repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
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IAI | IAI-main/configs/iai/ytvis2021_iai_condinst_r50.py | # model settings
batch_size = 2
max_obj_num = 25
model = dict(
type='IAICondInst',
pretrained='torchvision://resnet50',
id_cfg=dict(num_frames=5, batch_size=batch_size, max_obj_num=max_obj_num),
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3... | 5,042 | 29.017857 | 96 | py |
IAI | IAI-main/configs/iai/ytvis2019_iai_condinst_r101.py | # model settings
batch_size = 2
max_obj_num = 20
model = dict(
type='IAICondInst',
id_cfg=dict(num_frames=5, batch_size=batch_size, max_obj_num=max_obj_num),
backbone=dict(
type='ResNet',
depth=101,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm... | 5,067 | 29.166667 | 96 | py |
IAI | IAI-main/configs/iai/ovis_iai_condinst_r50.py | # model settings
batch_size = 2
max_obj_num = 25
model = dict(
type='IAICondInst',
pretrained='torchvision://resnet50',
id_cfg=dict(num_frames=5, batch_size=batch_size, max_obj_num=max_obj_num),
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3... | 5,003 | 28.785714 | 87 | py |
IAI | IAI-main/configs/iai/ytvis2019_iai_condinst_r50.py | # model settings
batch_size = 4
max_obj_num = 20
model = dict(
type='IAICondInst',
pretrained='torchvision://resnet50',
id_cfg=dict(num_frames=5, batch_size=batch_size, max_obj_num=max_obj_num),
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3... | 5,063 | 29.142857 | 87 | py |
IAI | IAI-main/mmdet/apis/inference.py | import warnings
import mmcv
import numpy as np
import torch
from mmcv.ops import RoIPool
from mmcv.parallel import collate, scatter
from mmcv.runner import load_checkpoint
from mmdet.core import get_classes
from mmdet.datasets import replace_ImageToTensor
from mmdet.datasets.pipelines import Compose
from mmdet.models... | 7,242 | 32.224771 | 79 | py |
IAI | IAI-main/mmdet/apis/test.py | import os.path as osp
import pickle
import shutil
import tempfile
import time
import mmcv
import torch
import torch.distributed as dist
import numpy as np
from mmcv.image import tensor2imgs
from mmcv.runner import get_dist_info
import pycocotools.mask as mask_util
def single_gpu_test(model,
data_... | 6,156 | 33.205556 | 82 | py |
IAI | IAI-main/mmdet/apis/train.py | import random
import warnings
import numpy as np
import torch
from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
from mmcv.runner import (HOOKS, DistSamplerSeedHook, EpochBasedRunner,
Fp16OptimizerHook, OptimizerHook, build_optimizer,
build_runner)
fro... | 6,357 | 35.965116 | 79 | py |
IAI | IAI-main/mmdet/core/evaluation/eval_hooks.py | import os.path as osp
import warnings
from math import inf
import mmcv
import torch.distributed as dist
from mmcv.runner import Hook
from torch.nn.modules.batchnorm import _BatchNorm
from torch.utils.data import DataLoader
from mmdet.utils import get_root_logger
class EvalHook(Hook):
"""Evaluation hook.
No... | 12,485 | 40.072368 | 79 | py |
IAI | IAI-main/mmdet/core/post_processing/merge_augs.py | import copy
import warnings
import numpy as np
import torch
from mmcv import ConfigDict
from mmcv.ops import nms
from ..bbox import bbox_mapping_back
def merge_aug_proposals(aug_proposals, img_metas, cfg):
"""Merge augmented proposals (multiscale, flip, etc.)
Args:
aug_proposals (list[Tensor]): pro... | 5,605 | 36.125828 | 78 | py |
IAI | IAI-main/mmdet/core/post_processing/bbox_nms.py | import torch
from mmcv.ops.nms import batched_nms
from mmdet.core.bbox.iou_calculators import bbox_overlaps
def multiclass_nms(multi_bboxes,
multi_scores,
score_thr,
nms_cfg,
max_num=-1,
score_factors=None,
... | 6,269 | 36.100592 | 79 | py |
IAI | IAI-main/mmdet/core/mask/structures.py | from abc import ABCMeta, abstractmethod
import cv2
import mmcv
import numpy as np
import pycocotools.mask as maskUtils
import torch
from mmcv.ops.roi_align import roi_align
class BaseInstanceMasks(metaclass=ABCMeta):
"""Base class for instance masks."""
