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
value |
|---|---|---|---|---|---|---|
LineFormer | LineFormer-main/mmdetection/configs/detr/detr_r50_8x2_150e_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py', '../_base_/default_runtime.py'
]
model = dict(
type='DETR',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(3, ),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=False),
norm... | 5,858 | 37.801325 | 79 | py |
LineFormer | LineFormer-main/mmdetection/configs/atss/atss_r101_fpn_1x_coco.py | _base_ = './atss_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 192 | 26.571429 | 61 | py |
LineFormer | LineFormer-main/mmdetection/configs/atss/atss_r50_fpn_1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
type='ATSS',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=d... | 1,925 | 29.571429 | 79 | py |
LineFormer | LineFormer-main/mmdetection/configs/ld/ld_r101_gflv1_r101dcn_fpn_coco_2x.py | _base_ = ['./ld_r18_gflv1_r101_fpn_coco_1x.py']
teacher_ckpt = 'https://download.openmmlab.com/mmdetection/v2.0/gfl/gfl_r101_fpn_dconv_c3-c5_mstrain_2x_coco/gfl_r101_fpn_dconv_c3-c5_mstrain_2x_coco_20200630_102002-134b07df.pth' # noqa
model = dict(
teacher_config='configs/gfl/gfl_r101_fpn_dconv_c3-c5_mstrain_2x_co... | 1,628 | 35.2 | 187 | py |
LineFormer | LineFormer-main/mmdetection/configs/ld/ld_r34_gflv1_r101_fpn_coco_1x.py | _base_ = ['./ld_r18_gflv1_r101_fpn_coco_1x.py']
model = dict(
backbone=dict(
type='ResNet',
depth=34,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
init_c... | 569 | 27.5 | 79 | py |
LineFormer | LineFormer-main/mmdetection/configs/ld/ld_r18_gflv1_r101_fpn_coco_1x.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
teacher_ckpt = 'https://download.openmmlab.com/mmdetection/v2.0/gfl/gfl_r101_fpn_mstrain_2x_coco/gfl_r101_fpn_mstrain_2x_coco_20200629_200126-dd12f847.pth' # noqa
model = dict(
type='Kn... | 2,120 | 32.666667 | 163 | py |
LineFormer | LineFormer-main/mmdetection/configs/ld/ld_r50_gflv1_r101_fpn_coco_1x.py | _base_ = ['./ld_r18_gflv1_r101_fpn_coco_1x.py']
model = dict(
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
init_c... | 572 | 27.65 | 79 | py |
LineFormer | LineFormer-main/mmdetection/configs/seesaw_loss/cascade_mask_rcnn_r101_fpn_sample1e-3_seesaw_loss_mstrain_2x_lvis_v1.py | _base_ = [
'../_base_/models/cascade_mask_rcnn_r50_fpn.py',
'../_base_/datasets/lvis_v1_instance.py',
'../_base_/schedules/schedule_2x.py', '../_base_/default_runtime.py'
]
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvi... | 3,783 | 37.222222 | 79 | py |
LineFormer | LineFormer-main/mmdetection/configs/seesaw_loss/mask_rcnn_r101_fpn_sample1e-3_seesaw_loss_mstrain_2x_lvis_v1.py | _base_ = './mask_rcnn_r50_fpn_sample1e-3_seesaw_loss_mstrain_2x_lvis_v1.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 231 | 32.142857 | 75 | py |
LineFormer | LineFormer-main/mmdetection/configs/seesaw_loss/mask_rcnn_r101_fpn_random_seesaw_loss_mstrain_2x_lvis_v1.py | _base_ = './mask_rcnn_r50_fpn_random_seesaw_loss_mstrain_2x_lvis_v1.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 227 | 31.571429 | 71 | py |
LineFormer | LineFormer-main/mmdetection/configs/seesaw_loss/mask_rcnn_r101_fpn_sample1e-3_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py | _base_ = './mask_rcnn_r50_fpn_sample1e-3_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py' # noqa: E501
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 257 | 35.857143 | 101 | py |
