System Setup for local machines:

This is the system setup instructions for CMSC733 class for local machines. Feel free to use a Virtual Machine on your system if you don’t an Ubuntu machine. We STRONGLY recommend Virtual Box as a virtual machine monitor. Please note that while this tutorial may be slightly outdated, you can install newer versions, but the procedure remains the same.

1. Install OpenCV-3.4:

Due to certain issues in opencv-4, we have decided to revert back to opencv3 for this course. After the latest release, the ‘right’ way to install opencv-3 is to build from source. Feel free to follow the official documentation for version 3.4.0 if you want or follow the given steps:

sudo apt update
sudo apt upgrade

Go to this github page and download the two shell scripts:

Do:

sudo chmod u+x install_opencv3-Part1.sh install_opencv3-Part2.sh
./install_opencv3-Part1.sh

If it outputs an error, please read the lines 33-36 from install_opencv3-Part1.sh to tackle the problem (hopefully). If it works, perfectly fine, do:

install_opencv3-Part2.sh

Now, check the OpenCV version by opening python console and do the following:

import cv2
cv2.__version__

It must be 3.4.0.

Please feel free to use any other sources for installation and try to avoid virtualenv and conda if possible.

2. Python Dependencies:

sudo apt install python-numpy python-scipy python-scikits-learn python-matplotlib python-skimage python-pil

sudo -H pip install termcolor tqdm

3. TensorFlow (CPU version)

If you have GPU’s that don’t support NVIDIA CUDA, install the CPU version for tensorflow

sudo -H pip install tensorflow

4. TensorFlow (GPU version)

If you have NVIDIA 970 or later, using gpu version of tensorflow is recommended.

A. Install NVIDIA drivers, if you don’t have one.

sudo apt install nvidia-smi nvidia-384

— or —

sudo apt install nvidia-smi nvidia-396


B. Download and install CUDA-9.0 : (File size is 1.1GB)

cd ~/Downloads/
wget https://developer.nvidia.com/compute/cuda/9.0/Prod/local_installers/cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64-deb
mv -i cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64-deb cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64.deb 
sudo apt-key add /var/cuda-repo-9-0-local/7fa2af80.pub
sudo dpkg -i cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64.deb 
sudo apt-get update
sudo apt-get install cuda
sudo apt install nvidia-cuda-toolkit
nvcc --version
  • If you see Cuda compilation tools version (nvcc --version) as 7.5 instead of cuda-9.0, do:
echo 'export PATH=/usr/local/cuda-9.0/bin${PATH:+:${PATH}}' >> ~/.bashrc
source ~/.bashrc
  • Check nvcc --version again. It should show you cuda-9.0.

C. CuDNN Installation:

  • Download cudnn-7.4 (for cuda-9.0 ) here. The file is 347 MB.
# install cuDNN v7.4
CUDNN_TAR_FILE="cudnn-9.0-linux-x64-v7.4.1.5.tgz"
tar -xzvf ${CUDNN_TAR_FILE}
sudo cp -P cuda/include/cudnn.h /usr/local/cuda-9.0/include
sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda-9.0/lib64/
sudo chmod a+r /usr/local/cuda-9.0/lib64/libcudnn*

# set environment variables
export PATH=/usr/local/cuda-9.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH

D. TensorFlow GPU package installation:

sudo -H pip install tensorflow-gpu

Google Cloud Platform Setup

(Coming Soon)