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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UniControl | UniControl-main/annotator/uniformer/mmseg/models/decode_heads/gc_head.py | import torch
from annotator.uniformer.mmcv.cnn import ContextBlock
from ..builder import HEADS
from .fcn_head import FCNHead
@HEADS.register_module()
class GCHead(FCNHead):
"""GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond.
This head is the implementation of `GCNet
<https://arxiv.... | 1,611 | 32.583333 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/decode_heads/point_head.py | # Modified from https://github.com/facebookresearch/detectron2/tree/master/projects/PointRend/point_head/point_head.py # noqa
import torch
import torch.nn as nn
from annotator.uniformer.mmcv.cnn import ConvModule, normal_init
from annotator.uniformer.mmcv.ops import point_sample
from annotator.uniformer.mmseg.models... | 14,754 | 41.157143 | 126 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/utils/se_layer.py | import annotator.uniformer.mmcv as mmcv
import torch.nn as nn
from annotator.uniformer.mmcv.cnn import ConvModule
from .make_divisible import make_divisible
class SELayer(nn.Module):
"""Squeeze-and-Excitation Module.
Args:
channels (int): The input (and output) channels of the SE layer.
rati... | 2,151 | 36.103448 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/utils/weight_init.py | """Modified from https://github.com/rwightman/pytorch-image-
models/blob/master/timm/models/layers/drop.py."""
import math
import warnings
import torch
def _no_grad_trunc_normal_(tensor, mean, std, a, b):
"""Reference: https://people.sc.fsu.edu/~jburkardt/presentations
/truncated_normal.pdf"""
def norm... | 2,327 | 35.952381 | 76 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/utils/res_layer.py | from annotator.uniformer.mmcv.cnn import build_conv_layer, build_norm_layer
from torch import nn as nn
class ResLayer(nn.Sequential):
"""ResLayer to build ResNet style backbone.
Args:
block (nn.Module): block used to build ResLayer.
inplanes (int): inplanes of block.
planes (int): pla... | 3,335 | 34.115789 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/utils/self_attention_block.py | import torch
from annotator.uniformer.mmcv.cnn import ConvModule, constant_init
from torch import nn as nn
from torch.nn import functional as F
class SelfAttentionBlock(nn.Module):
"""General self-attention block/non-local block.
Please refer to https://arxiv.org/abs/1706.03762 for details about key,
que... | 6,145 | 37.4125 | 78 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/utils/up_conv_block.py | import torch
import torch.nn as nn
from annotator.uniformer.mmcv.cnn import ConvModule, build_upsample_layer
class UpConvBlock(nn.Module):
"""Upsample convolution block in decoder for UNet.
This upsample convolution block consists of one upsample module
followed by one convolution block. The upsample mod... | 3,988 | 38.107843 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/utils/inverted_residual.py | from annotator.uniformer.mmcv.cnn import ConvModule
from torch import nn
from torch.utils import checkpoint as cp
from .se_layer import SELayer
class InvertedResidual(nn.Module):
"""InvertedResidual block for MobileNetV2.
Args:
in_channels (int): The input channels of the InvertedResidual block.
... | 7,025 | 32.617225 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/utils/drop.py | """Modified from https://github.com/rwightman/pytorch-image-
models/blob/master/timm/models/layers/drop.py."""
import torch
from torch import nn
class DropPath(nn.Module):
"""Drop paths (Stochastic Depth) per sample (when applied in main path of
residual blocks).