LineFormer | LineFormer-main/mmdetection/configs/seesaw_loss/mask_rcnn_r101_fpn_random_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py | _base_ = './mask_rcnn_r50_fpn_random_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py' # noqa: E501
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 253 | 35.285714 | 97 | py |
LineFormer | LineFormer-main/mmdetection/configs/seesaw_loss/cascade_mask_rcnn_r101_fpn_random_seesaw_loss_mstrain_2x_lvis_v1.py | _base_ = [
'../_base_/models/cascade_mask_rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_2x.py', '../_base_/default_runtime.py'
]
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvisio... | 4,807 | 35.150376 | 79 | py |
LineFormer | LineFormer-main/mmdetection/configs/tood/tood_x101_64x4d_fpn_mstrain_2x_coco.py | _base_ = './tood_r50_fpn_mstrain_2x_coco.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True... | 447 | 25.352941 | 76 | py |
LineFormer | LineFormer-main/mmdetection/configs/tood/tood_r50_fpn_1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
type='TOOD',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=d... | 2,306 | 29.76 | 79 | py |
LineFormer | LineFormer-main/mmdetection/configs/tood/tood_r101_fpn_mstrain_2x_coco.py | _base_ = './tood_r50_fpn_mstrain_2x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 201 | 24.25 | 61 | py |
LineFormer | LineFormer-main/mmdetection/configs/dyhead/atss_r50_fpn_dyhead_1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
type='ATSS',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=d... | 2,043 | 29.969697 | 79 | py |
LineFormer | LineFormer-main/mmdetection/configs/dyhead/atss_r50_caffe_fpn_dyhead_1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
type='ATSS',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=d... | 3,608 | 30.938053 | 73 | py |
LineFormer | LineFormer-main/mmdetection/configs/gn+ws/faster_rcnn_x50_32x4d_fpn_gn_ws-all_1x_coco.py | _base_ = './faster_rcnn_r50_fpn_gn_ws-all_1x_coco.py'
conv_cfg = dict(type='ConvWS')
norm_cfg = dict(type='GN', num_groups=32, requires_grad=True)
model = dict(
backbone=dict(
type='ResNeXt',
depth=50,
groups=32,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
... | 544 | 27.684211 | 66 | py |
LineFormer | LineFormer-main/mmdetection/configs/gn+ws/mask_rcnn_x101_32x4d_fpn_gn_ws-all_2x_coco.py | _base_ = './mask_rcnn_r50_fpn_gn_ws-all_2x_coco.py'
# model settings
conv_cfg = dict(type='ConvWS')
norm_cfg = dict(type='GN', num_groups=32, requires_grad=True)
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
base_width=4,
num_stages=4,
out_indices... | 561 | 27.1 | 67 | py |
LineFormer | LineFormer-main/mmdetection/configs/gn+ws/faster_rcnn_x101_32x4d_fpn_gn_ws-all_1x_coco.py | _base_ = './faster_rcnn_r50_fpn_gn_ws-all_1x_coco.py'
conv_cfg = dict(type='ConvWS')
norm_cfg = dict(type='GN', num_groups=32, requires_grad=True)
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
... | 546 | 27.789474 | 67 | py |
LineFormer | LineFormer-main/mmdetection/configs/gn+ws/mask_rcnn_x50_32x4d_fpn_gn_ws-all_2x_coco.py | _base_ = './mask_rcnn_r50_fpn_gn_ws-all_2x_coco.py'
# model settings
conv_cfg = dict(type='ConvWS')
norm_cfg = dict(type='GN', num_groups=32, requires_grad=True)
model = dict(
backbone=dict(
type='ResNeXt',
depth=50,
groups=32,
base_width=4,
num_stages=4,
out_indices=... | 559 | 27 | 66 | py |
LineFormer | LineFormer-main/mmdetection/configs/guided_anchoring/ga_faster_x101_64x4d_fpn_1x_coco.py | _base_ = './ga_faster_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
