audiosetdl

Modules and scripts for downloading Google's AudioSet dataset, a dataset of ~2.1 million annotated segments from YouTube videos.

Setup

• Clone the repository onto your machine.

• If you would like to get started right away with a standalone (mini)conda, environment, run setup.sh in the project directory. This will install a local Anaconda environment in <PROJECT DIR>/bin/miniconda. You can find a python executable at <PROJECT DIR>/bin/miniconda/bin/python.

  • Example: ./setup.sh

• If you would like to work with your existing working environment, it should satisfy the following requirements:

  • Python 3 and dependencies
    • On Mac, can be installed with brew install python3
    • On Ubuntu/Debian, can be installed with apt-get install python3
    • Dependencies can be installed with pip install -r <PROJECT DIR>/requirements.txt
  • ffmpeg
    • On Mac, can be installed with brew install ffmpeg
    • On Ubuntu/Debian, can be installed with apt-get install ffmpeg
      • NOTE: on versions of Ubuntu prior to 15.04 ("Vivid Vervet") ffmpeg may point to a Libav binary which is not the correct binary. If you are using anaconda, you can install the correct version by calling conda install -c conda-forge ffmpeg. Otherwise, you can obtain a static binary from the ffmpeg website.
  • sox
    • On Mac, can be installed with brew install sox
    • On Ubuntu/Debian, can be installed with apt-get install sox

Running

As a single script

• Run python download_audioset.py
  • If you are using the local standalone conda installation, either activate the conda virtual environment, or use the python executable found in the local conda installation.
  • The script will automatically download the scripts into your data directory if they do not exist and then start downloading the audio and video for all of the segments in parallel.
  • You can tweak how the downloading and processing is done. For example,
    • URL/path to dataset subset files
    • Audio/video format and codec
    • Different strategies for obtaining video
    • Number of multiprocessing pool workers used
    • Path to logging
  • Run python download_audioset.py -h for a full list of arguments

SLURM

This can be run as a batch of SLURM jobs

• Run download_subset_files.sh

  • Sets up the data directory structure in the given folder (which will be created) and downloads the AudioSet subset files to that directory. If the --split <N> option is used, the script splits the files into N parts, which will have a suffix for a job ID, e.g. eval_segments.csv.01.
  • Example: ./download_subset_files.sh --split 10 /home/user/audiosetdl/data

• Use sbatch to run the audiosetdl-job-array.s job array script

  • SLURM job array script that can be run by sbatch. Be sure to edit this to change the location of the repository ($SRCDIR) and to set the data directory ($DATADIR). Update any other configurations, such as email notifications and memory usage as it fits your use case.
  • Example: sbatch --array=1-10 audiosetdl-job-array.s

Examples

Examples can be found in the notebooks directory of this repository.

Cases where videos cannot be downloaded

• Video removed
• User account deleted
• Not available in country
• Need to sign in to view
• Video no longer exists
• Copyright takedown

Kinetics Dataset

This script can also be used to download the Kinetics dataset. Running kinetics/filter_subset.sh <filter_list> <kinetics_subset_csv> <output_file> will filter the given Kinetics subset csv file to contain only the classes in the given filter list, and put it in a format that is compatible with this script. kinetics/filter_classes.txt is provided as an example, and filters what seems to be close to what is used in Look, Listen and Learn (Arandjelović, R., Zisserman, A. 2017). Once you run it on all of the subset .csv files, you can provide those to the scripts instead of the AudioSet .csv files. Note that because the test labels are withheld, the .csv for the test set will be empty.