kwcoco.compat_dataset

A wrapper around the basic kwcoco dataset with a pycocotools API.

We do not recommend using this API because it has some idiosyncrasies, where names can be missleading and APIs are not always clear / efficient: e.g.

1. catToImgs returns integer image ids but imgToAnns returns annotation dictionaries.

2. showAnns takes a dictionary list as an argument instead of an integer list

The cool thing is that this extends the kwcoco API so you can drop this for compatibility with the old API, but you still get access to all of the kwcoco API including dynamic addition / removal of categories / annotations / images.

Module Contents

Classes

COCO	A wrapper around the basic kwcoco dataset with a pycocotools API.

class kwcoco.compat_dataset.COCO(annotation_file=None, **kw)

Bases: kwcoco.coco_dataset.CocoDataset

A wrapper around the basic kwcoco dataset with a pycocotools API.

Example

>>> from kwcoco.compat_dataset import *  # NOQA
>>> import kwcoco
>>> basic = kwcoco.CocoDataset.demo('shapes8')
>>> self = COCO(basic.dataset)
>>> self.info()
>>> print('self.imgToAnns = {!r}'.format(self.imgToAnns[1]))
>>> print('self.catToImgs = {!r}'.format(self.catToImgs))

createIndex(self)

info(self)

Print information about the annotation file. :return:

property imgToAnns(self)

property catToImgs(self)

unlike the name implies, this actually goes from category to image ids Name retained for backward compatibility

getAnnIds(self, imgIds=[], catIds=[], areaRng=[], iscrowd=None)

Get ann ids that satisfy given filter conditions. default skips that filter :param imgIds (int array) : get anns for given imgs

catIds (int array) : get anns for given cats areaRng (float array) : get anns for given area range (e.g. [0 inf]) iscrowd (boolean) : get anns for given crowd label (False or True)

Returns

ids (int array) : integer array of ann ids

Example

>>> from kwcoco.compat_dataset import *  # NOQA
>>> import kwcoco
>>> self = COCO(kwcoco.CocoDataset.demo('shapes8').dataset)
>>> self.getAnnIds()
>>> self.getAnnIds(imgIds=1)
>>> self.getAnnIds(imgIds=[1])
>>> self.getAnnIds(catIds=[3])

getCatIds(self, catNms=[], supNms=[], catIds=[])

filtering parameters. default skips that filter. :param catNms (str array) : get cats for given cat names :param supNms (str array) : get cats for given supercategory names :param catIds (int array) : get cats for given cat ids :return: ids (int array) : integer array of cat ids

Example

>>> from kwcoco.compat_dataset import *  # NOQA
>>> import kwcoco
>>> self = COCO(kwcoco.CocoDataset.demo('shapes8').dataset)
>>> self.getCatIds()
>>> self.getCatIds(catNms=['superstar'])
>>> self.getCatIds(supNms=['raster'])
>>> self.getCatIds(catIds=[3])

getImgIds(self, imgIds=[], catIds=[])

Get img ids that satisfy given filter conditions. :param imgIds (int array) : get imgs for given ids :param catIds (int array) : get imgs with all given cats :return: ids (int array) : integer array of img ids

Example

>>> from kwcoco.compat_dataset import *  # NOQA
>>> import kwcoco
>>> self = COCO(kwcoco.CocoDataset.demo('shapes8').dataset)
>>> self.getImgIds(imgIds=[1, 2])
>>> self.getImgIds(catIds=[3, 6, 7])
>>> self.getImgIds(catIds=[3, 6, 7], imgIds=[1, 2])

loadAnns(self, ids=[])

Load anns with the specified ids. :param ids (int array) : integer ids specifying anns :return: anns (object array) : loaded ann objects

loadCats(self, ids=[])

Load cats with the specified ids. :param ids (int array) : integer ids specifying cats :return: cats (object array) : loaded cat objects

loadImgs(self, ids=[])

Load anns with the specified ids. :param ids (int array) : integer ids specifying img :return: imgs (object array) : loaded img objects

showAnns(self, anns, draw_bbox=False)

Display the specified annotations. :param anns (array of object): annotations to display :return: None

loadRes(self, resFile)

Load result file and return a result api object. :param resFile (str) : file name of result file :return: res (obj) : result api object

download(self, tarDir=None, imgIds=[])

Download COCO images from mscoco.org server. :param tarDir (str): COCO results directory name

imgIds (list): images to be downloaded

Returns

loadNumpyAnnotations(self, data)

Convert result data from a numpy array [Nx7] where each row contains {imageID,x1,y1,w,h,score,class} :param data (numpy.ndarray) :return: annotations (python nested list)

annToRLE(self, ann)

Convert annotation which can be polygons, uncompressed RLE to RLE. :return: binary mask (numpy 2D array)

Note

• This requires the C-extensions for kwimage to be installed due to the need to interface with the bytes RLE format.

Example

>>> from kwcoco.compat_dataset import *  # NOQA
>>> import kwcoco
>>> self = COCO(kwcoco.CocoDataset.demo('shapes8').dataset)
>>> try:
>>>     rle = self.annToRLE(self.anns[1])
>>> except NotImplementedError:
>>>     import pytest
>>>     pytest.skip('missing kwimage c-extensions')
>>> else:
>>>     assert len(rle['counts']) > 2
>>> # xdoctest: +REQUIRES(module:pycocotools)
>>> self.conform(legacy=True)
>>> orig = self._aspycoco().annToRLE(self.anns[1])

annToMask(self, ann)

Convert annotation which can be polygons, uncompressed RLE, or RLE to binary mask.

Returns

binary mask (numpy 2D array)

Note

The mask is returned as a fortran (F-style) array with the same dimensions as the parent image.