style='pytorch',
... | 419 | 27 | 76 | py |
LineFormer | LineFormer-main/mmdetection/configs/guided_anchoring/ga_faster_x101_32x4d_fpn_1x_coco.py | _base_ = './ga_faster_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
style='pytorch',
... | 419 | 27 | 76 | py |
LineFormer | LineFormer-main/mmdetection/configs/guided_anchoring/ga_retinanet_x101_32x4d_fpn_1x_coco.py | _base_ = './ga_retinanet_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
style='pytorch'... | 422 | 27.2 | 76 | py |
LineFormer | LineFormer-main/mmdetection/configs/guided_anchoring/ga_rpn_x101_32x4d_fpn_1x_coco.py | _base_ = './ga_rpn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
style='pytorch',
... | 416 | 26.8 | 76 | py |
LineFormer | LineFormer-main/mmdetection/configs/guided_anchoring/ga_rpn_r101_caffe_fpn_1x_coco.py | _base_ = './ga_rpn_r50_caffe_fpn_1x_coco.py'
# model settings
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://detectron2/resnet101_caffe')))
| 236 | 25.333333 | 67 | py |
LineFormer | LineFormer-main/mmdetection/configs/guided_anchoring/ga_retinanet_x101_64x4d_fpn_1x_coco.py | _base_ = './ga_retinanet_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
style='pytorch'... | 422 | 27.2 | 76 | py |
LineFormer | LineFormer-main/mmdetection/configs/guided_anchoring/ga_faster_r101_caffe_fpn_1x_coco.py | _base_ = './ga_faster_r50_caffe_fpn_1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://detectron2/resnet101_caffe')))
| 222 | 26.875 | 67 | py |
LineFormer | LineFormer-main/mmdetection/configs/guided_anchoring/ga_rpn_x101_64x4d_fpn_1x_coco.py | _base_ = './ga_rpn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
style='pytorch',
... | 416 | 26.8 | 76 | py |
LineFormer | LineFormer-main/mmdetection/configs/guided_anchoring/ga_fast_r50_caffe_fpn_1x_coco.py | _base_ = '../fast_rcnn/fast_rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=False),
norm_eval=True,
style='caffe',
in... | 2,407 | 35.484848 | 78 | py |
LineFormer | LineFormer-main/mmdetection/configs/guided_anchoring/ga_faster_r50_caffe_fpn_1x_coco.py | _base_ = '../faster_rcnn/faster_rcnn_r50_caffe_fpn_1x_coco.py'
model = dict(
rpn_head=dict(
_delete_=True,
type='GARPNHead',
in_channels=256,
feat_channels=256,
approx_anchor_generator=dict(
type='AnchorGenerator',
octave_base_scale=8,
scal... | 2,408 | 35.5 | 77 | py |
LineFormer | LineFormer-main/mmdetection/configs/guided_anchoring/ga_retinanet_r101_caffe_fpn_1x_coco.py | _base_ = './ga_retinanet_r50_caffe_fpn_1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://detectron2/resnet101_caffe')))
| 225 | 27.25 | 67 | py |
LineFormer | LineFormer-main/mmdetection/configs/guided_anchoring/ga_retinanet_r50_caffe_fpn_1x_coco.py | _base_ = '../retinanet/retinanet_r50_caffe_fpn_1x_coco.py'
model = dict(
bbox_head=dict(
_delete_=True,
type='GARetinaHead',
num_classes=80,
in_channels=256,
stacked_convs=4,
feat_channels=256,
approx_anchor_generator=dict(
type='AnchorGenerator',
... | 2,055 | 31.634921 | 74 | py |
LineFormer | LineFormer-main/mmdetection/configs/guided_anchoring/ga_retinanet_r101_caffe_fpn_mstrain_2x.py | _base_ = '../_base_/default_runtime.py'
# model settings
model = dict(
type='RetinaNet',
backbone=dict(
type='ResNet',
depth=101,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=False),
norm_eval=True,
... | 5,095 | 28.976471 | 74 | py |
LineFormer | LineFormer-main/mmdetection/configs/guided_anchoring/ga_rpn_r50_caffe_fpn_1x_coco.py | _base_ = '../rpn/rpn_r50_caffe_fpn_1x_coco.py'