@abstractmethod
def rescale(self, scale, interpola... | 38,118 | 36.189268 | 141 | py |
IAI | IAI-main/mmdet/core/mask/mask_target.py | import numpy as np
import torch
from torch.nn.modules.utils import _pair
def mask_target(pos_proposals_list, pos_assigned_gt_inds_list, gt_masks_list,
cfg):
"""Compute mask target for positive proposals in multiple images.
Args:
pos_proposals_list (list[Tensor]): Positive proposals in... | 4,958 | 39.317073 | 78 | py |
IAI | IAI-main/mmdet/core/export/pytorch2onnx.py | from functools import partial
import mmcv
import numpy as np
import torch
from mmcv.runner import load_checkpoint
def generate_inputs_and_wrap_model(config_path,
checkpoint_path,
input_config,
cfg_options=None):
... | 5,779 | 36.290323 | 77 | py |
IAI | IAI-main/mmdet/core/export/__init__.py | from .pytorch2onnx import (build_model_from_cfg,
generate_inputs_and_wrap_model,
preprocess_example_input)
__all__ = [
'build_model_from_cfg', 'generate_inputs_and_wrap_model',
'preprocess_example_input'
]
| 269 | 29 | 61 | py |
IAI | IAI-main/mmdet/core/bbox/demodata.py | import numpy as np
import torch
from mmdet.utils.util_random import ensure_rng
def random_boxes(num=1, scale=1, rng=None):
"""Simple version of ``kwimage.Boxes.random``
Returns:
Tensor: shape (n, 4) in x1, y1, x2, y2 format.
References:
https://gitlab.kitware.com/computer-vision/kwimage... | 1,133 | 26 | 101 | py |
IAI | IAI-main/mmdet/core/bbox/transforms.py | import numpy as np
import torch
def bbox_flip(bboxes, img_shape, direction='horizontal'):
"""Flip bboxes horizontally or vertically.
Args:
bboxes (Tensor): Shape (..., 4*k)
img_shape (tuple): Image shape.
direction (str): Flip direction, options are "horizontal", "vertical",
... | 8,497 | 31.311787 | 79 | py |
IAI | IAI-main/mmdet/core/bbox/assigners/assign_result.py | import torch
from mmdet.utils import util_mixins
class AssignResult(util_mixins.NiceRepr):
"""Stores assignments between predicted and truth boxes.
Attributes:
num_gts (int): the number of truth boxes considered when computing this
assignment
gt_inds (LongTensor): for each predi... | 7,705 | 36.590244 | 79 | py |
IAI | IAI-main/mmdet/core/bbox/assigners/atss_assigner.py | import torch
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import build_iou_calculator
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
@BBOX_ASSIGNERS.register_module()
class ATSSAssigner(BaseAssigner):
"""Assign a corresponding gt bbox or background to each bbox.
... | 7,761 | 42.363128 | 87 | py |
IAI | IAI-main/mmdet/core/bbox/assigners/center_region_assigner.py | import torch
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import build_iou_calculator
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
def scale_boxes(bboxes, scale):
"""Expand an array of boxes by a given scale.
Args:
bboxes (Tensor): Shape (m, 4)
... | 15,429 | 44.922619 | 79 | py |
IAI | IAI-main/mmdet/core/bbox/assigners/region_assigner.py | import torch
from mmdet.core import anchor_inside_flags
from ..builder import BBOX_ASSIGNERS
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
def calc_region(bbox, ratio, stride, featmap_size=None):
"""Calculate region of the box defined by the ratio, the ratio is from the
cent... | 8,714 | 41.512195 | 79 | py |
IAI | IAI-main/mmdet/core/bbox/assigners/grid_assigner.py | import torch
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import build_iou_calculator
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
@BBOX_ASSIGNERS.register_module()
class GridAssigner(BaseAssigner):
"""Assign a corresponding gt bbox or background to each bbox.
