kwcoco.coco_objects1d module¶

Vectorized ORM-like objects used in conjunction with coco_dataset

class kwcoco.coco_objects1d.ObjectList1D(ids, dset, key)[source]¶

Bases: NiceRepr

Vectorized access to lists of dictionary objects

Lightweight reference to a set of object (e.g. annotations, images) that allows for convenient property access.

Parameters

ids (List[int]) – list of ids
dset (CocoDataset) – parent dataset
key (str) – main object name (e.g. ‘images’, ‘annotations’)

Types:: ObjT = Ann | Img | Cat # can be one of these types ObjectList1D gives us access to a List[ObjT]

Example

>>> import kwcoco
>>> dset = kwcoco.CocoDataset.demo()
>>> # Both annots and images are object lists
>>> self = dset.annots()
>>> self = dset.images()
>>> # can call with a list of ids or not, for everything
>>> self = dset.annots([1, 2, 11])
>>> self = dset.images([1, 2, 3])
>>> self.lookup('id')
>>> self.lookup(['id'])

unique()[source]¶

Removes any duplicates entries in this object

Returns: ObjectList1D

property objs¶

Get the underlying object dictionary for each object.

Returns: all object dictionaries
Return type: List[ObjT]

take(idxs)[source]¶

Take a subset by index

Returns: ObjectList1D

Example

>>> import kwcoco
>>> self = kwcoco.CocoDataset.demo().annots()
>>> assert len(self.take([0, 2, 3])) == 3

compress(flags)[source]¶

Take a subset by flags

Returns: ObjectList1D

Example

>>> import kwcoco
>>> self = kwcoco.CocoDataset.demo().images()
>>> assert len(self.compress([True, False, True])) == 2

peek()[source]¶

Return the first object dictionary

Returns: object dictionary
Return type: ObjT

Example

>>> import kwcoco
>>> dset = kwcoco.CocoDataset.demo()
>>> self = dset.images()
>>> assert self.peek()['id'] == 1
>>> # Check that subsets return correct items
>>> sub0 = self.compress([i % 2 == 0 for i in range(len(self))])
>>> sub1 = self.compress([i % 2 == 1 for i in range(len(self))])
>>> assert sub0.peek()['id'] == 1
>>> assert sub1.peek()['id'] == 2

lookup(key, default=NoParam, keepid=False)[source]¶

Lookup a list of object attributes

Parameters

key (str | Iterable) – name of the property you want to lookup can also be a list of names, in which case we return a dict
default – if specified, uses this value if it doesn’t exist in an ObjT.
keepid – if True, return a mapping from ids to the property

Returns

a list of whatever type the object is Dict[str, ObjT]

Return type

List[ObjT]

Example

>>> import kwcoco
>>> dset = kwcoco.CocoDataset.demo()
>>> self = dset.annots()
>>> self.lookup('id')
>>> key = ['id']
>>> default = None
>>> self.lookup(key=['id', 'image_id'])
>>> self.lookup(key=['id', 'image_id'])
>>> self.lookup(key='foo', default=None, keepid=True)
>>> self.lookup(key=['foo'], default=None, keepid=True)
>>> self.lookup(key=['id', 'image_id'], keepid=True)

get(key, default=NoParam, keepid=False)[source]¶

Lookup a list of object attributes

Parameters

key (str) – name of the property you want to lookup
default – if specified, uses this value if it doesn’t exist in an ObjT.
keepid – if True, return a mapping from ids to the property

Returns

a list of whatever type the object is Dict[str, ObjT]

Return type

List[ObjT]

Example

>>> import kwcoco
>>> dset = kwcoco.CocoDataset.demo()
>>> self = dset.annots()
>>> self.get('id')
>>> self.get(key='foo', default=None, keepid=True)

set(key, values)[source]¶

Assign a value to each annotation

Parameters

key (str) – the annotation property to modify
values (Iterable | Any) – an iterable of values to set for each annot in the dataset. If the item is not iterable, it is assigned to all objects.