model = dict(
rpn_head=dict(
_delete_=True,
type='GARPNHead',
in_channels=256,
feat_channels=256,
approx_anchor_generator=dict(
type='AnchorGenerator',
octave_base_scale=8,
scales_per_octave=3,... | 2,028 | 33.389831 | 74 | py |
LineFormer | LineFormer-main/mmdetection/configs/solov2/solov2_light_r34_fpn_3x_coco.py | _base_ = 'solov2_light_r50_fpn_3x_coco.py'
# model settings
model = dict(
backbone=dict(
depth=34, init_cfg=dict(checkpoint='torchvision://resnet34')),
neck=dict(in_channels=[64, 128, 256, 512]))
| 213 | 25.75 | 70 | py |
LineFormer | LineFormer-main/mmdetection/configs/solov2/solov2_r50_fpn_1x_coco.py | _base_ = [
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# model settings
model = dict(
type='SOLOv2',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,... | 1,825 | 28.451613 | 78 | py |
LineFormer | LineFormer-main/mmdetection/configs/solov2/solov2_r101_dcn_fpn_3x_coco.py | _base_ = 'solov2_r50_fpn_3x_coco.py'
# model settings
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(checkpoint='torchvision://resnet101'),
dcn=dict(type='DCNv2', deformable_groups=1, fallback_on_stride=False),
stage_with_dcn=(False, True, True, True)),
mask_head=dict(
... | 452 | 31.357143 | 78 | py |
LineFormer | LineFormer-main/mmdetection/configs/solov2/solov2_light_r18_fpn_3x_coco.py | _base_ = 'solov2_light_r50_fpn_3x_coco.py'
# model settings
model = dict(
backbone=dict(
depth=18, init_cfg=dict(checkpoint='torchvision://resnet18')),
neck=dict(in_channels=[64, 128, 256, 512]))
| 213 | 25.75 | 70 | py |
LineFormer | LineFormer-main/mmdetection/configs/solov2/solov2_r101_fpn_3x_coco.py | _base_ = 'solov2_r50_fpn_3x_coco.py'
# model settings
model = dict(
backbone=dict(
depth=101, init_cfg=dict(checkpoint='torchvision://resnet101')))
| 161 | 22.142857 | 72 | py |
LineFormer | LineFormer-main/mmdetection/configs/convnext/cascade_mask_rcnn_convnext-t_p4_w7_fpn_giou_4conv1f_fp16_ms-crop_3x_coco.py | _base_ = [
'../_base_/models/cascade_mask_rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# please install mmcls>=0.22.0
# import mmcls.models to trigger register_module in mmcls
custom_imports = dict(imports=['mmcls.models'], ... | 5,693 | 36.96 | 162 | py |
LineFormer | LineFormer-main/mmdetection/configs/convnext/mask_rcnn_convnext-t_p4_w7_fpn_fp16_ms-crop_3x_coco.py | _base_ = [
'../_base_/models/mask_rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# please install mmcls>=0.22.0
# import mmcls.models to trigger register_module in mmcls
custom_imports = dict(imports=['mmcls.models'], allow_fa... | 3,419 | 36.582418 | 162 | py |
LineFormer | LineFormer-main/mmdetection/configs/lad/lad_r50_paa_r101_fpn_coco_1x.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
teacher_ckpt = 'http://download.openmmlab.com/mmdetection/v2.0/paa/paa_r101_fpn_1x_coco/paa_r101_fpn_1x_coco_20200821-0a1825a4.pth' # noqa
model = dict(
type='LAD',
# student
ba... | 3,906 | 30.007937 | 139 | py |
LineFormer | LineFormer-main/mmdetection/configs/lad/lad_r101_paa_r50_fpn_coco_1x.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
teacher_ckpt = 'https://download.openmmlab.com/mmdetection/v2.0/paa/paa_r50_fpn_1x_coco/paa_r50_fpn_1x_coco_20200821-936edec3.pth' # noqa
model = dict(
type='LAD',
# student
bac... | 3,928 | 29.937008 | 138 | py |
LineFormer | LineFormer-main/mmdetection/configs/sparse_rcnn/sparse_rcnn_r101_fpn_mstrain_480-800_3x_coco.py | _base_ = './sparse_rcnn_r50_fpn_mstrain_480-800_3x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 216 | 26.125 | 61 | py |
