CS4243_2022
Computer Vision and Pattern Recognition, NUS CS4243, 2022
Cloud Machine #1 : Google Colab (Free GPU)
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Follow this Notebook installation :
https://colab.research.google.com/github/xbresson/CS4243_2022/blob/master/codes/installation/installation.ipynb -
Open your Google Drive :
https://www.google.com/drive -
Open in Google Drive Folder 'CS4243_2022' and go to Folder 'CS4243_2022/codes/'
Select the notebook 'file.ipynb' and open it with Google Colab using Control Click + Open With Colaboratory
Cloud Machine #2 : Binder (No GPU)
- Simply click here
Local Installation for OSX & Linux
- Open a Terminal and type
# Conda installation
curl https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -o miniconda.sh -J -L -k # Linux
curl https://repo.continuum.io/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -o miniconda.sh -J -L -k # OSX
chmod +x miniconda.sh
./miniconda.sh
source ~/.bashrc
# Clone GitHub repo
git clone https://github.com/xbresson/CS4243_2022.git
cd CS4243_2022
# Install python libraries
conda env create -f environment.yml
source activate deeplearn_course
# Run the notebooks in Chrome
jupyter notebookLocal Installation for Windows
# Install Anaconda
https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe
# Open an Anaconda Terminal
Go to Application => Anaconda3 => Anaconda Prompt
# Install git : Type in terminal
conda install git
# Clone GitHub repo
git clone https://github.com/xbresson/CS4243_2022.git
cd CS4243_2022
# Install python libraries
conda env create -f environment_windows.yml
conda activate deeplearn_course
# Run the notebooks in Chrome
jupyter notebook