Args:
drop_prob (float): Drop r... | 1,015 | 30.75 | 78 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/segmentors/base.py | import logging
import warnings
from abc import ABCMeta, abstractmethod
from collections import OrderedDict
import annotator.uniformer.mmcv as mmcv
import numpy as np
import torch
import torch.distributed as dist
import torch.nn as nn
from annotator.uniformer.mmcv.runner import auto_fp16
class BaseSegmentor(nn.Module... | 10,398 | 36.952555 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/segmentors/cascade_encoder_decoder.py | from torch import nn
from annotator.uniformer.mmseg.core import add_prefix
from annotator.uniformer.mmseg.ops import resize
from .. import builder
from ..builder import SEGMENTORS
from .encoder_decoder import EncoderDecoder
@SEGMENTORS.register_module()
class CascadeEncoderDecoder(EncoderDecoder):
"""Cascade Enc... | 3,708 | 36.464646 | 78 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/segmentors/encoder_decoder.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from annotator.uniformer.mmseg.core import add_prefix
from annotator.uniformer.mmseg.ops import resize
from .. import builder
from ..builder import SEGMENTORS
from .base import BaseSegmentor
@SEGMENTORS.register_module()
class EncoderDecoder(BaseSegm... | 11,344 | 36.943144 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/losses/dice_loss.py | """Modified from https://github.com/LikeLy-Journey/SegmenTron/blob/master/
segmentron/solver/loss.py (Apache-2.0 License)"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from ..builder import LOSSES
from .utils import get_class_weight, weighted_loss
@weighted_loss
def dice_loss(pred,
... | 4,239 | 34.333333 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/losses/lovasz_loss.py | """Modified from https://github.com/bermanmaxim/LovaszSoftmax/blob/master/pytor
ch/lovasz_losses.py Lovasz-Softmax and Jaccard hinge loss in PyTorch Maxim
Berman 2018 ESAT-PSI KU Leuven (MIT License)"""
import annotator.uniformer.mmcv as mmcv
import torch
import torch.nn as nn
import torch.nn.functional as F
from ..b... | 11,419 | 36.565789 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/losses/utils.py | import functools
import annotator.uniformer.mmcv as mmcv
import numpy as np
import torch.nn.functional as F
def get_class_weight(class_weight):
"""Get class weight for loss function.
Args:
class_weight (list[float] | str | None): If class_weight is a str,
take it as a file name and read ... | 3,718 | 29.483607 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/losses/accuracy.py | import torch.nn as nn
def accuracy(pred, target, topk=1, thresh=None):
"""Calculate accuracy according to the prediction and target.
Args:
pred (torch.Tensor): The model prediction, shape (N, num_class, ...)
target (torch.Tensor): The target of each prediction, shape (N, , ...)
topk (... | 2,970 | 36.607595 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/losses/cross_entropy_loss.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from ..builder import LOSSES
from .utils import get_class_weight, weight_reduce_loss
def cross_entropy(pred,
label,
weight=None,
class_weight=None,
reduction='mean',
... | 7,437 | 36.376884 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/backbones/hrnet.py | import torch.nn as nn
from annotator.uniformer.mmcv.cnn import (build_conv_layer, build_norm_layer, constant_init,
kaiming_init)
from annotator.uniformer.mmcv.runner import load_checkpoint
from annotator.uniformer.mmcv.utils.parrots_wrapper import _BatchNorm
from annotator.uniformer.mmseg.ops imp... | 21,226 | 37.178058 | 92 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/backbones/mobilenet_v2.py | import logging
import torch.nn as nn
from annotator.uniformer.mmcv.cnn import ConvModule, constant_init, kaiming_init
from annotator.uniformer.mmcv.runner import load_checkpoint
from torch.nn.modules.batchnorm import _BatchNorm
from ..builder import BACKBONES
from ..utils import InvertedResidual, make_divisible
@BA... | 6,981 | 37.574586 | 80 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/backbones/fast_scnn.py | import torch
import torch.nn as nn
from annotator.uniformer.mmcv.cnn import (ConvModule, DepthwiseSeparableConvModule, constant_init,
kaiming_init)
from torch.nn.modules.batchnorm import _BatchNorm
from annotator.uniformer.mmseg.models.decode_heads.psp_head import PPM
from annotator.uniformer.mms... | 14,436 | 37.396277 | 98 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/backbones/resnet.py | import torch.nn as nn
import torch.utils.checkpoint as cp
from annotator.uniformer.mmcv.cnn import (build_conv_layer, build_norm_layer, build_plugin_layer,
constant_init, kaiming_init)
from annotator.uniformer.mmcv.runner import load_checkpoint
from annotator.uniformer.mmcv.utils.parrots_wrapper i... | 24,310 | 34.28447 | 97 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/backbones/cgnet.py | import torch
import torch.nn as nn
import torch.utils.checkpoint as cp
from annotator.uniformer.mmcv.cnn import (ConvModule, build_conv_layer, build_norm_layer,
constant_init, kaiming_init)
from annotator.uniformer.mmcv.runner import load_checkpoint
from annotator.uniformer.mmcv.utils.parrots_wrap... | 13,183 | 34.826087 | 89 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/backbones/vit.py | """Modified from https://github.com/rwightman/pytorch-image-
models/blob/master/timm/models/vision_transformer.py."""