... | 6,816 | 42.698718 | 79 | py |
IAI | IAI-main/mmdet/core/bbox/assigners/hungarian_assigner.py | import torch
from ..builder import BBOX_ASSIGNERS
from ..match_costs import build_match_cost
from ..transforms import bbox_cxcywh_to_xyxy
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
try:
from scipy.optimize import linear_sum_assignment
except ImportError:
linear_sum_assignm... | 6,617 | 44.328767 | 79 | py |
IAI | IAI-main/mmdet/core/bbox/assigners/point_assigner.py | import torch
from ..builder import BBOX_ASSIGNERS
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
@BBOX_ASSIGNERS.register_module()
class PointAssigner(BaseAssigner):
"""Assign a corresponding gt bbox or background to each point.
Each proposals will be assigned with `0`, or a... | 5,947 | 43.38806 | 79 | py |
IAI | IAI-main/mmdet/core/bbox/assigners/approx_max_iou_assigner.py | import torch
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import build_iou_calculator
from .max_iou_assigner import MaxIoUAssigner
@BBOX_ASSIGNERS.register_module()
class ApproxMaxIoUAssigner(MaxIoUAssigner):
"""Assign a corresponding gt bbox or background to each bbox.
Each proposals will be... | 6,649 | 44.547945 | 79 | py |
IAI | IAI-main/mmdet/core/bbox/assigners/max_iou_assigner.py | import torch
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import build_iou_calculator
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
@BBOX_ASSIGNERS.register_module()
class MaxIoUAssigner(BaseAssigner):
"""Assign a corresponding gt bbox or background to each bbox.
... | 9,750 | 44.779343 | 79 | py |
IAI | IAI-main/mmdet/core/bbox/match_costs/match_cost.py | import torch
from mmdet.core.bbox.iou_calculators import bbox_overlaps
from mmdet.core.bbox.transforms import bbox_cxcywh_to_xyxy, bbox_xyxy_to_cxcywh
from .builder import MATCH_COST
@MATCH_COST.register_module()
class BBoxL1Cost(object):
"""BBoxL1Cost.
Args:
weight (int | float, optional): loss_w... | 6,326 | 33.2 | 79 | py |
IAI | IAI-main/mmdet/core/bbox/coder/yolo_bbox_coder.py | import mmcv
import torch
from ..builder import BBOX_CODERS
from .base_bbox_coder import BaseBBoxCoder
@BBOX_CODERS.register_module()
class YOLOBBoxCoder(BaseBBoxCoder):
"""YOLO BBox coder.
Following `YOLO <https://arxiv.org/abs/1506.02640>`_, this coder divide
image into grids, and encode bbox (x1, y1, ... | 3,487 | 37.755556 | 77 | py |
IAI | IAI-main/mmdet/core/bbox/coder/bucketing_bbox_coder.py | import mmcv
import numpy as np
import torch
import torch.nn.functional as F
from ..builder import BBOX_CODERS
from ..transforms import bbox_rescale
from .base_bbox_coder import BaseBBoxCoder
@BBOX_CODERS.register_module()
class BucketingBBoxCoder(BaseBBoxCoder):
"""Bucketing BBox Coder for Side-Aware Boundary Lo... | 14,071 | 39.091168 | 79 | py |
IAI | IAI-main/mmdet/core/bbox/coder/pseudo_bbox_coder.py | from ..builder import BBOX_CODERS
from .base_bbox_coder import BaseBBoxCoder
@BBOX_CODERS.register_module()
class PseudoBBoxCoder(BaseBBoxCoder):
"""Pseudo bounding box coder."""
def __init__(self, **kwargs):
super(BaseBBoxCoder, self).__init__(**kwargs)
def encode(self, bboxes, gt_bboxes):
... | 529 | 26.894737 | 60 | py |
IAI | IAI-main/mmdet/core/bbox/coder/tblr_bbox_coder.py | import mmcv
import torch
from ..builder import BBOX_CODERS
from .base_bbox_coder import BaseBBoxCoder
@BBOX_CODERS.register_module()
class TBLRBBoxCoder(BaseBBoxCoder):
"""TBLR BBox coder.
Following the practice in `FSAF <https://arxiv.org/abs/1903.00621>`_,
this coder encodes gt bboxes (x1, y1, x2, y2)... | 8,208 | 40.251256 | 78 | py |
IAI | IAI-main/mmdet/core/bbox/coder/legacy_delta_xywh_bbox_coder.py | import mmcv
import numpy as np
import torch
from ..builder import BBOX_CODERS
from .base_bbox_coder import BaseBBoxCoder
@BBOX_CODERS.register_module()
class LegacyDeltaXYWHBBoxCoder(BaseBBoxCoder):
"""Legacy Delta XYWH BBox coder used in MMDet V1.x.
