repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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DDOD | DDOD-main/mmdet/core/bbox/coder/__init__.py | from .base_bbox_coder import BaseBBoxCoder
from .bucketing_bbox_coder import BucketingBBoxCoder
from .delta_xywh_bbox_coder import DeltaXYWHBBoxCoder
from .legacy_delta_xywh_bbox_coder import LegacyDeltaXYWHBBoxCoder
from .pseudo_bbox_coder import PseudoBBoxCoder
from .tblr_bbox_coder import TBLRBBoxCoder
from .yolo_bb... | 584 | 38 | 66 | py |
DDOD | DDOD-main/mmdet/core/bbox/iou_calculators/__init__.py | from .builder import build_iou_calculator
from .iou2d_calculator import BboxOverlaps2D, bbox_overlaps
__all__ = ['build_iou_calculator', 'BboxOverlaps2D', 'bbox_overlaps']
| 173 | 33.8 | 69 | py |
DDOD | DDOD-main/mmdet/core/bbox/iou_calculators/builder.py | from mmcv.utils import Registry, build_from_cfg
IOU_CALCULATORS = Registry('IoU calculator')
def build_iou_calculator(cfg, default_args=None):
"""Builder of IoU calculator."""
return build_from_cfg(cfg, IOU_CALCULATORS, default_args)
| 245 | 26.333333 | 61 | py |
DDOD | DDOD-main/mmdet/core/bbox/iou_calculators/iou2d_calculator.py | import torch
from .builder import IOU_CALCULATORS
def cast_tensor_type(x, scale=1., dtype=None):
if dtype == 'fp16':
# scale is for preventing overflows
x = (x / scale).half()
return x
def fp16_clamp(x, min=None, max=None):
if not x.is_cuda and x.dtype == torch.float16:
# clamp ... | 9,633 | 35.911877 | 78 | py |
DDOD | DDOD-main/mmdet/core/bbox/samplers/instance_balanced_pos_sampler.py | import numpy as np
import torch
from ..builder import BBOX_SAMPLERS
from .random_sampler import RandomSampler
@BBOX_SAMPLERS.register_module()
class InstanceBalancedPosSampler(RandomSampler):
"""Instance balanced sampler that samples equal number of positive samples
for each instance."""
def _sample_pos... | 2,271 | 39.571429 | 79 | py |
DDOD | DDOD-main/mmdet/core/bbox/samplers/combined_sampler.py | from ..builder import BBOX_SAMPLERS, build_sampler
from .base_sampler import BaseSampler
@BBOX_SAMPLERS.register_module()
class CombinedSampler(BaseSampler):
"""A sampler that combines positive sampler and negative sampler."""
def __init__(self, pos_sampler, neg_sampler, **kwargs):
super(CombinedSamp... | 700 | 32.380952 | 72 | py |
DDOD | DDOD-main/mmdet/core/bbox/samplers/base_sampler.py | from abc import ABCMeta, abstractmethod
import torch
from .sampling_result import SamplingResult
class BaseSampler(metaclass=ABCMeta):
"""Base class of samplers."""
def __init__(self,
num,
pos_fraction,
neg_pos_ub=-1,
add_gt_as_proposals=T... | 3,872 | 36.970588 | 79 | py |
DDOD | DDOD-main/mmdet/core/bbox/samplers/random_sampler.py | import torch
from ..builder import BBOX_SAMPLERS
from .base_sampler import BaseSampler
@BBOX_SAMPLERS.register_module()
class RandomSampler(BaseSampler):
"""Random sampler.
Args:
num (int): Number of samples
pos_fraction (float): Fraction of positive samples
neg_pos_up (int, optional... | 3,023 | 35.878049 | 78 | py |
DDOD | DDOD-main/mmdet/core/bbox/samplers/ohem_sampler.py | import torch
from ..builder import BBOX_SAMPLERS
from ..transforms import bbox2roi
from .base_sampler import BaseSampler
@BBOX_SAMPLERS.register_module()
class OHEMSampler(BaseSampler):
r"""Online Hard Example Mining Sampler described in `Training Region-based
Object Detectors with Online Hard Example Mining... | 4,098 | 36.953704 | 79 | py |
DDOD | DDOD-main/mmdet/core/bbox/samplers/iou_balanced_neg_sampler.py | import numpy as np
import torch
from ..builder import BBOX_SAMPLERS
from .random_sampler import RandomSampler
@BBOX_SAMPLERS.register_module()
class IoUBalancedNegSampler(RandomSampler):
"""IoU Balanced Sampling.
arXiv: https://arxiv.org/pdf/1904.02701.pdf (CVPR 2019)
Sampling proposals according to th... | 6,692 | 41.360759 | 79 | py |
DDOD | DDOD-main/mmdet/core/bbox/samplers/score_hlr_sampler.py | import torch
from mmcv.ops import nms_match
from ..builder import BBOX_SAMPLERS
from ..transforms import bbox2roi
from .base_sampler import BaseSampler
from .sampling_result import SamplingResult
@BBOX_SAMPLERS.register_module()
class ScoreHLRSampler(BaseSampler):
r"""Importance-based Sample Reweighting (ISR_N),... | 11,187 | 41.218868 | 79 | py |
DDOD | DDOD-main/mmdet/core/bbox/samplers/__init__.py | from .base_sampler import BaseSampler
from .combined_sampler import CombinedSampler
from .instance_balanced_pos_sampler import InstanceBalancedPosSampler
from .iou_balanced_neg_sampler import IoUBalancedNegSampler
from .ohem_sampler import OHEMSampler
from .pseudo_sampler import PseudoSampler
from .random_sampler impor... | 628 | 38.3125 | 77 | py |
DDOD | DDOD-main/mmdet/core/bbox/samplers/sampling_result.py | import torch
from mmdet.utils import util_mixins
class SamplingResult(util_mixins.NiceRepr):
"""Bbox sampling result.
