Get Started

Requirements

The main requirements for sparse_caption are as follows:

  • python

  • pytorch

  • sentencepiece

  • torchvision

The full list of required packages can be found requirements_base.txt and requirements.txt.

Dependency Versions

The exact dependency versions that are tested can be found in requirements_dev_base.txt and requirements_dev.txt.

Possible {pycocotools} installation issues

  • One might run into issues related to numpy or cython when importing pycocotools.

  • To resolve it, either:

    • Install numpy and cython prior to installing pycocotools

    • Maybe try pycocotools-fix instead

  • This issue may lead to GitHub CI failing, if a different numpy version is reinstalled after pycocotools is built

Installation and Setup

Docker

Setup using Docker is the most convenient.

  1. Run docker build -t <YOUR_TAG> -f Dockerfile . to build the image.

  2. Run the command below to launch a container. Change <YOUR_DATASET_PATH> to your desired path. All dataset files will be placed inside <YOUR_DATASET_PATH>.

     docker run -it \
     --gpus all \
     --ipc=host \
     -v .:/workspace \
     -v <YOUR_DATASET_PATH>:/datasets \
     -v /tmp/.X11-unix:/tmp/.X11-unix -e DISPLAY=$DISPLAY \
     --rm <YOUR_TAG>

  3. In the container, run bash /workspace/scripts/dataset/setup.sh to perform dataset download, pre-processing, and feature extraction.

  4. Done.

Anaconda

Windows

  1. On Windows, you might need to install “Microsoft C++ Build Tools” in order to build pycocotools, by downloading from this link.

  2. Tick the options as shown: win-build-tools

  1. These commands should install the required packages:

    conda install h5py matplotlib pandas Pillow scipy seaborn tqdm
# conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch
conda install pytorch torchvision torchaudio cpuonly -c pytorch
conda install -c pytorch torchtext
conda install -c fastai sentencepiece
conda install -c conda-forge tensorboard six

# For dev, optional
conda install pytest
conda install -c conda-forge black doc8 myst-parser sphinx sphinx-autobuild sphinx_rtd_theme

  2. Install Java 8.

  3. Done.