LineFormer | LineFormer-main/mmdetection/configs/sparse_rcnn/sparse_rcnn_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco.py | _base_ = './sparse_rcnn_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 235 | 28.5 | 78 | py |
LineFormer | LineFormer-main/mmdetection/configs/sparse_rcnn/sparse_rcnn_r50_fpn_1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
num_stages = 6
num_proposals = 100
model = dict(
type='SparseRCNN',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
... | 3,469 | 35.145833 | 79 | py |
LineFormer | LineFormer-main/mmdetection/docs/en/conf.py | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... | 3,439 | 28.401709 | 79 | py |
LineFormer | LineFormer-main/mmdetection/docs/zh_cn/conf.py | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... | 3,461 | 28.092437 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/apis/inference.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
from pathlib import Path
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_Ima... | 8,629 | 32.449612 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/apis/test.py | # Copyright (c) OpenMMLab. All rights reserved.
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_t... | 7,817 | 36.228571 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/apis/train.py | # Copyright (c) OpenMMLab. All rights reserved.
import os
import random
import numpy as np
import torch
import torch.distributed as dist
from mmcv.runner import (DistSamplerSeedHook, EpochBasedRunner,
Fp16OptimizerHook, OptimizerHook, build_runner,
get_dist_info)
from... | 8,379 | 32.927126 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/evaluation/eval_hooks.py | # Copyright (c) OpenMMLab. All rights reserved.
import bisect
import os.path as osp
import mmcv
import torch.distributed as dist
from mmcv.runner import DistEvalHook as BaseDistEvalHook
from mmcv.runner import EvalHook as BaseEvalHook
from torch.nn.modules.batchnorm import _BatchNorm
def _calc_dynamic_intervals(star... | 5,604 | 38.751773 | 76 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/post_processing/merge_augs.py | # Copyright (c) OpenMMLab. All rights reserved.
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.)
... | 5,790 | 36.36129 | 78 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/post_processing/bbox_nms.py | # Copyright (c) OpenMMLab. All rights reserved.
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,
... | 6,495 | 36.767442 | 78 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/post_processing/matrix_nms.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
def mask_matrix_nms(masks,
labels,
scores,
filter_thr=-1,
nms_pre=-1,
max_num=-1,
kernel='gaussian',
sigma=2.0,
... | 4,622 | 36.893443 | 77 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/mask/structures.py | # Copyright (c) OpenMMLab. All rights reserved.
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."""
@abstr... | 41,496 | 36.62194 | 141 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/mask/mask_target.py | # Copyright (c) OpenMMLab. All rights reserved.
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_prop... | 5,115 | 38.96875 | 78 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/mask/utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import numpy as np
import pycocotools.mask as mask_util
import torch
def split_combined_polys(polys, poly_lens, polys_per_mask):
"""Split the combined 1-D polys into masks.