Example:
>>> # xdoctest: +IGNORE_WANT
>>> from mmdet.core.bbox.samplers.sampling_result import * # NOQA
>>> self = SamplingResult.random(rng=10)
>>> print(f'... | 5,334 | 33.869281 | 81 | py |
DDOD | DDOD-main/mmdet/core/bbox/samplers/pseudo_sampler.py | import torch
from ..builder import BBOX_SAMPLERS
from .base_sampler import BaseSampler
from .sampling_result import SamplingResult
@BBOX_SAMPLERS.register_module()
class PseudoSampler(BaseSampler):
"""A pseudo sampler that does not do sampling actually."""
def __init__(self, **kwargs):
pass
def... | 1,415 | 32.714286 | 79 | py |
DDOD | DDOD-main/mmdet/core/visualization/image.py | import matplotlib.pyplot as plt
import mmcv
import numpy as np
import pycocotools.mask as mask_util
from matplotlib.collections import PatchCollection
from matplotlib.patches import Polygon
from ..utils import mask2ndarray
EPS = 1e-2
def color_val_matplotlib(color):
"""Convert various input in BGR order to norm... | 10,946 | 35.009868 | 77 | py |
DDOD | DDOD-main/mmdet/core/visualization/__init__.py | from .image import (color_val_matplotlib, imshow_det_bboxes,
imshow_gt_det_bboxes)
__all__ = ['imshow_det_bboxes', 'imshow_gt_det_bboxes', 'color_val_matplotlib']
| 184 | 36 | 79 | py |
DDOD | DDOD-main/mmdet/core/utils/dist_utils.py | import warnings
from collections import OrderedDict
import torch.distributed as dist
from mmcv.runner import OptimizerHook
from torch._utils import (_flatten_dense_tensors, _take_tensors,
_unflatten_dense_tensors)
def _allreduce_coalesced(tensors, world_size, bucket_size_mb=-1):
if buck... | 2,327 | 32.257143 | 77 | py |
DDOD | DDOD-main/mmdet/core/utils/misc.py | from functools import partial
import numpy as np
import torch
from six.moves import map, zip
from ..mask.structures import BitmapMasks, PolygonMasks
def multi_apply(func, *args, **kwargs):
"""Apply function to a list of arguments.
Note:
This function applies the ``func`` to multiple inputs and
... | 2,615 | 29.776471 | 79 | py |
DDOD | DDOD-main/mmdet/core/utils/__init__.py | from .dist_utils import DistOptimizerHook, allreduce_grads, reduce_mean
from .misc import flip_tensor, mask2ndarray, multi_apply, unmap
__all__ = [
'allreduce_grads', 'DistOptimizerHook', 'reduce_mean', 'multi_apply',
'unmap', 'mask2ndarray', 'flip_tensor'
]
| 268 | 32.625 | 73 | py |
DDOD | DDOD-main/mmdet/core/anchor/point_generator.py | import numpy as np
import torch
from torch.nn.modules.utils import _pair
from .builder import PRIOR_GENERATORS
@PRIOR_GENERATORS.register_module()
class PointGenerator:
def _meshgrid(self, x, y, row_major=True):
xx = x.repeat(len(y))
yy = y.view(-1, 1).repeat(1, len(x)).view(-1)
if row_m... | 9,782 | 39.42562 | 79 | py |
DDOD | DDOD-main/mmdet/core/anchor/anchor_generator.py | import warnings
import mmcv
import numpy as np
import torch
from torch.nn.modules.utils import _pair
from .builder import PRIOR_GENERATORS
@PRIOR_GENERATORS.register_module()
class AnchorGenerator:
"""Standard anchor generator for 2D anchor-based detectors.
Args:
strides (list[int] | list[tuple[int... | 35,686 | 41.535161 | 79 | py |
DDOD | DDOD-main/mmdet/core/anchor/utils.py | import torch
def images_to_levels(target, num_levels):
"""Convert targets by image to targets by feature level.
[target_img0, target_img1] -> [target_level0, target_level1, ...]
