def getCatIds(self,
catNms=[],
supNms=[],
catIds=[],
category_type='categories'):
"""
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
"""
if category_type not in self.dataset.keys():
return None
catNms = catNms if _isArrayLike(catNms) else [catNms]
supNms = supNms if _isArrayLike(supNms) else [supNms]
catIds = catIds if _isArrayLike(catIds) else [catIds]
if len(catNms) == len(supNms) == len(catIds) == 0:
cats = self.dataset[category_type]
else:
cats = self.dataset[category_type]
cats = cats if len(catNms) == 0 else [
cat for cat in cats if cat['name'] in catNms
]
cats = cats if len(supNms) == 0 else [
cat for cat in cats if cat['supercategory'] in supNms
]
cats = cats if len(catIds) == 0 else [
cat for cat in cats if cat['id'] in catIds
]
ids = [cat['id'] for cat in cats]
return ids
def getAnnIds(self,
imgIds=[],
catIds=[],
areaRng=[],
iscrowd=None,
typeIds=[]):
"""
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)
typeIds (int array) : get anns for given type ids
:return: ids (int array) : integer array of ann ids
"""
imgIds = imgIds if _isArrayLike(imgIds) else [imgIds]
catIds = catIds if _isArrayLike(catIds) else [catIds]
typeIds = typeIds if _isArrayLike(typeIds) else [typeIds]
if len(imgIds) == len(catIds) == len(areaRng) == len(typeIds) == 0:
anns = self.dataset['annotations']
else:
if not len(imgIds) == 0:
lists = [
self.imgToAnns[imgId] for imgId in imgIds
if imgId in self.imgToAnns
]
anns = list(itertools.chain.from_iterable(lists))
else:
anns = self.dataset['annotations']
anns = anns if len(catIds) == 0 else [
ann for ann in anns if ann['category_id'] in catIds
]
anns = anns if len(areaRng) == 0 else [
ann for ann in anns
if ann['area'] > areaRng[0] and ann['area'] < areaRng[1]
]
anns = anns if len(typeIds) == 0 else [
ann for ann in anns if ann['type_id'] in typeIds
]
if not iscrowd == None:
ids = [ann['id'] for ann in anns if ann['iscrowd'] == iscrowd]
else:
ids = [ann['id'] for ann in anns]
return ids
def get_vid_ids(self, vidIds=[]):
vidIds = vidIds if _isArrayLike(vidIds) else [vidIds]
if len(vidIds) == 0:
ids = self.videos.keys()
else:
ids = set(vidIds)
return list(ids)
def load_vids(self, ids=[]):
"""Get video information of given video ids.
Default return all videos information.
Args:
ids (list[int]): The given video ids. Defaults to [].
Returns:
list[dict]: List of video information.
"""
if _isArrayLike(ids):
return [self.videos[id] for id in ids]
elif type(ids) == int:
return [self.videos[ids]]
def getBBoxes(self, catIds=[]):
"""
Get bboxes of given cat ids.
Args:
catIds (int array):
Returns:
bboxes: numpy array of bboxes.
"""
catIds = catIds if _isArrayLike(catIds) else [catIds]
bboxes = []
if len(catIds) == 0:
catIds = self.getCatIds()
for id in catIds:
bboxes.extend(self.catToBBoxes[id])
return np.array(bboxes)
def get_vid_ids(self, vidIds=[]):
"""Get video ids that satisfy given filter conditions.
Default return all video ids.
Args:
vidIds (list[int]): The given video ids. Defaults to [].
Returns:
list[int]: Video ids.
"""
vidIds = vidIds if _isArrayLike(vidIds) else [vidIds]
if len(vidIds) == 0:
ids = self.videos.keys()
else:
ids = set(vidIds)
return list(ids)
def load_vids(self, ids=[]):
if _isArrayLike(ids):
return [self.videos[id] for id in ids]
elif type(ids) == int:
return [self.videos[ids]]