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Data preparation
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:Date:   2019-04-03

This part introduce how to prepare and load data for the project

Generate Signals and Annotations
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    This project is the simplified version  of classification and detection 2d
    signals. So the first thing we should do is generate some 1d data to feed
    the algorithm. the **data** package is created for this purpose

Load Data from files
---------------------

    After data generation, we will get a bunch of signal files and a json file
    that contains the annotation information for each of these signals. This
    annotation file follows the convention of COCO dataset [#]_ which is widely
    used in object detection and segmentation researches.

Pytorch DataLoader
-------------------

    Pytorch is very convenient and efficient in data loading, there's a package
    called DataLoader which can help you load data from files with multi-cpu
    parallel processing. As long as you give it the proper method of loading a
    single dataframe, it will help you load the whole dataset in a very short
    period of time.


.. rubric:: References

.. [#] An Image Dataset with abandant annotations which is created for advanced
    image classification, object detection and segmentation researches. See
    COCO_

.. _COCO: http://cocodataset.org/