"""
target = torch.stack(target, 0)
level_targets = []
start = 0
for n in num_levels:
end = start + n
... | 2,497 | 33.694444 | 79 | py |
DDOD | DDOD-main/mmdet/core/anchor/__init__.py | from .anchor_generator import (AnchorGenerator, LegacyAnchorGenerator,
YOLOAnchorGenerator)
from .builder import (ANCHOR_GENERATORS, PRIOR_GENERATORS,
build_anchor_generator, build_prior_generator)
from .point_generator import MlvlPointGenerator, PointGenerator
from ... | 672 | 47.071429 | 73 | py |
DDOD | DDOD-main/mmdet/core/anchor/builder.py | import warnings
from mmcv.utils import Registry, build_from_cfg
PRIOR_GENERATORS = Registry('Generator for anchors and points')
ANCHOR_GENERATORS = PRIOR_GENERATORS
def build_prior_generator(cfg, default_args=None):
return build_from_cfg(cfg, PRIOR_GENERATORS, default_args)
def build_anchor_generator(cfg, de... | 535 | 27.210526 | 74 | py |
DDOD | DDOD-main/mmdet/models/__init__.py | from .backbones import * # noqa: F401,F403
from .builder import (BACKBONES, DETECTORS, HEADS, LOSSES, NECKS,
ROI_EXTRACTORS, SHARED_HEADS, build_backbone,
build_detector, build_head, build_loss, build_neck,
build_roi_extractor, build_shared_head)
from .... | 765 | 44.058824 | 78 | py |
DDOD | DDOD-main/mmdet/models/builder.py | import warnings
from mmcv.cnn import MODELS as MMCV_MODELS
from mmcv.utils import Registry
MODELS = Registry('models', parent=MMCV_MODELS)
BACKBONES = MODELS
NECKS = MODELS
ROI_EXTRACTORS = MODELS
SHARED_HEADS = MODELS
HEADS = MODELS
LOSSES = MODELS
DETECTORS = MODELS
def build_backbone(cfg):
"""Build backbone... | 1,401 | 22.762712 | 71 | py |
DDOD | DDOD-main/mmdet/models/detectors/fsaf.py | from ..builder import DETECTORS
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class FSAF(SingleStageDetector):
"""Implementation of `FSAF <https://arxiv.org/abs/1903.00621>`_"""
def __init__(self,
backbone,
neck,
bbox_head,
... | 587 | 29.947368 | 72 | py |
DDOD | DDOD-main/mmdet/models/detectors/two_stage.py | import warnings
import torch
from ..builder import DETECTORS, build_backbone, build_head, build_neck
from .base import BaseDetector
@DETECTORS.register_module()
class TwoStageDetector(BaseDetector):
"""Base class for two-stage detectors.
Two-stage detectors typically consisting of a region proposal network... | 7,199 | 34.643564 | 79 | py |
DDOD | DDOD-main/mmdet/models/detectors/base.py | from abc import ABCMeta, abstractmethod
from collections import OrderedDict
import mmcv
import numpy as np
import torch
import torch.distributed as dist
from mmcv.runner import BaseModule, auto_fp16
from mmdet.core.visualization import imshow_det_bboxes
class BaseDetector(BaseModule, metaclass=ABCMeta):
"""Base... | 14,139 | 39.4 | 79 | py |
DDOD | DDOD-main/mmdet/models/detectors/single_stage.py | import warnings
import torch
from mmdet.core import bbox2result
from ..builder import DETECTORS, build_backbone, build_head, build_neck
from .base import BaseDetector
@DETECTORS.register_module()
class SingleStageDetector(BaseDetector):
"""Base class for single-stage detectors.
Single-stage detectors direc... | 6,461 | 37.927711 | 78 | py |
DDOD | DDOD-main/mmdet/models/detectors/gfl.py | from ..builder import DETECTORS
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class GFL(SingleStageDetector):
def __init__(self,
backbone,
neck,
bbox_head,
train_cfg=None,
test_cfg=None,
... | 513 | 27.555556 | 71 | py |
DDOD | DDOD-main/mmdet/models/detectors/detr.py | import torch
from ..builder import DETECTORS
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class DETR(SingleStageDetector):
r"""Implementation of `DETR: End-to-End Object Detection with
Transformers <https://arxiv.org/pdf/2005.12872>`_"""
def __init__(self,
... | 1,652 | 34.170213 | 79 | py |
DDOD | DDOD-main/mmdet/models/detectors/yolo.py | # Copyright (c) 2019 Western Digital Corporation or its affiliates.
from ..builder import DETECTORS
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class YOLOV3(SingleStageDetector):
def __init__(self,
backbone,
neck,
bbox_head,
... | 591 | 28.6 | 74 | py |
DDOD | DDOD-main/mmdet/models/detectors/reppoints_detector.py | from ..builder import DETECTORS
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class RepPointsDetector(SingleStageDetector):
"""RepPoints: Point Set Representation for Object Detection.