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as cp
from annotator.uniformer.mmcv.cnn import (Conv2d, Linear, build_activation_layer, bui... | 18,085 | 38.317391 | 128 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/backbones/resnext.py | import math
from annotator.uniformer.mmcv.cnn import build_conv_layer, build_norm_layer
from ..builder import BACKBONES
from ..utils import ResLayer
from .resnet import Bottleneck as _Bottleneck
from .resnet import ResNet
class Bottleneck(_Bottleneck):
"""Bottleneck block for ResNeXt.
If style is "pytorch"... | 5,161 | 34.356164 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/backbones/mobilenet_v3.py | import logging
import annotator.uniformer.mmcv as mmcv
import torch.nn as nn
from annotator.uniformer.mmcv.cnn import ConvModule, constant_init, kaiming_init
from annotator.uniformer.mmcv.cnn.bricks import Conv2dAdaptivePadding
from annotator.uniformer.mmcv.runner import load_checkpoint
from torch.nn.modules.batchnorm... | 10,390 | 39.589844 | 80 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/backbones/unet.py | import torch.nn as nn
import torch.utils.checkpoint as cp
from annotator.uniformer.mmcv.cnn import (UPSAMPLE_LAYERS, ConvModule, build_activation_layer,
build_norm_layer, constant_init, kaiming_init)
from annotator.uniformer.mmcv.runner import load_checkpoint
from annotator.uniformer.mmcv.utils.pa... | 18,269 | 41.488372 | 94 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/backbones/resnest.py | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as cp
from annotator.uniformer.mmcv.cnn import build_conv_layer, build_norm_layer
from ..builder import BACKBONES
from ..utils import ResLayer
from .resnet import Bottleneck as _Bottleneck
from .resnet import ... | 10,110 | 31.098413 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/models/backbones/uniformer.py | # --------------------------------------------------------
# UniFormer
# Copyright (c) 2022 SenseTime X-Lab
# Licensed under The MIT License [see LICENSE for details]
# Written by Kunchang Li
# --------------------------------------------------------
from collections import OrderedDict
import math
from functools impo... | 18,476 | 42.680851 | 145 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/datasets/custom.py | import os
import os.path as osp
from collections import OrderedDict
from functools import reduce
import annotator.uniformer.mmcv as mmcv
import numpy as np
from annotator.uniformer.mmcv.utils import print_log
from prettytable import PrettyTable
from torch.utils.data import Dataset
from annotator.uniformer.mmseg.core ... | 14,716 | 35.700748 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/datasets/dataset_wrappers.py | from torch.utils.data.dataset import ConcatDataset as _ConcatDataset
from .builder import DATASETS
@DATASETS.register_module()
class ConcatDataset(_ConcatDataset):
"""A wrapper of concatenated dataset.
Same as :obj:`torch.utils.data.dataset.ConcatDataset`, but
concat the group flag for image aspect rati... | 1,499 | 28.411765 | 78 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/datasets/builder.py | import copy
import platform
import random
from functools import partial
import numpy as np
from annotator.uniformer.mmcv.parallel import collate
from annotator.uniformer.mmcv.runner import get_dist_info
from annotator.uniformer.mmcv.utils import Registry, build_from_cfg
from annotator.uniformer.mmcv.utils.parrots_wrap... | 5,951 | 34.011765 | 85 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/datasets/pipelines/formating.py | from collections.abc import Sequence
import annotator.uniformer.mmcv as mmcv
import numpy as np
import torch
from annotator.uniformer.mmcv.parallel import DataContainer as DC
from ..builder import PIPELINES
def to_tensor(data):
"""Convert objects of various python types to :obj:`torch.Tensor`.