Example

>>> import kwcoco
>>> dset = kwcoco.CocoDataset.demo()
>>> self = dset.annots()
>>> self.set('my-key1', 'my-scalar-value')
>>> self.set('my-key2', np.random.rand(len(self)))
>>> print('dset.imgs = {}'.format(ub.repr2(dset.imgs, nl=1)))
>>> self.get('my-key2')

attribute_frequency()[source]¶

Compute the number of times each key is used in a dictionary

Returns: Dict[str, int]

Example

>>> import kwcoco
>>> dset = kwcoco.CocoDataset.demo()
>>> self = dset.annots()
>>> attrs = self.attribute_frequency()
>>> print('attrs = {}'.format(ub.repr2(attrs, nl=1)))

class kwcoco.coco_objects1d.ObjectGroups(groups, dset)[source]¶

Bases: NiceRepr

An object for holding a groups of ObjectList1D objects

lookup(key, default=NoParam)[source]¶

class kwcoco.coco_objects1d.Categories(ids, dset)[source]¶

Bases: ObjectList1D

Vectorized access to category attributes

SeeAlso:: kwcoco.coco_dataset.MixinCocoObjects.categories()

Example

>>> from kwcoco.coco_objects1d import Categories  # NOQA
>>> import kwcoco
>>> dset = kwcoco.CocoDataset.demo()
>>> ids = list(dset.cats.keys())
>>> self = Categories(ids, dset)
>>> print('self.name = {!r}'.format(self.name))
>>> print('self.supercategory = {!r}'.format(self.supercategory))

property cids¶

property name¶

property supercategory¶

class kwcoco.coco_objects1d.Videos(ids, dset)[source]¶

Bases: ObjectList1D

Vectorized access to video attributes

SeeAlso:: kwcoco.coco_dataset.MixinCocoObjects.videos()

Example

>>> from kwcoco.coco_objects1d import Videos  # NOQA
>>> import kwcoco
>>> dset = kwcoco.CocoDataset.demo('vidshapes5')
>>> ids = list(dset.index.videos.keys())
>>> self = Videos(ids, dset)
>>> print('self = {!r}'.format(self))
self = <Videos(num=5) at ...>

property images¶

Example:

>>> import kwcoco
>>> self = kwcoco.CocoDataset.demo('vidshapes8').videos()
>>> print(self.images)
<ImageGroups(n=8, m=2.0, s=0.0)>

class kwcoco.coco_objects1d.Images(ids, dset)[source]¶

Bases: ObjectList1D

Vectorized access to image attributes

Example

>>> import kwcoco
>>> dset = kwcoco.CocoDataset.demo('photos')
>>> images = dset.images()
>>> print('images = {}'.format(images))
images = <Images(num=3)...>
>>> print('images.gname = {}'.format(images.gname))
images.gname = ['astro.png', 'carl.jpg', 'stars.png']

SeeAlso:: kwcoco.coco_dataset.MixinCocoObjects.images()

property coco_images¶

property gids¶

property gname¶

property gpath¶

property width¶

property height¶

property size¶

Example:

>>> import kwcoco
>>> self = kwcoco.CocoDataset.demo().images()
>>> self._dset._ensure_imgsize()
...
>>> print(self.size)
[(512, 512), (328, 448), (256, 256)]

property area¶

Example:

>>> import kwcoco
>>> self = kwcoco.CocoDataset.demo().images()
>>> self._dset._ensure_imgsize()
...
>>> print(self.area)
[262144, 146944, 65536]

property n_annots¶

Example:

>>> import kwcoco
>>> self = kwcoco.CocoDataset.demo().images()
>>> print(ub.repr2(self.n_annots, nl=0))
[9, 2, 0]

property aids¶

Example:

>>> import kwcoco
>>> self = kwcoco.CocoDataset.demo().images()
>>> print(ub.repr2(list(map(list, self.aids)), nl=0))
[[1, 2, 3, 4, 5, 6, 7, 8, 9], [10, 11], []]

property annots¶

Example:

>>> import kwcoco
>>> self = kwcoco.CocoDataset.demo().images()
>>> print(self.annots)
<AnnotGroups(n=3, m=3.7, s=3.9)>

class kwcoco.coco_objects1d.Annots(ids, dset)[source]¶

Bases: ObjectList1D

Vectorized access to annotation attributes

SeeAlso:: kwcoco.coco_dataset.MixinCocoObjects.annots()