This detector is the implementation of:
- RepPoints detector (https://arxiv.org/pdf... | 736 | 29.708333 | 76 | py |
DDOD | DDOD-main/mmdet/models/detectors/scnet.py | from ..builder import DETECTORS
from .cascade_rcnn import CascadeRCNN
@DETECTORS.register_module()
class SCNet(CascadeRCNN):
"""Implementation of `SCNet <https://arxiv.org/abs/2012.10150>`_"""
def __init__(self, **kwargs):
super(SCNet, self).__init__(**kwargs)
| 280 | 24.545455 | 71 | py |
DDOD | DDOD-main/mmdet/models/detectors/kd_one_stage.py | import mmcv
import torch
from mmcv.runner import load_checkpoint
from .. import build_detector
from ..builder import DETECTORS
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class KnowledgeDistillationSingleStageDetector(SingleStageDetector):
r"""Implementation of `Distilling the Know... | 4,102 | 39.623762 | 79 | py |
DDOD | DDOD-main/mmdet/models/detectors/fast_rcnn.py | from ..builder import DETECTORS
from .two_stage import TwoStageDetector
@DETECTORS.register_module()
class FastRCNN(TwoStageDetector):
"""Implementation of `Fast R-CNN <https://arxiv.org/abs/1504.08083>`_"""
def __init__(self,
backbone,
roi_head,
train_cfg,
... | 2,116 | 37.490909 | 78 | py |
DDOD | DDOD-main/mmdet/models/detectors/autoassign.py | from ..builder import DETECTORS
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class AutoAssign(SingleStageDetector):
"""Implementation of `AutoAssign: Differentiable Label Assignment for Dense
Object Detection <https://arxiv.org/abs/2007.03496>`_."""
def __init__(self,
... | 634 | 32.421053 | 79 | py |
DDOD | DDOD-main/mmdet/models/detectors/cascade_rcnn.py | from ..builder import DETECTORS
from .two_stage import TwoStageDetector
@DETECTORS.register_module()
class CascadeRCNN(TwoStageDetector):
r"""Implementation of `Cascade R-CNN: Delving into High Quality Object
Detection <https://arxiv.org/abs/1906.09756>`_"""
def __init__(self,
backbone,
... | 1,650 | 32.693878 | 75 | py |
DDOD | DDOD-main/mmdet/models/detectors/deformable_detr.py | from ..builder import DETECTORS
from .detr import DETR
@DETECTORS.register_module()
class DeformableDETR(DETR):
def __init__(self, *args, **kwargs):
super(DETR, self).__init__(*args, **kwargs)
| 208 | 19.9 | 51 | py |
DDOD | DDOD-main/mmdet/models/detectors/nasfcos.py | from ..builder import DETECTORS
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class NASFCOS(SingleStageDetector):
"""NAS-FCOS: Fast Neural Architecture Search for Object Detection.
https://arxiv.org/abs/1906.0442
"""
def __init__(self,
backbone,
... | 641 | 28.181818 | 75 | py |
DDOD | DDOD-main/mmdet/models/detectors/mask_rcnn.py | from ..builder import DETECTORS
from .two_stage import TwoStageDetector
@DETECTORS.register_module()
class MaskRCNN(TwoStageDetector):
"""Implementation of `Mask R-CNN <https://arxiv.org/abs/1703.06870>`_"""
def __init__(self,
backbone,
rpn_head,
roi_head,
... | 755 | 27 | 76 | py |
DDOD | DDOD-main/mmdet/models/detectors/paa.py | from ..builder import DETECTORS
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class PAA(SingleStageDetector):
"""Implementation of `PAA <https://arxiv.org/pdf/2007.08103.pdf>`_."""
def __init__(self,
backbone,
neck,
bbox_head,
... | 588 | 30 | 74 | py |
DDOD | DDOD-main/mmdet/models/detectors/faster_rcnn.py | from ..builder import DETECTORS
from .two_stage import TwoStageDetector
@DETECTORS.register_module()
class FasterRCNN(TwoStageDetector):
"""Implementation of `Faster R-CNN <https://arxiv.org/abs/1506.01497>`_"""
def __init__(self,
backbone,
rpn_head,
roi_hea... | 761 | 27.222222 | 78 | py |
DDOD | DDOD-main/mmdet/models/detectors/grid_rcnn.py | from ..builder import DETECTORS
from .two_stage import TwoStageDetector
@DETECTORS.register_module()
class GridRCNN(TwoStageDetector):
"""Grid R-CNN.
This detector is the implementation of:
- Grid R-CNN (https://arxiv.org/abs/1811.12030)
- Grid R-CNN Plus: Faster and Better (https://arxiv.org/abs/190... | 878 | 26.46875 | 75 | py |
DDOD | DDOD-main/mmdet/models/detectors/yolact.py | import torch
from mmdet.core import bbox2result
from ..builder import DETECTORS, build_head
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class YOLACT(SingleStageDetector):
"""Implementation of `YOLACT <https://arxiv.org/abs/1904.02689>`_"""
def __init__(self,
b... | 4,537 | 37.786325 | 79 | py |
DDOD | DDOD-main/mmdet/models/detectors/rpn.py | import warnings
import mmcv
import torch
from mmcv.image import tensor2imgs
from mmdet.core import bbox_mapping
from ..builder import DETECTORS, build_backbone, build_head, build_neck
from .base import BaseDetector
@DETECTORS.register_module()
class RPN(BaseDetector):
"""Implementation of Region Proposal Networ... | 5,897 | 37.051613 | 78 | py |
DDOD | DDOD-main/mmdet/models/detectors/trident_faster_rcnn.py | from ..builder import DETECTORS
from .faster_rcnn import FasterRCNN
@DETECTORS.register_module()
class TridentFasterRCNN(FasterRCNN):
"""Implementation of `TridentNet <https://arxiv.org/abs/1901.01892>`_"""
def __init__(self,
backbone,
rpn_head,
roi_head,
... | 2,725 | 38.507246 | 79 | py |
DDOD | DDOD-main/mmdet/models/detectors/retinanet.py | from ..builder import DETECTORS
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class RetinaNet(SingleStageDetector):
"""Implementation of `RetinaNet <https://arxiv.org/abs/1708.02002>`_"""
def __init__(self,
backbone,
neck,
bbox_h... | 607 | 31 | 77 | py |
DDOD | DDOD-main/mmdet/models/detectors/point_rend.py | from ..builder import DETECTORS
from .two_stage import TwoStageDetector
@DETECTORS.register_module()
class PointRend(TwoStageDetector):
"""PointRend: Image Segmentation as Rendering
This detector is the implementation of
`PointRend <https://arxiv.org/abs/1912.08193>`_.
