:param t1_box_nums: list of number of t1 boxes - length is batch size :param t2_box_nums: list of number of t2 boxes - length is ba

Create configs and perform basic setups.

Create configs and perform basic setups.

Args: cfg (CfgNode): model (nn.Module): evaluators (list[DatasetEvaluator] or None): if None, will call

Args: cfg (CfgNode): model (nn.Module): evaluators (list[DatasetEvaluator] or None): if None, will ca

get top K point in score map

transform predicted boxes to target boxes Args: boxes: Tensor torch Tensor with (Batch, N, 4) shape

r""" transform predicted boxes to target boxes Args: boxes(Tensor): torch Tensor with (Batch, N, 4) shape img

Update a matched track :type new_track: STrack :type frame_id: int :type update_feature: bool :return:

Args: original_image (np.ndarray): an image of shape (H, W, C) (in BGR order). Returns: predictions (dict):

Args: border(int): border size of image output_size(tuple): a tuple represents (width, height) of image r

output_size:(w, h)

Args: size (int): the total number of data of the underlying dataset to sample from

Args: size (int): the total number of data of the underlying dataset to sample from

COCO by json variable, instead of json file