from detectron2.data.samplers import RepeatFactorTrainingSampler
from detectron2.data.common import DatasetFromList
from detectron2.data.build import get_detection_dataset_dicts
from numpy.core.fromnumeric import repeat


class RepeatfactorSampler(RepeatFactorTrainingSampler):
    """
	Similar to TrainingSampler, but a sample may appear more times than others based on its "repeat factor". 
	This is suitable for training on class imbalanced datasets like LVIS.
	"""
    repeat_factors = None
    threshold = None

    def __init__(self, size: int, shuffle=True, seed=None):
        super().__init__(RepeatFactorTrainingSampler.
            repeat_factors_from_category_frequency(self.repeat_factors,
            self.threshold), shuffle=shuffle, seed=seed)

170a73ed985d2098ea61d79adee676b3ed43b5e8
<mask token>


class RepeatfactorSampler(RepeatFactorTrainingSampler):
    <mask token>
    <mask token>
    <mask token>

    def __init__(self, size: int, shuffle=True, seed=None):
        super().__init__(RepeatFactorTrainingSampler.
            repeat_factors_from_category_frequency(self.repeat_factors,
            self.threshold), shuffle=shuffle, seed=seed)

<mask token>


class RepeatfactorSampler(RepeatFactorTrainingSampler):
    <mask token>
    repeat_factors = None
    threshold = None

    def __init__(self, size: int, shuffle=True, seed=None):
        super().__init__(RepeatFactorTrainingSampler.
            repeat_factors_from_category_frequency(self.repeat_factors,
            self.threshold), shuffle=shuffle, seed=seed)

<mask token>


class RepeatfactorSampler(RepeatFactorTrainingSampler):
    """
	Similar to TrainingSampler, but a sample may appear more times than others based on its "repeat factor". 
	This is suitable for training on class imbalanced datasets like LVIS.
	"""
    repeat_factors = None
    threshold = None

    def __init__(self, size: int, shuffle=True, seed=None):
        super().__init__(RepeatFactorTrainingSampler.
            repeat_factors_from_category_frequency(self.repeat_factors,
            self.threshold), shuffle=shuffle, seed=seed)

from detectron2.data.samplers import RepeatFactorTrainingSampler
from detectron2.data.common import DatasetFromList
from detectron2.data.build import get_detection_dataset_dicts
from numpy.core.fromnumeric import repeat


class RepeatfactorSampler(RepeatFactorTrainingSampler):
    """
	Similar to TrainingSampler, but a sample may appear more times than others based on its "repeat factor". 
	This is suitable for training on class imbalanced datasets like LVIS.
	"""
    repeat_factors = None
    threshold = None

    def __init__(self, size: int, shuffle=True, seed=None):
        super().__init__(RepeatFactorTrainingSampler.
            repeat_factors_from_category_frequency(self.repeat_factors,
            self.threshold), shuffle=shuffle, seed=seed)
