.. _ref-docker-meta-information:

Meta Information
======================

.. warning::
    **The Docker Archive documentation is deprecated**

    The old workflow described in these docs will not be supported with new Lightly Worker versions above 2.6.
    Please switch to our `new documentation page <https://docs.lightly.ai/docs>`_ instead.

Depending on your current setup one of the following topics might interest you:

- | You have a dataset but want lightly to "ignore" certain Samples.
  | --> `Mask Samples`_

- | You have an existing dataset and want to add only relevant new data.
  | --> `Use Pre-Selected Samples`_

- | You have your own (weak) labels. Can lightly use this information to improve
    the selection? 
  | --> `Custom Weak Labels`_


Mask Samples
-----------------------------------

You can also add masking information to prevent certain samples from being
used to the .csv file. 

The following example shows a dataset in which the column "masked" is used
to prevent Lightly Docker from using this specific sample. In this example,
img-1.jpg is simply ignored and not considered for selection. E.g. the sample
neither gets selected nor is it affecting the selection of any other sample.

.. list-table:: masked_embeddings.csv
   :widths: 50 50 50 50 50
   :header-rows: 1

   * - filenames
     - embedding_0
     - embedding_1
     - masked
     - labels
   * - img-1.jpg
     - 0.1
     - 0.5
     - 1
     - 0
   * - img-2.jpg
     - 0.2
     - 0.2
     - 0
     - 0
   * - img-3.jpg
     - 0.1
     - 0.9
     - 0
     - 0


Use Pre-Selected Samples
-----------------------------------
Very similar to masking samples we can also pre-select specific samples. This 
can be useful for semi-automated data selection processes. A human annotator
can pre-select some of the relevant samples and let Lightly Docker add only
additional samples that are enriching the existing selection.


.. list-table:: selected_embeddings.csv
   :widths: 50 50 50 50 50
   :header-rows: 1

   * - filenames
     - embedding_0
     - embedding_1
     - selected
     - labels
   * - img-1.jpg
     - 0.1
     - 0.5
     - 0
     - 0
   * - img-2.jpg
     - 0.2
     - 0.2
     - 0
     - 0
   * - img-3.jpg
     - 0.1
     - 0.9
     - 1
     - 0

.. note:: Pre-selected samples also count for the target number of samples.
          For example, you have a dataset with 100 samples. If you have preselected
          60 samples and want to select another 10,
          you have to set the target number of samples to 70.

Custom Weak Labels
-----------------------------------

You can always add custom embeddings to the dataset by following the guide
here: :ref:`lightly-custom-labels`