kwcoco.cli.coco_split module

class kwcoco.cli.coco_split.CocoSplitCLI

Bases: object

Splits a coco files into two parts base on some criteria.

Useful for generating quick and dirty train/test splits, but in general users should opt for using kwcoco subset instead to explicitly construct these splits based on domain knowledge.

name = 'split'

class CLIConfig(data=None, default=None, cmdline=False)

Bases: Config

Split a single COCO dataset into two sub-datasets.

Parameters:

• data (object) – filepath, dict, or None

• default (dict | None) – overrides the class defaults

• cmdline (bool | List[str] | str | dict) – If False, then no command line information is used. If True, then sys.argv is parsed and used. If a list of strings that used instead of sys.argv. If a string, then that is parsed using shlex and used instead

  of sys.argv.

  If a dictionary grants fine grained controls over the args passed to Config._read_argv(). Can contain:

  • strict (bool): defaults to False

  • argv (List[str]): defaults to None

  • special_options (bool): defaults to True

  • autocomplete (bool): defaults to False

  Defaults to False.

Note

Avoid setting cmdline parameter here. Instead prefer to use the cli classmethod to create a command line aware config instance..

default = {'balance_categories': <Value(True)>, 'compress': <Value('auto')>, 'dst1': <Value('split1.kwcoco.json')>, 'dst2': <Value('split2.kwcoco.json')>, 'factor': <Value(3)>, 'num_write': <Value(1)>, 'rng': <Value(None)>, 'splitter': <Value('auto')>, 'src': <Value(None)>}

classmethod main(cmdline=True, **kw)

Example

>>> from kwcoco.cli.coco_split import *  # NOQA
>>> import ubelt as ub
>>> dpath = ub.Path.appdir('kwcoco/tests/cli/split').ensuredir()
>>> kw = {'src': 'special:vidshapes8',
>>>       'dst1': dpath / 'train.json',
>>>       'dst2': dpath / 'test.json'}
>>> cmdline = False
>>> cls = CocoSplitCLI
>>> cls.main(cmdline, **kw)

kwcoco.cli.coco_split._CLI

alias of CocoSplitCLI