Default initialization for Parameters of Module.

query_bbox: [B, Q, 10] query_feat: [B, Q, C]

query_bbox: [B, Q, 10] query_feat: [B, Q, C]

query_bbox: [B, Q, 10] query_feat: [B, Q, C]

Inverse function of sigmoid. Args: x (Tensor): The tensor to do the inverse. eps (float): EPS avoid numerical

value: [B, N, H1W1 + H2W2..., C] sampling_locations: [B, Q, P, 3] scale_weights: [B, Q, P, 4]

value: [B, N, H1W1 + H2W2..., C] sampling_locations: [B, Q, P, 3] scale_weights: [B, Q, P, 4]

r"""Convert an integer label x-D tensor to a one-hot (x+1)-D tensor. Args: labels: tensor with labels of shape :math:`(N, *)`, where N is

Apply dynamic voxelization to points. Args: points (list[torch.Tensor]): Points of each sample. Returns: tup

Render sample data onto axis. :param sample_data_token: Sample_data token. :param with_anns: Whether to draw box annotations. :param

r"""Convert an image from RGB to HSV. .. image:: _static/img/rgb_to_hsv.png The image data is assumed to be in the range of (0, 1). Arg

https://github.com/Megvii-BaseDetection/BEVStereo/blob/master/dataset/nusc_mv_det_dataset.py#L247

Args: sample_points: 3D sampling points in shape [B, Q, T, G, P, 3] mlvl_feats: list of multi-scale features from neck, each in s

Visualizes a sample from BEV with annotations and detection results. :param nusc: NuScenes object. :param sample_token: The nuScenes samp

Call function to pad images, masks, semantic segmentation maps. Args: results (dict): Result dict from loading pipeline. R

Call function to normalize images. Args: results (dict): Result dict from loading pipeline. Returns: dict: Nor

Call function to perform photometric distortion on images. Args: results (dict): Result dict from loading pipeline. Return

Call function to normalize images. Args: results (dict): Result dict from loading pipeline. Returns: dict: N

Call function to flip bounding boxes, masks, semantic segmentation maps. Args: results (dict): Result dict from loading p

Call function to load points data from file. Args: results (dict): Result dict containing point clouds data. Returns:

Call function to load points data from file. Args: results (dict): Result dict containing point clouds data. Returns:

Call function to load points data from file. Args: results (dict): Result dict containing point clouds data. Returns:

Call function to transform and format common fields in results. Args: results (dict): Result dict contains the data to convert.

Call function to perform photometric distortion on images. Args: results (dict): Result dict from loading pipeline. Return

Args: bbox_pred (Tensor): Predicted boxes with normalized coordinates (cx, cy, w, h), which are all in range [0,

Args: bbox_pred (Tensor): Predicted boxes with normalized coordinates (cx, cy, w, h), which are all in range [0,