This repo contains lab materials for CS4243 - Computer Vision and Pattern Recognition in AY22/23 Sem 1. I will be updating the link of my slides and other related materials here.

• Lab Contents
• Environment Setup
  • For Linux & OS X (Intel)
  • For OS X (Apple Silicon)
  • For Windows

• Week 3 Lab 1
• Week 4 Lab 2
• Week 5 Lab 3
• Week 6 Lab 4
• Week 7 Lab 5
• Week 8 Lab 6
• Week 9 Lab 7

• Execute the following commands in terminal

1. Install Miniconda3

   # For Linux
   curl https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -o miniconda.sh -J -L -k
   # For OS X (x86_64)
   curl https://repo.continuum.io/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -o miniconda.sh -J -L -k
   chmod +x miniconda.sh
   ./miniconda.sh
   source ~/.bashrc # source ~/.zshrc if you are using zsh

2. Install the Python libraries

   # Clone this repo
   git clone https://github.com/ljhgabe/CS4243-Lab-Materials.git
   cd CS4243-Lab-Materials
   
   # Install python libraries
   conda create -n tf python=3.9
   conda activate tf
   pip install -r requirements.txt

3. Run Jupyter Notebook

   jupyter notebook

• I found previous commands did not work for installing tensorflow on Mac with Apple Silicon. Here is a solution that works on my Mac M1. Shout out to Better Data Science.

1. Install Homebrew:

   /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

2. Install Xcode build tools (if you don't have it yet):

   xcode-select --install

3. Download and install Miniforge from the following URL:
   • https://github.com/conda-forge/miniforge
   • Download the ARM64 version
   • Now you have a file called Miniforge3-MacOSX-arm64.sh

   chmod +x Miniforge3-MacOSX-arm64.sh
   ./Miniforge3-MacOSX-arm64.sh
   source ~/.bashrc # source ~/.zshrc if you are using zsh

4. Create a new virtual environment and activate it:

   # Clone this repo
   git clone https://github.com/ljhgabe/CS4243-Lab-Materials.git
   cd CS4243-Lab-Materials
   
   conda create -n tf python=3.9
   conda activate tf

5. Install TensorFlow and other libraries:

   conda install -c apple tensorflow-deps
   pip install -r requirements_arm.txt
   conda install jupyter

6. Run Jupyter Notebook

   jupyter notebook

1. Install Anaconda 3

   • https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe

2. Go to Application -> Anaconda3 -> Anaconda Prompt

3. Install git (if you don't have it yet)

   conda install git
   git clone https://github.com/ljhgabe/CS4243-Lab-Materials.git
   cd CS4243-Lab-Materials

4. Create your conda environment

    conda create -n tf python=3.9
    conda activate tf

5. Install TensorFlow and other libraries:

   pip install -r requirements.txt

6. Run Jupyter Notebook

   jupyter notebook