"""
def __init__(self,
... | 836 | 25.15625 | 52 | py |
DDOD | DDOD-main/mmdet/models/detectors/atss.py | from ..builder import DETECTORS
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class ATSS(SingleStageDetector):
"""Implementation of `ATSS <https://arxiv.org/abs/1912.02424>`_."""
def __init__(self,
backbone,
neck,
bbox_head,
... | 588 | 30 | 72 | py |
DDOD | DDOD-main/mmdet/models/detectors/centernet.py | import torch
from mmdet.core import bbox2result
from mmdet.models.builder import DETECTORS
from ...core.utils import flip_tensor
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class CenterNet(SingleStageDetector):
"""Implementation of CenterNet(Objects as Points)
<https://arxiv.o... | 4,158 | 36.468468 | 79 | py |
DDOD | DDOD-main/mmdet/models/detectors/fcos.py | from ..builder import DETECTORS
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class FCOS(SingleStageDetector):
"""Implementation of `FCOS <https://arxiv.org/abs/1904.01355>`_"""
def __init__(self,
backbone,
neck,
bbox_head,
... | 587 | 29.947368 | 72 | py |
DDOD | DDOD-main/mmdet/models/detectors/fovea.py | from ..builder import DETECTORS
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class FOVEA(SingleStageDetector):
"""Implementation of `FoveaBox <https://arxiv.org/abs/1904.03797>`_"""
def __init__(self,
backbone,
neck,
bbox_head,
... | 594 | 30.315789 | 74 | py |
DDOD | DDOD-main/mmdet/models/detectors/htc.py | from ..builder import DETECTORS
from .cascade_rcnn import CascadeRCNN
@DETECTORS.register_module()
class HybridTaskCascade(CascadeRCNN):
"""Implementation of `HTC <https://arxiv.org/abs/1901.07518>`_"""
def __init__(self, **kwargs):
super(HybridTaskCascade, self).__init__(**kwargs)
@property
... | 450 | 27.1875 | 69 | py |
DDOD | DDOD-main/mmdet/models/detectors/__init__.py | from .atss import ATSS
from .autoassign import AutoAssign
from .base import BaseDetector
from .cascade_rcnn import CascadeRCNN
from .centernet import CenterNet
from .cornernet import CornerNet
from .deformable_detr import DeformableDETR
from .detr import DETR
from .fast_rcnn import FastRCNN
from .faster_rcnn import Fas... | 1,631 | 35.266667 | 77 | py |
DDOD | DDOD-main/mmdet/models/detectors/cornernet.py | import torch
from mmdet.core import bbox2result, bbox_mapping_back
from ..builder import DETECTORS
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class CornerNet(SingleStageDetector):
"""CornerNet.
This detector is the implementation of the paper `CornerNet: Detecting
Objects... | 3,620 | 36.329897 | 79 | py |
DDOD | DDOD-main/mmdet/models/detectors/vfnet.py | from ..builder import DETECTORS
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class VFNet(SingleStageDetector):
"""Implementation of `VarifocalNet
(VFNet).<https://arxiv.org/abs/2008.13367>`_"""
def __init__(self,
backbone,
neck,
... | 610 | 29.55 | 73 | py |
DDOD | DDOD-main/mmdet/models/detectors/sparse_rcnn.py | from ..builder import DETECTORS
from .two_stage import TwoStageDetector
@DETECTORS.register_module()
class SparseRCNN(TwoStageDetector):
r"""Implementation of `Sparse R-CNN: End-to-End Object Detection with
Learnable Proposals <https://arxiv.org/abs/2011.12450>`_"""
def __init__(self, *args, **kwargs):
... | 4,421 | 38.837838 | 78 | py |
DDOD | DDOD-main/mmdet/models/detectors/mask_scoring_rcnn.py | from ..builder import DETECTORS
from .two_stage import TwoStageDetector
@DETECTORS.register_module()
class MaskScoringRCNN(TwoStageDetector):
"""Mask Scoring RCNN.
https://arxiv.org/abs/1903.00241
"""
def __init__(self,
backbone,
rpn_head,
roi_head,... | 764 | 24.5 | 46 | py |
DDOD | DDOD-main/mmdet/models/detectors/yolof.py | from ..builder import DETECTORS
from .single_stage import SingleStageDetector
@DETECTORS.register_module()
class YOLOF(SingleStageDetector):
r"""Implementation of `You Only Look One-level Feature
<https://arxiv.org/abs/2103.09460>`_"""
def __init__(self,
backbone,
neck,
... | 580 | 29.578947 | 73 | py |
DDOD | DDOD-main/mmdet/models/necks/ssd_neck.py | import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmcv.runner import BaseModule
from ..builder import NECKS
@NECKS.register_module()
class SSDNeck(BaseModule):
"""Extra layers of SSD backbone to generate multi-scale feature maps.