Following the practice in R-CNN [1]_, this coder encodes ... | 8,209 | 37.009259 | 79 | py |
IAI | IAI-main/mmdet/core/bbox/coder/delta_xywh_bbox_coder.py | import mmcv
import numpy as np
import torch
from ..builder import BBOX_CODERS
from .base_bbox_coder import BaseBBoxCoder
@BBOX_CODERS.register_module()
class DeltaXYWHBBoxCoder(BaseBBoxCoder):
"""Delta XYWH BBox coder.
Following the practice in `R-CNN <https://arxiv.org/abs/1311.2524>`_,
this coder enco... | 9,282 | 38.004202 | 79 | py |
IAI | IAI-main/mmdet/core/bbox/iou_calculators/iou2d_calculator.py | import torch
from .builder import IOU_CALCULATORS
@IOU_CALCULATORS.register_module()
class BboxOverlaps2D(object):
"""2D Overlaps (e.g. IoUs, GIoUs) Calculator."""
def __call__(self, bboxes1, bboxes2, mode='iou', is_aligned=False):
"""Calculate IoU between 2D bboxes.
Args:
bboxe... | 6,182 | 37.64375 | 78 | py |
IAI | IAI-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 |
IAI | IAI-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 |
IAI | IAI-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... | 2,817 | 34.670886 | 76 | py |
IAI | IAI-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 |
IAI | IAI-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 |
IAI | IAI-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 |
IAI | IAI-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 |
IAI | IAI-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 |
IAI | IAI-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 |
IAI | IAI-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
... | 1,865 | 29.096774 | 79 | py |
IAI | IAI-main/mmdet/core/anchor/point_generator.py | import torch
from .builder import ANCHOR_GENERATORS
@ANCHOR_GENERATORS.register_module()
class PointGenerator(object):
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_major:
return xx, yy
else:
... | 1,362 | 34.868421 | 70 | py |
IAI | IAI-main/mmdet/core/anchor/anchor_generator.py | import mmcv
import numpy as np
import torch
from torch.nn.modules.utils import _pair
from .builder import ANCHOR_GENERATORS
@ANCHOR_GENERATORS.register_module()
class AnchorGenerator(object):
"""Standard anchor generator for 2D anchor-based detectors.
Args:
strides (list[int] | list[tuple[int, int]]... | 31,185 | 41.837912 | 79 | py |
IAI | IAI-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 |
IAI | IAI-main/mmdet/models/builder.py | import warnings
from mmcv.utils import Registry, build_from_cfg
from torch import nn
BACKBONES = Registry('backbone')
NECKS = Registry('neck')
ROI_EXTRACTORS = Registry('roi_extractor')
SHARED_HEADS = Registry('shared_head')
HEADS = Registry('head')
LOSSES = Registry('loss')
DETECTORS = Registry('detector')
def bui... | 2,094 | 25.858974 | 78 | py |
IAI | IAI-main/mmdet/models/detectors/two_stage.py | import torch
import torch.nn as nn
# from mmdet.core import bbox2result, bbox2roi, build_assigner, build_sampler
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 de... | 7,658 | 34.458333 | 79 | py |
IAI | IAI-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
import torch.nn as nn
from mmcv.runner import auto_fp16
from mmcv.utils import print_log
from mmdet.core.visualization import imshow_det_bboxes
from mmdet.utils impo... | 14,245 | 39.016854 | 79 | py |
IAI | IAI-main/mmdet/models/detectors/single_stage.py | import torch
import torch.nn as nn
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 ... | 5,999 | 37.709677 | 78 | py |
IAI | IAI-main/mmdet/models/detectors/detr.py | from mmdet.core import bbox2result
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__(se... | 1,738 | 36 | 78 | py |
IAI | IAI-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 |
IAI | IAI-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... | 6,129 | 40.70068 | 79 | py |
IAI | IAI-main/mmdet/models/detectors/utils.py | import torch
import torch.nn.functional as F
def aligned_bilinear(tensor, factor):
assert tensor.dim() == 4
assert factor >= 1
assert int(factor) == factor
if factor == 1:
return tensor
h, w = tensor.size()[2:]
tensor = F.pad(tensor, pad=(0, 1, 0, 1), mode="replicate")
oh = factor ... | 6,438 | 37.556886 | 109 | py |
IAI | IAI-main/mmdet/models/detectors/rpn.py | import mmcv
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 Network."""
