-
Machine Learning Basics
Linear Regression
How to Minimize Cost
Multi-Variable Linear Regression
Logistic (Regression) Classification
Softmax Classification: Multinomial Classification
Application & Tips: Learning Rate, Data Preprocessing, Overfitting
Deep Neural Nets for Everyone
Neural Nets(NN) for XOR
ReLU: Better Non-Linearity
CNN Introduction
RNN
How to install DeepStream SDK 1.5
Note: DeepStream SDK is based on the following libraries, please download them before building.
Packages | Version |
---|---|
Ubuntu | 16.04 LTS (with GCC 5.4) |
Display driver | 384 |
CUDA | 9.0 |
cuDNN | 7.0.4 |
VideoSDK | 8.0.14 |
TensorRT | 3.0 |
CUDA Toolkit 9.0 RUNFILE Packages (Recommended)
sudo sh cuda_9.0.176_384.81_linux.run
Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 384.81?
(y)es/(n)o/(q)uit: n
OR
sudo cuda_9.0.176_384.81_linux.run -silent -driver
CUDA Toolkit 9.0 DEB Packages (Not Recommended)
sudo dpkg -i cuda-repo-ubuntu1604_9.0.176-1_amd64.deb
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub
sudo apt-get update
sudo apt-get install cuda
To uninstall the CUDA Toolkit, run the uninstall script in /usr/local/cuda-9.0/bin
cuDNN v7.0.4 for CUDA 9.0 Packages
tar -xzvf cudnn-9.0-linux-x64-v7.tgz
sudo cp cuda/include/cudnn.h /usr/local/cuda/include
sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64
sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*
TensorRT 3.0.2 for Ubuntu 16.04 and CUDA 9.0 TAR packages (Recommended)
tar xzvf TensorRT-3.0.2.Ubuntu-16.04.3.x86_64.cuda-9.0.cudnn7.0.tar.gz
sudo mv TensorRT-3.0.2 /usr/local
TensorRT 3.0.2 for Ubuntu 16.04 and CUDA 9.0 DEB packages (Not Recommended)
sudo dpkg -i nv-tensorrt-repo-ubuntu1604-ga-cuda9.0-trt3.0.2-20180108_1-1_amd64.deb
sudo apt-key add /var/nv-tensorrt-repo-ga-cuda9.0-trt3.0.2-20180108/7fa2af80.pub
sudo apt-get update
sudo apt-get install tensorrt
Edit .bashrc
gedit ~/.bashrc
export CUDA=cuda-9.0
export TENSORRT=/usr/local/TensorRT-3.0.2
export PATH=/usr/local/${CUDA}/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/${CUDA}/lib64:${TENSORRT}/lib${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
source ~/.bashrc
Python Installation
sudo apt install python3-pip
python3 -m pip install --upgrade pip
cd ${TENSORRT}/python
sudo python3 -m pip install tensorrt-3.0.2-cp35-cp35m-linux_x86_64.whl
cd ${TENSORRT}/uff
sudo python3 -m pip install uff-0.2.0-py2.py3-none-any.whl
Update the custom_plugins example to point to the location where the tar package was installed into. For example, in the <PYTHON_INSTALL_PATH>/tensorrt/examples/custom_layers/tensorrtplugins/setup.py file, change the following:
- Change TENSORRT_INC_DIR to point to the <TAR_INSTALL_ROOT>/include directory.
- Change TENSORRT_LIB_DIR to point to <TAR_INSTALL_ROOT>/lib directory.
Tensorflow Installation (Optional)
sudo python3 -m pip install jupyter
sudo python3 -m pip install tensorflow-gpu
DeepStream SDK Pre-Installation
sudo apt-get update
sudo apt-get install build-essential
sudo apt-get install ffmpeg
sudo apt-get install libxmu-dev
sudo apt-get install libgl1-mesa-dev
sudo apt-get install libglu1-mesa-dev
sudo apt-get install freeglut3-dev
sudo apt-get install libopencv-dev python-opencv
GLEW
make all
sudo make install
Edit deepstream/makes/defines.inc
TENSORRT_INC_PATH = ${TENSORRT}/include
TENSORRT_LIB_PATH = ${TENSORRT}/lib
VIDEOSDK_INSTALL_PATH = /home/${username}/cuda-workspace/Video_Codec_SDK_8.0.14
- Previous
- Next