Args:
in_channels ... | 4,843 | 36.550388 | 77 | py |
DDOD | DDOD-main/mmdet/models/necks/rfp.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import constant_init, xavier_init
from mmcv.runner import BaseModule, ModuleList
from ..builder import NECKS, build_backbone
from .fpn import FPN
class ASPP(BaseModule):
"""ASPP (Atrous Spatial Pyramid Pooling)
This is an imple... | 5,004 | 36.074074 | 78 | py |
DDOD | DDOD-main/mmdet/models/necks/dilated_encoder.py | import torch.nn as nn
from mmcv.cnn import (ConvModule, caffe2_xavier_init, constant_init, is_norm,
normal_init)
from torch.nn import BatchNorm2d
from ..builder import NECKS
class Bottleneck(nn.Module):
"""Bottleneck block for DilatedEncoder used in `YOLOF.
<https://arxiv.org/abs/2103.... | 3,820 | 34.37963 | 79 | py |
DDOD | DDOD-main/mmdet/models/necks/fpg.py | import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule
from ..builder import NECKS
class Transition(BaseModule):
"""Base class for transition.
Args:
in_channels (int): Number of input channels.
out_channels (int): Number of ou... | 16,290 | 39.125616 | 79 | py |
DDOD | DDOD-main/mmdet/models/necks/pafpn.py | import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmcv.runner import auto_fp16
from ..builder import NECKS
from .fpn import FPN
@NECKS.register_module()
class PAFPN(FPN):
"""Path Aggregation Network for Instance Segmentation.
This is an implementation of the `PAFPN i... | 6,203 | 38.265823 | 79 | py |
DDOD | DDOD-main/mmdet/models/necks/nasfcos_fpn.py | import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, caffe2_xavier_init
from mmcv.ops.merge_cells import ConcatCell
from mmcv.runner import BaseModule
from ..builder import NECKS
@NECKS.register_module()
class NASFCOS_FPN(BaseModule):
"""FPN structure in NASFPN.
Implementat... | 6,543 | 37.721893 | 79 | py |
DDOD | DDOD-main/mmdet/models/necks/fpn_carafe.py | import torch.nn as nn
from mmcv.cnn import ConvModule, build_upsample_layer, xavier_init
from mmcv.ops.carafe import CARAFEPack
from mmcv.runner import BaseModule, ModuleList
from ..builder import NECKS
@NECKS.register_module()
class FPN_CARAFE(BaseModule):
"""FPN_CARAFE is a more flexible implementation of FPN.... | 11,052 | 39.192727 | 79 | py |
DDOD | DDOD-main/mmdet/models/necks/ct_resnet_neck.py | import math
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule, auto_fp16
from mmdet.models.builder import NECKS
@NECKS.register_module()
class CTResNetNeck(BaseModule):
"""The neck used in `CenterNet <https://arxiv.org/abs/1904.07850>`_ for
object classification and bo... | 3,594 | 37.244681 | 77 | py |
DDOD | DDOD-main/mmdet/models/necks/fpn.py | import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule, auto_fp16
from ..builder import NECKS
@NECKS.register_module()
class FPN(BaseModule):
r"""Feature Pyramid Network.
This is an implementation of paper `Feature Pyramid Networks for Object... | 8,623 | 41.482759 | 79 | py |
DDOD | DDOD-main/mmdet/models/necks/nas_fpn.py | import torch.nn as nn
from mmcv.cnn import ConvModule
from mmcv.ops.merge_cells import GlobalPoolingCell, SumCell
from mmcv.runner import BaseModule, ModuleList
from ..builder import NECKS
@NECKS.register_module()
class NASFPN(BaseModule):
"""NAS-FPN.
Implementation of `NAS-FPN: Learning Scalable Feature Py... | 6,529 | 40.329114 | 79 | py |
DDOD | DDOD-main/mmdet/models/necks/__init__.py | from .bfp import BFP
from .channel_mapper import ChannelMapper
from .ct_resnet_neck import CTResNetNeck
from .dilated_encoder import DilatedEncoder
from .fpg import FPG
from .fpn import FPN
from .fpn_carafe import FPN_CARAFE
from .hrfpn import HRFPN
from .nas_fpn import NASFPN
from .nasfcos_fpn import NASFCOS_FPN
from ... | 612 | 28.190476 | 76 | py |
DDOD | DDOD-main/mmdet/models/necks/bfp.py | import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmcv.cnn.bricks import NonLocal2d
from mmcv.runner import BaseModule
from ..builder import NECKS
@NECKS.register_module()
class BFP(BaseModule):
"""BFP (Balanced Feature Pyramids)
BFP takes multi-level features as inputs and gather them in... | 3,729 | 35.568627 | 79 | py |
DDOD | DDOD-main/mmdet/models/necks/yolo_neck.py | # Copyright (c) 2019 Western Digital Corporation or its affiliates.
import torch
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule
from ..builder import NECKS
class DetectionBlock(BaseModule):
"""Detection block in YOLO neck.
