kwcoco.compat_dataset module¶
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.
catToImgs returns integer image ids but imgToAnns returns annotation dictionaries.
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.
- class kwcoco.compat_dataset.COCO(annotation_file=None, **kw)[source]¶
Bases:
CocoDatasetA 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))
- property imgToAnns¶
- property catToImgs¶
unlike the name implies, this actually goes from category to image ids Name retained for backward compatibility
- getAnnIds(imgIds=[], catIds=[], areaRng=[], iscrowd=None)[source]¶
Get ann ids that satisfy given filter conditions. default skips that filter
- Parameters
imgIds (List[int]) – get anns for given imgs
catIds (List[int]) – get anns for given cats
areaRng (List[float]) – get anns for given area range (e.g. [0 inf])
iscrowd (bool) – get anns for given crowd label (False or True)
- Returns
integer array of ann ids
- Return type
List[int]
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(catNms=[], supNms=[], catIds=[])[source]¶
filtering parameters. default skips that filter.
- Parameters
catNms (List[str]) – get cats for given cat names
supNms (List[str]) – get cats for given supercategory names
catIds (List[int]) – get cats for given cat ids
- Returns
integer array of cat ids
- Return type
List[int]
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(imgIds=[], catIds=[])[source]¶
Get img ids that satisfy given filter conditions.
- Parameters
imgIds (List[int]) – get imgs for given ids
catIds (List[int]) – get imgs with all given cats
- Returns
integer array of img ids
- Return type
List[int]
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(ids=[])[source]¶
Load anns with the specified ids.
- Parameters
ids (List[int]) – integer ids specifying anns
- Returns
loaded ann objects
- Return type
List[dict]
- loadCats(ids=[])[source]¶
Load cats with the specified ids.
- Parameters
ids (List[int]) – integer ids specifying cats
- Returns
loaded cat objects
- Return type
List[dict]
- loadImgs(ids=[])[source]¶
Load anns with the specified ids.
- Parameters
ids (List[int]) – integer ids specifying img
- Returns
loaded img objects
- Return type
List[dict]
- showAnns(anns, draw_bbox=False)[source]¶
Display the specified annotations.
- Parameters
anns (List[Dict]) – annotations to display
- loadRes(resFile)[source]¶
Load result file and return a result api object.
- Parameters
resFile (str) – file name of result file
- Returns
res result api object
- Return type
- download(tarDir=None, imgIds=[])[source]¶
Download COCO images from mscoco.org server.
- Parameters
tarDir (str) – COCO results directory name
imgIds (list) – images to be downloaded
- loadNumpyAnnotations(data)[source]¶
Convert result data from a numpy array [Nx7] where each row contains {imageID,x1,y1,w,h,score,class}
- Parameters
data (numpy.ndarray)
- Returns
annotations (python nested list)
- Return type
List[Dict]
- annToRLE(ann)[source]¶
Convert annotation which can be polygons, uncompressed RLE to RLE.
- Returns
kwimage.Mask
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])