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# Copyright (c) OpenMMLab. All rights reserved. | |
"""copy from | |
https://github.com/ZwwWayne/K-Net/blob/main/knet/det/mask_pseudo_sampler.py.""" | |
import torch | |
from mmengine.structures import InstanceData | |
from mmdet.registry import TASK_UTILS | |
from ..assigners import AssignResult | |
from .base_sampler import BaseSampler | |
from .mask_sampling_result import MaskSamplingResult | |
class MaskPseudoSampler(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 | |
def sample(self, assign_result: AssignResult, pred_instances: InstanceData, | |
gt_instances: InstanceData, *args, **kwargs): | |
"""Directly returns the positive and negative indices of samples. | |
Args: | |
assign_result (:obj:`AssignResult`): Mask assigning results. | |
pred_instances (:obj:`InstanceData`): Instances of model | |
predictions. It includes ``scores`` and ``masks`` predicted | |
by the model. | |
gt_instances (:obj:`InstanceData`): Ground truth of instance | |
annotations. It usually includes ``labels`` and ``masks`` | |
attributes. | |
Returns: | |
:obj:`SamplingResult`: sampler results | |
""" | |
pred_masks = pred_instances.masks | |
gt_masks = gt_instances.masks | |
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 = pred_masks.new_zeros(pred_masks.shape[0], dtype=torch.uint8) | |
sampling_result = MaskSamplingResult( | |
pos_inds=pos_inds, | |
neg_inds=neg_inds, | |
masks=pred_masks, | |
gt_masks=gt_masks, | |
assign_result=assign_result, | |
gt_flags=gt_flags, | |
avg_factor_with_neg=False) | |
return sampling_result | |