Let out_channels = n, the Detect... | 5,383 | 37.457143 | 77 | py |
DDOD | DDOD-main/mmdet/models/necks/channel_mapper.py | import torch.nn as nn
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule
from ..builder import NECKS
@NECKS.register_module()
class ChannelMapper(BaseModule):
r"""Channel Mapper to reduce/increase channels of backbone features.
This is used to reduce/increase channels of backbone features.
... | 3,927 | 38.28 | 77 | py |
DDOD | DDOD-main/mmdet/models/necks/hrfpn.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule
from torch.utils.checkpoint import checkpoint
from ..builder import NECKS
@NECKS.register_module()
class HRFPN(BaseModule):
"""HRFPN (High Resolution Feature Pyramids)
paper:... | 3,461 | 33.62 | 79 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/nasfcos_head.py | import copy
import torch.nn as nn
from mmcv.cnn import ConvModule, Scale
from mmdet.models.dense_heads.fcos_head import FCOSHead
from ..builder import HEADS
@HEADS.register_module()
class NASFCOSHead(FCOSHead):
"""Anchor-free head used in `NASFCOS <https://arxiv.org/abs/1906.04423>`_.
It is quite similar w... | 2,860 | 34.7625 | 78 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/reppoints_head.py | import numpy as np
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmcv.ops import DeformConv2d
from mmdet.core import (build_assigner, build_sampler, images_to_levels,
multi_apply, multiclass_nms, unmap)
from mmdet.core.anchor.point_generator import MlvlPointGenerator
f... | 34,356 | 44.809333 | 101 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/cascade_rpn_head.py | from __future__ import division
import copy
import warnings
import torch
import torch.nn as nn
from mmcv import ConfigDict
from mmcv.ops import DeformConv2d, batched_nms
from mmcv.runner import BaseModule, ModuleList
from mmdet.core import (RegionAssigner, build_assigner, build_sampler,
images... | 33,320 | 41.339263 | 79 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/vfnet_head.py | import numpy as np
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, Scale
from mmcv.ops import DeformConv2d
from mmcv.runner import force_fp32
from mmdet.core import (bbox2distance, bbox_overlaps, build_anchor_generator,
build_assigner, build_sampler, distance2bbox,
... | 34,888 | 43.051768 | 79 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/centernet_head.py | import torch
import torch.nn as nn
from mmcv.cnn import bias_init_with_prob, normal_init
from mmcv.ops import batched_nms
from mmcv.runner import force_fp32
from mmdet.core import multi_apply
from mmdet.models import HEADS, build_loss
from mmdet.models.utils import gaussian_radius, gen_gaussian_target
from ..utils.gau... | 16,477 | 42.249344 | 79 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/fsaf_head.py | import numpy as np
import torch
from mmcv.runner import force_fp32
from mmdet.core import (anchor_inside_flags, images_to_levels, multi_apply,
unmap)
from ..builder import HEADS
from ..losses.accuracy import accuracy
from ..losses.utils import weight_reduce_loss
from .retina_head import RetinaH... | 19,290 | 43.551963 | 79 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/atss_head.py | import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, Scale
from mmcv.runner import force_fp32
from mmdet.core import (anchor_inside_flags, build_assigner, build_sampler,
images_to_levels, multi_apply, multiclass_nms,
reduce_mean, unmap)
from ..builder impo... | 30,349 | 43.306569 | 79 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/detr_head.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import Conv2d, Linear, build_activation_layer
from mmcv.cnn.bricks.transformer import FFN, build_positional_encoding
from mmcv.runner import force_fp32
from mmdet.core import (bbox_cxcywh_to_xyxy, bbox_xyxy_to_cxcywh,
... | 39,660 | 45.991706 | 79 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/rpn_head.py | import copy
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.ops import batched_nms
from mmcv.runner import force_fp32
from ..builder import HEADS
from .anchor_head import AnchorHead
@HEADS.register_module()
class RPNHead(AnchorHead):
"""RPN head.
Args:
in_channels (int)... | 14,140 | 43.190625 | 106 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/anchor_head.py | import torch
import torch.nn as nn
from mmcv.runner import force_fp32
from mmdet.core import (anchor_inside_flags, build_anchor_generator,
build_assigner, build_bbox_coder, build_sampler,
images_to_levels, multi_apply, multiclass_nms, unmap)
from ..builder import HEADS, ... | 34,469 | 45.206434 | 79 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/retina_head.py | import torch.nn as nn
from mmcv.cnn import ConvModule
from ..builder import HEADS
from .anchor_head import AnchorHead
@HEADS.register_module()
class RetinaHead(AnchorHead):
r"""An anchor-based head used in `RetinaNet
<https://arxiv.org/pdf/1708.02002.pdf>`_.