def __init__(self,
... | 5,811 | 36.496774 | 78 | py |
IAI | IAI-main/mmdet/models/detectors/iai_condinst.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from mmdet.core import bbox2roi
from ..builder import DETECTORS, build_head, build_neck, build_roi_extractor, build_loss
from .single_stage import SingleStageDetector
from .utils import split_frames, process_id, get_new_masks, aligned_bilinear
import p... | 11,970 | 38.508251 | 131 | py |
IAI | IAI-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... | 3,578 | 36.28125 | 79 | py |
IAI | IAI-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 |
IAI | IAI-main/mmdet/models/lstt_block/gct.py | import torch
import torch.nn.functional as F
import math
from torch import nn
class GCT(nn.Module):
def __init__(self, num_channels, epsilon=1e-5, mode='l2', after_relu=False):
super(GCT, self).__init__()
self.alpha = nn.Parameter(torch.ones(1, num_channels, 1, 1))
self.gamma = nn.Paramete... | 3,056 | 32.593407 | 100 | py |
IAI | IAI-main/mmdet/models/lstt_block/lstt.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from mmcv.runner import ModuleList
from mmdet.models.builder import HEADS
from mmcv.runner import BaseModule, auto_fp16, force_fp32
from .transformer import LongShortTermTransformer
from .position import PositionEmbeddingSine
from ... | 9,510 | 34.755639 | 131 | py |
IAI | IAI-main/mmdet/models/lstt_block/position.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import math
class Downsample2D(nn.Module):
def __init__(self, mode='nearest', scale=4):
super().__init__()
self.mode = mode
self.scale = scale
def forward(self, x):
n, c, h, w = x.size()
x = F.interpol... | 3,334 | 33.381443 | 103 | py |
IAI | IAI-main/mmdet/models/lstt_block/transformer.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import nn, Tensor
import copy
from .basic import DropPath, GroupNorm1D, GNActGCTDWConv2d, seq_to_2d
from .gct import GCT
def _get_norm(indim, type='ln', groups=8):
if type == 'gn':
return GroupNorm1D(indim, groups)
else:
... | 17,978 | 33.91068 | 162 | py |
IAI | IAI-main/mmdet/models/lstt_block/basic.py | import torch
import torch.nn.functional as F
import math
from torch import nn
from .gct import GCT
class GroupNorm1D(nn.Module):
def __init__(self, indim, groups=8):
super().__init__()
self.gn = nn.GroupNorm(groups, indim)
def forward(self, x):
return self.gn(x.permute(1, 2, 0)).permut... | 2,886 | 33.369048 | 108 | py |
IAI | IAI-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, kaiming_init, xavier_init
from ..builder import NECKS, build_backbone
from .fpn import FPN
class ASPP(nn.Module):
"""ASPP (Atrous Spatial Pyramid Pooling)
This is an implementation of the ASPP module used ... | 4,592 | 34.604651 | 78 | py |
IAI | IAI-main/mmdet/models/necks/fpg.py | import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, caffe2_xavier_init, constant_init, is_norm
from ..builder import NECKS
class Transition(nn.Module):
"""Base class for transition.
Args:
in_channels (int): Number of input channels.
out_channels (int): Numb... | 15,923 | 38.909774 | 79 | py |
IAI | IAI-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... | 5,713 | 38.958042 | 79 | py |
IAI | IAI-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 ..builder import NECKS
@NECKS.register_module()
class NASFCOS_FPN(nn.Module):
"""FPN structure in NASFPN.
Implementation of paper `NAS-FCOS: Fast Neural ... | 6,164 | 37.055556 | 79 | py |
IAI | IAI-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 ..builder import NECKS
@NECKS.register_module()
class FPN_CARAFE(nn.Module):
"""FPN_CARAFE is a more flexible implementation of FPN. It allows more
choice for upsample methods ... | 10,671 | 38.820896 | 79 | py |
IAI | IAI-main/mmdet/models/necks/fpn.py | import warnings
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, xavier_init
from mmcv.runner import auto_fp16
from ..builder import NECKS
@NECKS.register_module()
class FPN(nn.Module):
r"""Feature Pyramid Network.
