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hub / github.com/OpenDriveLab/OpenLane / getAnnIds

Method getAnnIds

eval/CIPO_evaluation/adapter.py:313–342  ·  view source on GitHub ↗

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])

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

Source from the content-addressed store, hash-verified

311 return [self.anns[ids]]
312
313 def getAnnIds(self, imgIds=[], catIds=[], areaRng=[], iscrowd=None):
314 """
315 Get ann ids that satisfy given filter conditions. default skips that filter
316 :param imgIds (int array) : get anns for given imgs
317 catIds (int array) : get anns for given cats
318 areaRng (float array) : get anns for given area range (e.g. [0 inf])
319 iscrowd (boolean) : get anns for given crowd label (False or True)
320 :return: ids (int array) : integer array of ann ids
321 """
322 imgIds = imgIds if _isArrayLike(imgIds) else [imgIds]
323 catIds = catIds if _isArrayLike(catIds) else [catIds]
324
325 if len(imgIds) == len(catIds) == len(areaRng) == 0:
326 anns = self.dataset['annotations']
327 else:
328 if not len(imgIds) == 0:
329 lists = [self.imgToAnns[imgId] for imgId in imgIds if imgId in self.imgToAnns]
330 # print(len(lists), "lists")
331 # print(lists)
332 anns = list(itertools.chain.from_iterable(lists))
333 else:
334 anns = self.dataset['annotations']
335 anns = anns if len(areaRng) == 0 else [ann for ann in anns if ann['area'] > areaRng[0] and ann['area'] < areaRng[1]]
336 if not iscrowd == None:
337 ids = [int(ann['id']) for ann in anns if ann['iscrowd'] == iscrowd]
338 else:
339 # for ann in anns:
340 # print("a", ann)
341 ids = [int(ann['id']) for ann in anns]
342 return ids

Callers 3

CIPO_evalFunction · 0.80
CIPO_evalFunction · 0.80
_prepareMethod · 0.80

Calls 1

_isArrayLikeFunction · 0.85

Tested by

no test coverage detected