The head contains two subnetworks. The first ... | 4,003 | 33.817391 | 76 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/ga_rpn_head.py | import copy
import warnings
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv import ConfigDict
from mmcv.ops import nms
from ..builder import HEADS
from .guided_anchor_head import GuidedAnchorHead
@HEADS.register_module()
class GARPNHead(GuidedAnchorHead):
"""Guided-Anchor-based RPN ... | 7,039 | 38.774011 | 79 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/deformable_detr_head.py | import copy
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import Linear, bias_init_with_prob, constant_init
from mmcv.runner import force_fp32
from mmdet.core import multi_apply
from mmdet.models.utils.transformer import inverse_sigmoid
from ..builder import HEADS
from .detr_head im... | 13,680 | 42.022013 | 98 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/ga_retina_head.py | import torch.nn as nn
from mmcv.cnn import ConvModule
from mmcv.ops import MaskedConv2d
from ..builder import HEADS
from .guided_anchor_head import FeatureAdaption, GuidedAnchorHead
@HEADS.register_module()
class GARetinaHead(GuidedAnchorHead):
"""Guided-Anchor-based RetinaNet head."""
def __init__(self,
... | 3,875 | 33.300885 | 77 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/ld_head.py | import torch
from mmcv.runner import force_fp32
from mmdet.core import (bbox2distance, bbox_overlaps, distance2bbox,
multi_apply, reduce_mean)
from ..builder import HEADS, build_loss
from .gfl_head import GFLHead
@HEADS.register_module()
class LDHead(GFLHead):
"""Localization distillation... | 10,641 | 39.618321 | 79 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/ssd_head.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmcv.runner import force_fp32
from mmdet.core import (build_anchor_generator, build_assigner,
build_bbox_coder, build_sampler, multi_apply)
from ..builder import... | 14,425 | 40.693642 | 79 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/fcos_head.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import Scale
from mmcv.runner import force_fp32
from mmdet.core import distance2bbox, multi_apply, multiclass_nms, reduce_mean
from ..builder import HEADS, build_loss
from .anchor_free_head import AnchorFreeHead
INF = 1e8
@HEADS.regist... | 29,400 | 44.302003 | 113 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/yolo_head.py | # Copyright (c) 2019 Western Digital Corporation or its affiliates.
import warnings
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import (ConvModule, bias_init_with_prob, constant_init, is_norm,
normal_init)
from mmcv.runner import force_fp32
from mmdet.core i... | 27,175 | 42.621188 | 106 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/centripetal_head.py | import torch.nn as nn
from mmcv.cnn import ConvModule, normal_init
from mmcv.ops import DeformConv2d
from mmdet.core import multi_apply
from ..builder import HEADS, build_loss
from .corner_head import CornerHead
@HEADS.register_module()
class CentripetalHead(CornerHead):
"""Head of CentripetalNet: Pursuing High-... | 19,763 | 45.285714 | 79 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/paa_head.py | import numpy as np
import torch
from mmcv.runner import force_fp32
from mmdet.core import multi_apply, multiclass_nms
from mmdet.core.bbox.iou_calculators import bbox_overlaps
from mmdet.models import HEADS
from mmdet.models.dense_heads import ATSSHead
EPS = 1e-12
try:
import sklearn.mixture as skm
except ImportE... | 29,827 | 43.255193 | 79 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/retina_sepbn_head.py | import torch.nn as nn
from mmcv.cnn import ConvModule, bias_init_with_prob, normal_init
from ..builder import HEADS
from .anchor_head import AnchorHead
@HEADS.register_module()
class RetinaSepBNHead(AnchorHead):
""""RetinaHead with separate BN.
In RetinaHead, conv/norm layers are shared across different FPN... | 4,510 | 37.228814 | 79 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/anchor_free_head.py | from abc import abstractmethod
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmcv.runner import force_fp32
from mmdet.core import multi_apply
from ..builder import HEADS, build_loss
from .base_dense_head import BaseDenseHead
from .dense_test_mixins import BBoxTestMixin
@HEADS.register_modu... | 13,512 | 38.627566 | 79 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/pisa_ssd_head.py | import torch
from mmdet.core import multi_apply
from ..builder import HEADS
from ..losses import CrossEntropyLoss, SmoothL1Loss, carl_loss, isr_p
from .ssd_head import SSDHead
# TODO: add loss evaluator for SSD
@HEADS.register_module()
class PISASSDHead(SSDHead):
def loss(self,
cls_scores,
... | 5,551 | 38.657143 | 79 | py |
DDOD | DDOD-main/mmdet/models/dense_heads/embedding_rpn_head.py | import torch
import torch.nn as nn
from mmcv.runner import BaseModule
from mmdet.models.builder import HEADS
from ...core import bbox_cxcywh_to_xyxy
@HEADS.register_module()
class EmbeddingRPNHead(BaseModule):
"""RPNHead in the `Sparse R-CNN <https://arxiv.org/abs/2011.12450>`_ .
Unlike traditional RPNHead,... | 4,581 | 38.5 | 78 | py |
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