# audiosetdl

**Repository Path**: tunmx/audiosetdl

## Basic Information

- **Project Name**: audiosetdl
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-07-15
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

audiosetdl
================
Modules and scripts for downloading Google's
[AudioSet](https://research.google.com/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](https://conda.io/miniconda.html), 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](https://www.python.org/downloads/) 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`](https://www.ffmpeg.org/)
    * 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](http://stackoverflow.com/a/9477756/2007700) 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](https://ffmpeg.org/download.html).
  * [`sox`](http://sox.sourceforge.net/)
    * 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](https://deepmind.com/research/open-source/open-source-datasets/kinetics/). 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](https://arxiv.org/pdf/1705.08168.pdf)). 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.