CS4243 (Miniconda/Miniforge Environment Initialisation)

National University of Singapore, CS4243: Computer Vision and Pattern Recognition, lab group B4.

Verify the installation

   # Activate the conda env
   conda activate CS4243

   # Run the notebooks in Chrome
   jupyter notebook

   # Run the test.ipynb

For Mac OS (intel, M1/M2) - without GPU support

   # Do all of these in the terminal

   # Conda installation
   curl https://repo.continuum.io/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -o miniconda.sh -J -L -k
   chmod +x miniconda.sh
   ./miniconda.sh

   # Clone GitHub repo
   git clone https://github.com/li-chuan-1998/CS4243.git
   cd CS4243

   # Install python libraries
   conda env create -f environment_mac_x86.yml
   
   # Activate the environment
   conda activate CS4243

   # Run the notebooks in Chrome
   jupyter notebook

This script will install the latest compatible packages. If you run into any difficulties in the installation, here is the last tested working versions (for your reference):

Python 3.9.13 | packaged by conda-forge | (main, May 27 2022, 17:01:00)
[Clang 13.0.1 ]
Tensorflow Version: 2.9.2
Keras Version: 2.9.0
scikit-learn version is 1.1.2.
pandas version is 1.4.3.
OpenCV Version: 4.6.0

For Mac OS (M1/M2) - with GPU support

   
   # Do all of these in the terminal
   # Miniforge donwload
   curl https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-MacOSX-arm64.sh -O
   chmod +x Miniforge3-MacOSX-arm64.sh
   ./Miniforge3-MacOSX-arm64.sh

   # Clone GitHub repo
   git clone https://github.com/li-chuan-1998/CS4243.git
   cd CS4243

   # Install python libraries
   conda env create -f environment_mac_arm.yml
   
   # Activate the environment
   conda activate CS4243

   # Run the notebooks in Chrome
   jupyter notebook

This script will install the latest compatible packages. If you run into any difficulties in the installation, here is the last tested working versions (for your reference):

Python 3.9.13 | packaged by conda-forge | (main, May 27 2022, 17:00:52) 
[Clang 13.0.1 ]
Tensorflow Version: 2.9.1
Keras Version: 2.9.0
scikit-learn version is 1.1.2.
pandas version is 1.4.3.
OpenCV Version: 4.6.0

For Windows - without GPU support

   # Install Anaconda 
   https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe

   # Open an Anaconda Terminal 
   Go to Application => Anaconda3 => Anaconda Cmd Prompt 

   # Install git & clone repo: Type in terminal
   conda install git 
   git clone https://github.com/li-chuan-1998/CS4243.git
   cd CS4243

   # Install python libraries
   conda env create -f environment_win10.yml
   conda activate CS4243

   # Run the notebooks in Chrome
   jupyter notebook

This script will install the latest compatible packages. If you run into any difficulties in the installation, here is the last tested working versions (for your reference):

Python 3.9.13 | packaged by conda-forge | (main, May 27 2022, 16:50:36) [MSC v.1929 64 bit (AMD64)]
Tensorflow Version: 2.9.0
Keras Version: 2.9.0
scikit-learn version is 1.1.2.
pandas version is 1.4.3.
OpenCV Version: 4.6.0

For Windows - with GPU support (tested only on RTX 30 series card)

   # Install Anaconda 
   https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe

   # Open an Anaconda Terminal 
   Go to Application => Anaconda3 => Anaconda Cmd Prompt 

   # Install git & clone repo: Type in terminal
   conda install git 
   git clone https://github.com/li-chuan-1998/CS4243.git
   cd CS4243

   # Install python libraries
   conda env create -f environment_win10_gpu.yml
   conda activate CS4243

   # Run the notebooks in Chrome
   jupyter notebook

This script will install the latest compatible packages. If you run into any difficulties in the installation, here is the last tested working versions (for your reference):

Python 3.9.13 | packaged by conda-forge | (main, May 27 2022, 16:50:36) [MSC v.1929 64 bit (AMD64)]
Tensorflow Version: 2.9.0
Keras Version: 2.9.0
scikit-learn version is 1.1.2.
pandas version is 1.4.3.
OpenCV Version: 4.6.0

Introduction Slides:

https://docs.google.com/presentation/d/1viNKVNFs1rp4xr490Az3M3J4qXoYMd_KjZ8TkVb11bU/edit#slide=id.g144a03c3c64_0_53

Lab slides:

https://docs.google.com/presentation/d/16JJ6KmhWDtNLMeveXpdKm7Vs_yKaiPNQKth9P-_BaSs/edit?usp=sharing