This is an implementation of paper `Feature Pyramid Ne... | 9,466 | 41.644144 | 79 | py |
IAI | IAI-main/mmdet/models/necks/nas_fpn.py | import torch.nn as nn
from mmcv.cnn import ConvModule, caffe2_xavier_init
from mmcv.ops.merge_cells import GlobalPoolingCell, SumCell
from ..builder import NECKS
@NECKS.register_module()
class NASFPN(nn.Module):
"""NAS-FPN.
Implementation of `NAS-FPN: Learning Scalable Feature Pyramid Architecture
for O... | 6,539 | 39.621118 | 79 | py |
IAI | IAI-main/mmdet/models/necks/bfp.py | import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, xavier_init
from mmcv.cnn.bricks import NonLocal2d
from ..builder import NECKS
@NECKS.register_module()
class BFP(nn.Module):
"""BFP (Balanced Feature Pyramids)
BFP takes multi-level features as inputs and gather them int... | 3,744 | 34.666667 | 79 | py |
IAI | IAI-main/mmdet/models/necks/yolo_neck.py | # Copyright (c) 2019 Western Digital Corporation or its affiliates.
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from ..builder import NECKS
class DetectionBlock(nn.Module):
"""Detection block in YOLO neck.
Let out_channels = n, the DetectionBlock conta... | 5,089 | 36.153285 | 77 | py |
IAI | IAI-main/mmdet/models/necks/channel_mapper.py | import torch.nn as nn
from mmcv.cnn import ConvModule, xavier_init
from ..builder import NECKS
@NECKS.register_module()
class ChannelMapper(nn.Module):
r"""Channel Mapper to reduce/increase channels of backbone features.
This is used to reduce/increase channels of backbone features.
Args:
in_ch... | 2,765 | 35.88 | 76 | py |
IAI | IAI-main/mmdet/models/necks/hrfpn.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, caffe2_xavier_init
from torch.utils.checkpoint import checkpoint
from ..builder import NECKS
@NECKS.register_module()
class HRFPN(nn.Module):
"""HRFPN (High Resolution Feature Pyramids)
paper: `High-Resolutio... | 3,480 | 32.796117 | 79 | py |
IAI | IAI-main/mmdet/models/dense_heads/nasfcos_head.py | import copy
import torch.nn as nn
from mmcv.cnn import (ConvModule, Scale, bias_init_with_prob,
caffe2_xavier_init, normal_init)
from mmdet.models.dense_heads.fcos_head import FCOSHead
from ..builder import HEADS
@HEADS.register_module()
class NASFCOSHead(FCOSHead):
"""Anchor-free head use... | 2,793 | 35.763158 | 78 | py |
IAI | IAI-main/mmdet/models/dense_heads/reppoints_head.py | import numpy as np
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, bias_init_with_prob, normal_init
from mmcv.ops import DeformConv2d
from mmdet.core import (PointGenerator, build_assigner, build_sampler,
images_to_levels, multi_apply, multiclass_nms, unmap)
from ..builder i... | 35,305 | 45.212042 | 101 | py |
IAI | IAI-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.cnn import normal_init
from mmcv.ops import DeformConv2d, batched_nms
from mmdet.core import (RegionAssigner, build_assigner, build_sampler,
images_to_levels, mu... | 32,988 | 41.024204 | 79 | py |
IAI | IAI-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, bias_init_with_prob, normal_init
from mmcv.ops import DeformConv2d
from mmcv.runner import force_fp32
from mmdet.core import (bbox2distance, bbox_overlaps, build_anchor_generator,
build_assigner, build... | 35,403 | 43.533333 | 79 | py |
IAI | IAI-main/mmdet/models/dense_heads/fsaf_head.py | import numpy as np
import torch
from mmcv.cnn import normal_init
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... | 18,883 | 43.643026 | 79 | py |
IAI | IAI-main/mmdet/models/dense_heads/atss_head.py | import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, Scale, bias_init_with_prob, normal_init
from mmcv.runner import force_fp32
from mmdet.core import (anchor_inside_flags, build_assigner, build_sampler,
images_to_levels, multi_apply, multiclass_nms,
reduc... | 30,511 | 43.22029 | 79 | py |
IAI | IAI-main/mmdet/models/dense_heads/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.cnn import normal_init
from mmcv.ops import batched_nms
from ..builder import HEADS
from .anchor_head import AnchorHead
from .rpn_test_mixin import RPNTestMixin
@HEADS.register_module... | 10,616 | 43.797468 | 79 | py |
IAI | IAI-main/mmdet/models/dense_heads/anchor_head.py | import torch
import torch.nn as nn
from mmcv.cnn import normal_init
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, unm... | 34,125 | 44.806711 | 79 | py |
IAI | IAI-main/mmdet/models/dense_heads/retina_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 RetinaHead(AnchorHead):
r"""An anchor-based head used in `RetinaNet
<https://arxiv.org/pdf/1708.02002.pdf>`_.
