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README.md

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# SoccerTrack
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.. rubric:: SoccerTrack
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[![Documentation Status](https://readthedocs.org/projects/soccertrack/badge/?version=latest)](https://soccertrack.readthedocs.io/en/latest/?badge=latest)
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SoccerTrack is a dataset for tracking soccer players and balls.
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Project Organization
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------------
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## What is SoccerTrack?
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├── LICENSE
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├── Makefile <- Makefile with commands like `make data` or `make train`
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├── README.md <- The top-level README for developers using this project.
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├── data
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│   ├── external <- Data from third party sources.
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│   ├── interim <- Intermediate data that has been transformed.
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│   ├── processed <- The final, canonical data sets for modeling.
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│   └── raw <- The original, immutable data dump.
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├── docs <- A default Sphinx project; see sphinx-doc.org for details
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├── models <- Trained and serialized models, model predictions, or model summaries
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SoccerTrack is a dataset and for tracking soccer players and balls.
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## Project Organization
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This project was based on the [cookiecutter data science template](https://drivendata.github.io/cookiecutter-data-science/), but some folders were removed. Below is a brief overview of the current project structure.
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```
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├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
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│ the creator's initials, and a short `-` delimited description, e.g.
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│ `1.0-jqp-initial-data-exploration`.
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├── docs <- Sphinx project.
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├── references <- Data dictionaries, manuals, and all other explanatory materials.
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├── notebooks <- Jupyter notebooks for example usage.
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├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
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│   └── figures <- Generated graphics and figures to be used in reporting
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├── reports <- Generated analysis including references
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├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
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│ generated with `pip freeze > requirements.txt`
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├── soccertrack <- Source code. See API Refence.
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├── setup.py <- makes project pip installable (pip install -e .) so src can be imported
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├── src <- Source code for use in this project.
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│   ├── __init__.py <- Makes src a Python module
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│ │
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│   ├── data <- Scripts to download or generate data
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│   │   └── make_dataset.py
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│ │
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│   ├── features <- Scripts to turn raw data into features for modeling
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│   │   └── build_features.py
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│ │
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│   ├── models <- Scripts to train models and then use trained models to make
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│ │ │ predictions
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│   │   ├── predict_model.py
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│   │   └── train_model.py
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│ │
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│   └── visualization <- Scripts to create exploratory and results oriented visualizations
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│   └── visualize.py
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├── data <- (Only minimum stuff on github).
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│   ├── external <- Data from third party sources.
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│   ├── interim <- Intermediate data that has been transformed.
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│   ├── processed <- The final, canonical data sets for modeling.
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│   └── raw <- The original, immutable data dump.
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└── tox.ini <- tox file with settings for running tox; see tox.readthedocs.io
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└── models <- Trained model weights (only minimum stuff on github).
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```
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--------
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<p><small>Project based on the <a target="_blank" href="https://drivendata.github.io/cookiecutter-data-science/">cookiecutter data science project template</a>. #cookiecutterdatascience</small></p>

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