A mask is represented as a list of polys, and a poly is represented as
a... | 3,017 | 32.533333 | 75 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/hook/sync_random_size_hook.py | # Copyright (c) OpenMMLab. All rights reserved.
import random
import warnings
import torch
from mmcv.runner import get_dist_info
from mmcv.runner.hooks import HOOKS, Hook
from torch import distributed as dist
@HOOKS.register_module()
class SyncRandomSizeHook(Hook):
"""Change and synchronize the random image size... | 3,061 | 40.945205 | 78 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/hook/checkloss_hook.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmcv.runner.hooks import HOOKS, Hook
@HOOKS.register_module()
class CheckInvalidLossHook(Hook):
"""Check invalid loss hook.
This hook will regularly check whether the loss is valid
during training.
Args:
interval (int): Checki... | 681 | 26.28 | 66 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/hook/sync_norm_hook.py | # Copyright (c) OpenMMLab. All rights reserved.
from collections import OrderedDict
from mmcv.runner import get_dist_info
from mmcv.runner.hooks import HOOKS, Hook
from torch import nn
from ..utils.dist_utils import all_reduce_dict
def get_norm_states(module):
async_norm_states = OrderedDict()
for name, chi... | 1,789 | 32.773585 | 77 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/export/model_wrappers.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import warnings
import numpy as np
import torch
from mmdet.core import bbox2result
from mmdet.models import BaseDetector
class DeployBaseDetector(BaseDetector):
"""DeployBaseDetector."""
def __init__(self, class_names, device_id):
... | 7,469 | 39.597826 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/export/pytorch2onnx.py | # Copyright (c) OpenMMLab. All rights reserved.
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,
... | 5,995 | 36.475 | 78 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/export/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .onnx_helper import (add_dummy_nms_for_onnx, dynamic_clip_for_onnx,
get_k_for_topk)
from .pytorch2onnx import (build_model_from_cfg,
generate_inputs_and_wrap_model,
preprocess_example_inp... | 505 | 37.923077 | 75 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/export/onnx_helper.py | # Copyright (c) OpenMMLab. All rights reserved.
import os
import torch
def dynamic_clip_for_onnx(x1, y1, x2, y2, max_shape):
"""Clip boxes dynamically for onnx.
Since torch.clamp cannot have dynamic `min` and `max`, we scale the
boxes by 1/max_shape and clamp in the range [0, 1].
Args:
x1... | 8,367 | 36.357143 | 98 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/demodata.py | # Copyright (c) OpenMMLab. All rights reserved.
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:
ht... | 1,181 | 26.488372 | 101 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/transforms.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
def find_inside_bboxes(bboxes, img_h, img_w):
"""Find bboxes as long as a part of bboxes is inside the image.
Args:
bboxes (Tensor): Shape (N, 4).
img_h (int): Image height.
img_w (int): Image width.
... | 8,962 | 32.073801 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/assigners/assign_result.py | # Copyright (c) OpenMMLab. All rights reserved.
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
assignme... | 7,761 | 36.497585 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/assigners/sim_ota_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import torch
import torch.nn.functional as F
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import bbox_overlaps
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
@BBOX_ASSIGNERS.register_module()
class SimOTA... | 11,495 | 43.55814 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/assigners/atss_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
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):
... | 10,174 | 42.297872 | 87 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/assigners/center_region_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
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.
A... | 15,477 | 44.928783 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/assigners/region_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
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 defi... | 9,473 | 41.484305 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/assigners/grid_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
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 corr... | 6,863 | 42.719745 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/assigners/mask_hungarian_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from scipy.optimize import linear_sum_assignment
from mmdet.core.bbox.builder import BBOX_ASSIGNERS
from mmdet.core.bbox.match_costs.builder import build_match_cost
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
@BBOX_ASSIG... | 5,312 | 41.166667 | 77 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/assigners/hungarian_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from scipy.optimize import linear_sum_assignment
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
@B... | 6,439 | 45 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/assigners/task_aligned_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import build_iou_calculator
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
INF = 100000000
@BBOX_ASSIGNERS.register_module()
class TaskAlignedAssigner(BaseAssigne... | 6,554 | 42.125 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/assigners/uniform_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import build_iou_calculator
from ..transforms import bbox_xyxy_to_cxcywh
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
@BBOX_ASSIGNERS.register_module()
class Uni... | 5,556 | 39.860294 | 77 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/assigners/point_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
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.