The head co... | 4,051 | 34.234783 | 76 | py |
IAI | IAI-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.cnn import normal_init
from mmcv.ops import nms
from ..builder import HEADS
from .guided_anchor_head import GuidedAnchorHead
from .rpn_test_mixin import RPNTestMixin
@HEADS.register_m... | 6,896 | 39.098837 | 79 | py |
IAI | IAI-main/mmdet/models/dense_heads/ga_retina_head.py | import torch.nn as nn
from mmcv.cnn import ConvModule, bias_init_with_prob, normal_init
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 h... | 3,876 | 34.245455 | 78 | py |
IAI | IAI-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 |
IAI | IAI-main/mmdet/models/dense_heads/utils.py | import torch
import torch.nn.functional as F
from mmcv.ops.nms import batched_nms
def multiclass_nms(multi_bboxes,
multi_cls_scores,
multi_id_scores,
multi_kernels,
multi_points,
multi_strides,
cls_score_... | 4,617 | 34.251908 | 85 | py |
IAI | IAI-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 xavier_init
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 HEADS
from ..losses import s... | 11,038 | 40.5 | 79 | py |
IAI | IAI-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, normal_init
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
... | 28,339 | 43.984127 | 113 | py |
IAI | IAI-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, normal_init
from mmcv.runner import force_fp32
from mmdet.core import (build_anchor_generator, build_assigner,
... | 24,983 | 42.224913 | 79 | py |
IAI | IAI-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-... | 19,469 | 45.137441 | 79 | py |
IAI | IAI-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... | 29,706 | 43.206845 | 79 | py |
IAI | IAI-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... | 4,288 | 36.622807 | 79 | py |
IAI | IAI-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, bias_init_with_prob, normal_init
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 BB... | 13,496 | 38.580645 | 79 | py |
IAI | IAI-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 |
IAI | IAI-main/mmdet/models/dense_heads/embedding_rpn_head.py | import torch
import torch.nn as nn
from mmdet.models.builder import HEADS
from ...core import bbox_cxcywh_to_xyxy
@HEADS.register_module()
class EmbeddingRPNHead(nn.Module):
"""RPNHead in the `Sparse R-CNN <https://arxiv.org/abs/2011.12450>`_ .
Unlike traditional RPNHead, this module does not need FPN input... | 3,916 | 37.782178 | 78 | py |
IAI | IAI-main/mmdet/models/dense_heads/pisa_retinanet_head.py | import torch
from mmcv.runner import force_fp32
from mmdet.core import images_to_levels
from ..builder import HEADS
from ..losses import carl_loss, isr_p
from .retina_head import RetinaHead
@HEADS.register_module()
class PISARetinaHead(RetinaHead):
"""PISA Retinanet Head.
The head owns the same structure wi... | 6,220 | 39.135484 | 79 | py |
IAI | IAI-main/mmdet/models/dense_heads/gfl_head.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, Scale, bias_init_with_prob, normal_init
from mmcv.runner import force_fp32
from mmdet.core import (anchor_inside_flags, bbox2distance, bbox_overlaps,
build_assigner, build_sampler, distance2bbox,... | 28,062 | 42.307099 | 79 | py |
IAI | IAI-main/mmdet/models/dense_heads/corner_head.py | from logging import warning
from math import ceil, log
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, bias_init_with_prob
from mmcv.ops import CornerPool, batched_nms
from mmdet.core import multi_apply
from ..builder import HEADS, build_loss
from ..utils import gau... | 46,589 | 42.339535 | 79 | py |
IAI | IAI-main/mmdet/models/dense_heads/yolact_head.py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, xavier_init
from mmcv.runner import force_fp32
from mmdet.core import build_sampler, fast_nms, images_to_levels, multi_apply
from ..builder import HEADS, build_loss
from .anchor_head import AnchorHead... | 39,679 | 41.033898 | 79 | py |
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