Supported ty... | 9,276 | 31.100346 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/ops/wrappers.py | import warnings
import torch.nn as nn
import torch.nn.functional as F
def resize(input,
size=None,
scale_factor=None,
mode='nearest',
align_corners=None,
warning=True):
if warning:
if size is not None and align_corners:
input_h, input_w =... | 1,827 | 34.843137 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmseg/ops/encoding.py | import torch
from torch import nn
from torch.nn import functional as F
class Encoding(nn.Module):
"""Encoding Layer: a learnable residual encoder.
Input is of shape (batch_size, channels, height, width).
Output is of shape (batch_size, num_codes, channels).
Args:
channels: dimension of the ... | 2,788 | 36.186667 | 78 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/apis/inference.py | import warnings
import annotator.uniformer.mmcv as mmcv
import numpy as np
import torch
# from annotator.uniformer.mmcv.ops import RoIPool
from annotator.uniformer.mmcv.parallel import collate, scatter
from annotator.uniformer.mmcv.runner import load_checkpoint
from annotator.uniformer.mmdet.core import get_classes
... | 7,413 | 32.853881 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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
from mmcv.image import tensor2imgs
from mmcv.runner import get_dist_info
from mmdet.core import encode_mask_results
def single_gpu_test(model,
data_loader,
... | 6,826 | 34.743455 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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... | 6,899 | 36.096774 | 102 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/core/evaluation/eval_hooks.py | import os.path as osp
import warnings
from math import inf
import annotator.uniformer.mmcv as mmcv
import torch.distributed as dist
from annotator.uniformer.mmcv.runner import Hook
from torch.nn.modules.batchnorm import _BatchNorm
from torch.utils.data import DataLoader
from annotator.uniformer.mmdet.utils import get... | 12,553 | 40.296053 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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",
... | 7,899 | 31.780083 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/core/bbox/assigners/assign_result.py | import torch
from annotator.uniformer.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 (LongTen... | 7,725 | 36.687805 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/core/bbox/assigners/region_assigner.py | import torch
from annotator.uniformer.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 ... | 9,432 | 41.490991 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/core/bbox/match_costs/match_cost.py | import torch
from annotator.uniformer.mmdet.core.bbox.iou_calculators import bbox_overlaps
from annotator.uniformer.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:
... | 6,366 | 33.416216 | 99 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/core/bbox/coder/yolo_bbox_coder.py | import annotator.uniformer.mmcv as 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 grid... | 3,515 | 38.066667 | 77 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/core/bbox/coder/bucketing_bbox_coder.py | import annotator.uniformer.mmcv as 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 Code... | 14,099 | 39.17094 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/core/bbox/coder/tblr_bbox_coder.py | import annotator.uniformer.mmcv as 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 encode... | 8,236 | 40.39196 | 78 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/core/bbox/coder/legacy_delta_xywh_bbox_coder.py | import annotator.uniformer.mmcv as 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-C... | 8,237 | 37.138889 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/core/bbox/coder/delta_xywh_bbox_coder.py | import annotator.uniformer.mmcv as 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.... | 9,310 | 38.121849 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/core/bbox/samplers/score_hlr_sampler.py | import torch
from annotator.uniformer.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 ... | 11,207 | 41.29434 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/core/bbox/samplers/sampling_result.py | import torch
from annotator.uniformer.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)
... | 5,354 | 34 | 81 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/core/anchor/anchor_generator.py | import annotator.uniformer.mmcv as 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[... | 31,213 | 41.876374 | 79 | py |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
UniControl | UniControl-main/annotator/uniformer/mmdet_null/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 |
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