... | 5,995 | 43.414815 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/assigners/approx_max_iou_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
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 back... | 6,697 | 44.564626 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/assigners/max_iou_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
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 co... | 10,168 | 45.43379 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/assigners/ascend_max_iou_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from ....utils import masked_fill
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import build_iou_calculator
from .ascend_assign_result import AscendAssignResult
from .base_assigner import BaseAssigner
@BBOX_ASSIGNERS.register_module()
class A... | 8,841 | 48.396648 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/match_costs/match_cost.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn.functional as F
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:
""... | 12,651 | 34.144444 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/coder/yolo_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
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... | 3,252 | 37.72619 | 77 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/coder/distance_point_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
from ..builder import BBOX_CODERS
from ..transforms import bbox2distance, distance2bbox
from .base_bbox_coder import BaseBBoxCoder
@BBOX_CODERS.register_module()
class DistancePointBBoxCoder(BaseBBoxCoder):
"""Distance Point BBox coder.
This coder encodes gt bb... | 2,481 | 37.78125 | 78 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/coder/bucketing_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
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):
""... | 14,119 | 39.113636 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/coder/pseudo_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
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... | 577 | 27.9 | 60 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/coder/tblr_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
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>`_,
... | 8,625 | 40.671498 | 78 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/coder/legacy_delta_xywh_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
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... | 8,257 | 37.0553 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/coder/delta_xywh_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
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 i... | 15,978 | 39.659033 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/iou_calculators/iou2d_calculator.py | # Copyright (c) OpenMMLab. All rights reserved.
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_cud... | 9,602 | 35.793103 | 78 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/samplers/instance_balanced_pos_sampler.py | # Copyright (c) OpenMMLab. All rights reserved.
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 sample... | 2,319 | 39.701754 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/samplers/mask_sampling_result.py | # Copyright (c) OpenMMLab. All rights reserved.
"""copy from
https://github.com/ZwwWayne/K-Net/blob/main/knet/det/mask_pseudo_sampler.py."""
import torch
from .sampling_result import SamplingResult
class MaskSamplingResult(SamplingResult):
"""Mask sampling result."""
def __init__(self, pos_inds, neg_inds, ... | 2,031 | 32.311475 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/samplers/base_sampler.py | # Copyright (c) OpenMMLab. All rights reserved.
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_p... | 3,920 | 37.067961 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/samplers/random_sampler.py | # Copyright (c) OpenMMLab. All rights reserved.
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 po... | 3,071 | 36.012048 | 78 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/samplers/ohem_sampler.py | # Copyright (c) OpenMMLab. All rights reserved.
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
... | 4,221 | 36.696429 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/samplers/iou_balanced_neg_sampler.py | # Copyright (c) OpenMMLab. All rights reserved.
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 (CV... | 6,740 | 41.396226 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/samplers/mask_pseudo_sampler.py | # Copyright (c) OpenMMLab. All rights reserved.
"""copy from
https://github.com/ZwwWayne/K-Net/blob/main/knet/det/mask_pseudo_sampler.py."""
import torch
from mmdet.core.bbox.builder import BBOX_SAMPLERS
from .base_sampler import BaseSampler
from .mask_sampling_result import MaskSamplingResult
@BBOX_SAMPLERS.regist... | 1,583 | 34.2 | 79 | py |
LineFormer | LineFormer-main/mmdetection/mmdet/core/bbox/samplers/score_hlr_sampler.py | # Copyright (c) OpenMMLab. All rights reserved.
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):
... | 11,235 | 41.240602 | 79 | py |
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