installing  TensorFlow 

sudo pip3 install jupyter

...You are using pip version 10.0.1, however version 19.1.1 is available.

You should consider upgrading via the 'pip install --upgrade pip' command

sudo -H pip install --upgrade pip --user

How can I uninstall python 2.7 and reinstall 3.5 in Ubuntu 14.04?

sudo apt-get install python3-notebook jupyter-core python-ipykernel

https://askubuntu.com/questions/847263/install-jupyter-notebook-for-python-2-7

///windows file

Found Windows Boot Manager on /dev/sda1@/EFI/Microsoft/Boot/bootmgfw.efi

Adding boot menu entry for EFI firmware configuration

sudo apt-get update

sudo apt-get autoremove

sudo apt-get -y install python3-pip python3-dev

sudo -H pip3 install --upgrade pip

sudo apt-get -y install ipython3 ipython3-notebook

sudo -H pip3 install jupyter

sudo -H pip3 install jupyter --user

Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.

https://github.com/jupyter/notebook/issues/2786

command not found: 'jupyter

/usr/local/bin/pip3

/usr/local/bin/jupyter

export PATH=$PATH:~/.local/bin

File "/tmp/pip-install-Ej0KVF/tornado/setup.py", line 146, in <module>

raise ImportError("Tornado requires an up-to-date SSL module. This means "

sudo pip install 'Tornado>=4.0.0,<5.0.0'

matplotlib 1.3.1 requires nose, which is not installed.

https://github.com/googlesamples/assistant-sdk-python/issues/264

Try using

sudo easy_install nose

sudo easy_install tornado

sudo pip install 'Tornado>=4.0.0,<5.0.0'

sudo -H pip install jupyter

https://github.com/Tony607/tf_jetson_nano 

Run Keras/Tensorflow model on Jetson Nano

https://ehmatthes.github.io/pcc/chapter_01/osx_setup.html 

To be able to run jupyter notebook from terminal, you need to make sure that ~/.local/bin is in your path.

Do this by running export PATH=$PATH:~/.local/bin for your current session, or adding that line to the end of ~/.bashrc to make your changes last for future sessions (e.g. by using nano ~/.bashrc). If you edit ~/.bashrc you will need to log out and log back in to make see your changes take effect

jupyter notebook ///////////// now it worked .....// 11.07 PM

https://github.com/Tony607/tf_jetson_nano

Run Keras/Tensorflow model on Jetson Nano

git clone https://github.com/Tony607/tf_jetson_nano

pip3 install -r requirements.txt

git clone https://github.com/Tony607/tf_jetson_nano.git

pip install numpy --upgrade

sudo pip install numpy --upgrade --ignore-installed

kernel2 or kerl 3 issue in Jypeter notebook

https://stackoverflow.com/questions/30492623/using-both-python-2-x-and-python-3-x-in-ipython-notebook 

sudo apt-get install python-dev python3-dev python-pip python3-pip

sudo python -m pip install virtualenv --user

///worked

sudo apt install python-pip

sudo pip install absl-py

sudo pip install gast

sudo pip install grpcio

sudo pip install mock

sudo pip install tensorboard>=1.8.0

pip install numpy --upgrade

///DL SDK doc from NVIDIA

https://docs.nvidia.com/deeplearning/sdk/tensorrt-developer-guide/index.html#import_model_python

// hello world in TF RT

https://docs.nvidia.com/deeplearning/sdk/tensorrt-sample-support-guide/index.html#end_to_end_tensorflow_mnist

Python Matrices and NumPy Arrays

https://www.programiz.com/python-programming/matrix

https://stackoverflow.com/questions/28831854/how-do-i-add-python3-kernel-to-jupyter-ipython 

sudo pip3 install ipython>=5.0.0

/tmp/pub$ pip3 --version

pip 19.1.1 from /usr/local/lib/python3.4/dist-packages/pip (python 3.4)

/tmp/pub$ pip2 --version

pip 19.1.1 from /usr/local/lib/python2.7/dist-packages/pip (python 2.7)

//following worked well ,,,installed 3.5 version with ease

sudo apt-get install libssl-dev openssl

wget https://www.python.org/ftp/python/3.5.0/Python-3.5.0.tgz

sudo tar -xzvf Python-3.5.0.tgz

cd Python-3.5.0

./configure

sudo make

sudo make install

//following worked well

jupyter-notebook

//////////// issue on TensorRT

https://devtalk.nvidia.com/default/board/360/container-tensorrt/

https://devtalk.nvidia.com/default/board/304/

//download tensorRT

https://developer.nvidia.com/tensorrt

TensorRT 5.0 Usage Survey

https://developer.nvidia.com/embedded/downloads#?search=Jetson%20Nano 

TensorRT 5.1 GA ( general availability RC is release candidate)

Tar File Install Packages For Linux Power

TensorRT-5.1.3.6 for Ubuntu

installation of tensorrT

https://docs.nvidia.com/deeplearning/sdk/tensorrt-install-guide/index.html

//model

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:<eg:TensorRT-5.1.x.x/lib>

//wrong

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:</home/tmp/jetson/TensorRT-5.1.3.6/lib>

//correct one

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/tmp/jetson/TensorRT-5.1.3.6/lib

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/tmp/jetson/TensorRT-5.1.2.2/lib

sudo pip3 install tensorrt-5.1.3.6-cp35-none-linux_ppc64le.whl

sudo pip3 install tensorrt-5.1.2.2-cp35-none-linux_x86_64.whl

sudo pip3 install uff-0.6.3-py2.py3-none-any.whl

//issue

sudo pip3 install graphsurgeon-0.4.1-py2.py3-none-any.whl

//working

sudo pip3 install graphsurgeon-0.4.0-py2.py3-none-any.whl

$ which jupyter

/usr/local/bin/jupyter

TensorRT, OpenCV

TensorFlow is one of the most popular deep learning frameworks today. NVIDIA® TensorRT™ is a deep learning platform that optimizes neural network models and speeds up inference across all kinds of GPU-accelerated platforms running in data centers, embedded and automotive devices. TensorFlow integrates nicely with TensorRT, which seems a natural fit, particularly as NVIDIA provides platforms well-suited to accelerate TensorFlow. This enables TensorFlow users to have extremely high inference performance and a near transparent workflow when using TensorRT.

Adding TensorRT to the TensorFlow inference workflow involves an additional step, as shown in Figure 3. In this step (highlighted in green), TensorRT builds an optimized inference graph from a frozen TensorFlow graph.

Throughout this article, we will use python 3. Let’s install TensorFlow and TensorRT on the device. You can find good instructions in the NVIDIA TensorFlow/TensorRT Models on Jetson repository. But first, you should install python3-dev and libfreetype6-dev packages. They may solve some problems with matplotlib installation:

sudo apt-get update

sudo apt-get upgrade

sudo apt-get install libfreetype6-dev python3-dev

Also, we recommend installing the last version of TensorFlow, currently it is 1.10.1.

After installing TensorRT we had a problem with the jupyter example. Since the example uses a ssd_inception_v2 model which tries to allocate a lot of GPU memory, the session run process gets killed by the system. To resolve this problem we changed the model to SSD Lite MobileNet v2 from TensorFlow Model ZOO. The model zoo is Google’s collection of pre-trained object detection models that have various levels of processing speed and accuracy.