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UPF - Face and Gesture Analysis: practices repository

Installation instructions

conda

Before proceeding with the installation, please check the environment.yml file. It is now configured to install the CPU version of pytorch, since running inference does not require a GPU. Please uncomment the appropriate lines if you want GPU support. To replicate the development environment simply run the following commands (you can change the name of the environment from face_analysis to something else):

conda env create --name face_analysis --file environment.yml &&
conda activate face_analysis &&
conda config --env --add channels conda-forge &&
conda config --env --add channels pytorch &&
# conda config --env --add channels nvidia # Only needed if you want GPU support

pip

Alternatively, we also provide a requirements.txt file that can be used with pip. Please take into account that the project has been developed with python 3.11. We have not tested if the code works with other versions of python. To replicate the development environment simply run the following commands:

python3 -m venv .venv &&
source .venv/bin/activate &&
python -m pip install -r requirements.txt
Lab Week Weight
1-2 1-2 15%
3 3-4 15%
4 5-6 15%
Competitive challenge 7-9 25% (grade > 5 required)

Compiling the TEX reports using latexmk

To compile the TEX file under the report folder of the project, you can use latexmk. latexmk is a command-line tool that automates the process of compiling LaTeX documents.

Follow the steps below to compile the TEX file:

  1. Open a terminal or command prompt.
  2. Navigate to the report folder of the project using the cd command:
    cd Lab2/report
  3. Run the following command to compile the TEX file using latexmk:
    latexmk -pdf main.tex
    This command will compile the main.tex file and generate a PDF output.

NOTE: latexmkrc is a configuration file used by latexmk. We have downloaded the one provided by Overleaf to have a consistent output.

Having a live preview of the pdf file

If you want Latexmk to continuously check all input files for changes and re-compile the whole thing if needed and always display the result, type

latexmk -pdf -pvc main.tex

Then, whenever you change something in any of your source files and save your changes, the preview is automagically updated. But: This doesn't work with all viewers, especially not with Adobe Reader. For more information about this feature check the official documentation.

Cleaning temporary files

To clean temporary files generated during the compilation process, you can use the latexmk command with the -c option.

latexmk -c

This command will remove all the temporary files generated during the compilation process.

Installation requirements

  • For Linux OSes: To use latexmk on Linux, you need to have two main dependencies installed: texlive and latexmk. texlive is a comprehensive distribution of LaTeX, which includes all the necessary packages and tools for compiling LaTeX documents. latexmk is a command-line tool that automates the compilation process.

    To install texlive and latexmk on Linux, you can use the package manager specific to your Linux distribution. For example, on Ubuntu or Debian-based systems, you can use the following command:

    sudo apt install texlive latexmk

    This command will install texlive and latexmk along with their dependencies.

  • For macOS: On macOS, you need to have MacTeX installed, which is a distribution of LaTeX specifically designed for macOS. MacTeX includes all the necessary packages and tools, including latexmk, for compiling LaTeX documents.

    To install MacTeX on macOS, you can download the MacTeX distribution from the official website (https://www.tug.org/mactex/) and follow the installation instructions provided. Once MacTeX is installed, you will have latexmk available for compiling your TEX files, so you don't need to install it separately.

With the required dependencies installed, you can follow the steps mentioned in the README to compile your TEX file using latexmk.

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Four university projects of increasing complexity for building an automatic face recognition model.

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