Shortcuts

mmdet.core.bbox.samplers.pseudo_sampler 源代码

# Copyright (c) OpenMMLab. All rights reserved.
import torch

from ..builder import BBOX_SAMPLERS
from .base_sampler import BaseSampler
from .sampling_result import SamplingResult


[文档]@BBOX_SAMPLERS.register_module() class PseudoSampler(BaseSampler): """A pseudo sampler that does not do sampling actually.""" def __init__(self, **kwargs): pass def _sample_pos(self, **kwargs): """Sample positive samples.""" raise NotImplementedError def _sample_neg(self, **kwargs): """Sample negative samples.""" raise NotImplementedError
[文档] def sample(self, assign_result, bboxes, gt_bboxes, *args, **kwargs): """Directly returns the positive and negative indices of samples. Args: assign_result (:obj:`AssignResult`): Assigned results bboxes (torch.Tensor): Bounding boxes gt_bboxes (torch.Tensor): Ground truth boxes Returns: :obj:`SamplingResult`: sampler results """ pos_inds = torch.nonzero( assign_result.gt_inds > 0, as_tuple=False).squeeze(-1).unique() neg_inds = torch.nonzero( assign_result.gt_inds == 0, as_tuple=False).squeeze(-1).unique() gt_flags = bboxes.new_zeros(bboxes.shape[0], dtype=torch.uint8) sampling_result = SamplingResult(pos_inds, neg_inds, bboxes, gt_bboxes, assign_result, gt_flags) return sampling_result