Example

>>> import kwcoco
>>> dset = kwcoco.CocoDataset.demo('photos')
>>> annots = dset.annots()
>>> print('annots = {}'.format(annots))
annots = <Annots(num=11)>
>>> image_ids = annots.lookup('image_id')
>>> print('image_ids = {}'.format(image_ids))
image_ids = [1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2]

property aids¶: The annotation ids of this column of annotations

property images¶

Get the column of images

Returns: Images

property image_id¶

property category_id¶

property gids¶

Get the column of image-ids

Returns: list of image ids
Return type: List[int]

property cids¶

Get the column of category-ids

Returns: List[int]

property cnames¶

Get the column of category names

Returns: List[int]

property detections¶

Get the kwimage-style detection objects

Returns: kwimage.Detections

Example

>>> # xdoctest: +REQUIRES(module:kwimage)
>>> import kwcoco
>>> self = kwcoco.CocoDataset.demo('shapes32').annots([1, 2, 11])
>>> dets = self.detections
>>> print('dets.data = {!r}'.format(dets.data))
>>> print('dets.meta = {!r}'.format(dets.meta))

property boxes¶

Get the column of kwimage-style bounding boxes

Returns: kwimage.Boxes

Example

>>> import kwcoco
>>> self = kwcoco.CocoDataset.demo().annots([1, 2, 11])
>>> print(self.boxes)
<Boxes(xywh,
    array([[ 10,  10, 360, 490],
           [350,   5, 130, 290],
           [156, 130,  45,  18]]))>

property xywh¶

Returns raw boxes

DEPRECATED.

Returns: raw boxes in xywh format
Return type: List[List[int]]

Example

>>> import kwcoco
>>> self = kwcoco.CocoDataset.demo().annots([1, 2, 11])
>>> print(self.xywh)

class kwcoco.coco_objects1d.AnnotGroups(groups, dset)[source]¶

Bases: ObjectGroups

Annotation groups are vectorized lists of lists.

Each item represents a set of annotations that corresopnds with something (i.e. belongs to a particular image).

Example

>>> from kwcoco.coco_objects1d import ImageGroups
>>> import kwcoco
>>> dset = kwcoco.CocoDataset.demo('photos')
>>> images = dset.images()
>>> # Requesting the "annots" property from a Images object
>>> # will return an AnnotGroups object
>>> group: AnnotGroups = images.annots
>>> # Printing the group gives info on the mean/std of the number
>>> # of items per group.
>>> print(group)
<AnnotGroups(n=3, m=3.7, s=3.9)...>
>>> # Groups are fairly restrictive, they dont provide property level
>>> # access in many cases, but the lookup method is available
>>> print(group.lookup('id'))
[[1, 2, 3, 4, 5, 6, 7, 8, 9], [10, 11], []]
>>> print(group.lookup('image_id'))
[[1, 1, 1, 1, 1, 1, 1, 1, 1], [2, 2], []]
>>> print(group.lookup('category_id'))
[[1, 2, 3, 4, 5, 5, 5, 5, 5], [6, 4], []]

property cids¶

Get the grouped category ids for annotations in this group

Return type: List[List[id]]

Example

>>> import kwcoco
>>> self = kwcoco.CocoDataset.demo('photos').images().annots
>>> print('self.cids = {}'.format(ub.repr2(self.cids, nl=0)))
self.cids = [[1, 2, 3, 4, 5, 5, 5, 5, 5], [6, 4], []]

property cnames¶

Get the grouped category names for annotations in this group

Return type: List[List[str]]

Example

>>> import kwcoco
>>> self = kwcoco.CocoDataset.demo('photos').images().annots
>>> print('self.cnames = {}'.format(ub.repr2(self.cnames, nl=0)))
self.cnames = [['astronaut', 'rocket', 'helmet', 'mouth', 'star', 'star', 'star', 'star', 'star'], ['astronomer', 'mouth'], []]

class kwcoco.coco_objects1d.ImageGroups(groups, dset)[source]¶

Bases: ObjectGroups

Image groups are vectorized lists of other Image objects.

Each item represents a set of images that corresopnds with something (i.e. belongs to a particular video).

Example

>>> from kwcoco.coco_objects1d import ImageGroups
>>> import kwcoco
>>> dset = kwcoco.CocoDataset.demo('vidshapes8')
>>> videos = dset.videos()
>>> # Requesting the "images" property from a Videos object
>>> # will return an ImageGroups object
>>> group: ImageGroups = videos.images
>>> # Printing the group gives info on the mean/std of the number
>>> # of items per group.
>>> print(group)
<ImageGroups(n=8, m=2.0, s=0.0)...>
>>> # Groups are fairly restrictive, they dont provide property level
>>> # access in many cases, but the lookup method is available
>>> print(group.lookup('id'))
[[1, 2], [3, 4], [5, 6], [7, 8], [9, 10], [11, 12], [13, 14], [15, 16]]
>>> print(group.lookup('video_id'))
[[1, 1], [2, 2], [3, 3], [4, 4], [5, 5], [6, 6], [7, 7], [8, 8]]
>>> print(group.lookup('frame_index'))
[[0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1]]