repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
value |
|---|---|---|---|---|---|---|
PseCo | PseCo-master/thirdparty/mmdetection/configs/mask_rcnn/mask_rcnn_x101_32x4d_fpn_1x_coco.py | _base_ = './mask_rcnn_r101_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',
... | 420 | 27.066667 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/mask_rcnn/mask_rcnn_x101_64x4d_fpn_mstrain-poly_3x_coco.py | _base_ = [
'../common/mstrain-poly_3x_coco_instance.py',
'../_base_/models/mask_rcnn_r50_fpn.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_c... | 485 | 24.578947 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/mask_rcnn/mask_rcnn_r101_fpn_mstrain-poly_3x_coco.py | _base_ = [
'../common/mstrain-poly_3x_coco_instance.py',
'../_base_/models/mask_rcnn_r50_fpn.py'
]
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 263 | 23 | 61 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/mask_rcnn/mask_rcnn_x101_64x4d_fpn_1x_coco.py | _base_ = './mask_rcnn_x101_32x4d_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='pyto... | 426 | 27.466667 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/mask_rcnn/mask_rcnn_r50_fpn_2x_coco.py | _base_ = [
'../_base_/models/mask_rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_2x.py', '../_base_/default_runtime.py'
]
| 174 | 28.166667 | 72 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/mask_rcnn/mask_rcnn_r101_caffe_fpn_mstrain-poly_3x_coco.py | _base_ = [
'../common/mstrain-poly_3x_coco_instance.py',
'../_base_/models/mask_rcnn_r50_fpn.py'
]
model = dict(
backbone=dict(
depth=101,
norm_cfg=dict(requires_grad=False),
norm_eval=True,
style='caffe',
init_cfg=dict(
type='Pretrained',
che... | 1,660 | 28.660714 | 77 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_mstrain-poly_3x_coco.py | _base_ = './mask_rcnn_r50_caffe_fpn_mstrain-poly_1x_coco.py'
# learning policy
lr_config = dict(step=[28, 34])
runner = dict(type='EpochBasedRunner', max_epochs=36)
| 165 | 32.2 | 60 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/mask_rcnn/mask_rcnn_r50_fpn_mstrain-poly_3x_coco.py | _base_ = [
'../common/mstrain-poly_3x_coco_instance.py',
'../_base_/models/mask_rcnn_r50_fpn.py'
]
| 107 | 20.6 | 49 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_1x_coco.py | _base_ = './mask_rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(requires_grad=False),
style='caffe',
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://detectron2/resnet50_caffe')))
# use caffe img_norm
img_norm_cfg = dict(
mean=[103.5... | 1,412 | 33.463415 | 77 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/pisa/pisa_retinanet_x101_32x4d_fpn_1x_coco.py | _base_ = '../retinanet/retinanet_x101_32x4d_fpn_1x_coco.py'
model = dict(
bbox_head=dict(
type='PISARetinaHead',
loss_bbox=dict(type='SmoothL1Loss', beta=0.11, loss_weight=1.0)),
train_cfg=dict(isr=dict(k=2., bias=0.), carl=dict(k=1., bias=0.2)))
| 272 | 33.125 | 73 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/pisa/pisa_mask_rcnn_x101_32x4d_fpn_1x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_x101_32x4d_fpn_1x_coco.py'
model = dict(
roi_head=dict(
type='PISARoIHead',
bbox_head=dict(
loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=1.0))),
train_cfg=dict(
rpn_proposal=dict(
nms_pre=2000,
max_per_img... | 929 | 29 | 77 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/pisa/pisa_retinanet_r50_fpn_1x_coco.py | _base_ = '../retinanet/retinanet_r50_fpn_1x_coco.py'
model = dict(
bbox_head=dict(
type='PISARetinaHead',
loss_bbox=dict(type='SmoothL1Loss', beta=0.11, loss_weight=1.0)),
train_cfg=dict(isr=dict(k=2., bias=0.), carl=dict(k=1., bias=0.2)))
| 265 | 32.25 | 73 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/pisa/pisa_faster_rcnn_r50_fpn_1x_coco.py | _base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'
model = dict(
roi_head=dict(
type='PISARoIHead',
bbox_head=dict(
loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=1.0))),
train_cfg=dict(
rpn_proposal=dict(
nms_pre=2000,
max_per_img=20... | 926 | 28.903226 | 77 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/pisa/pisa_ssd512_coco.py | _base_ = '../ssd/ssd512_coco.py'
model = dict(
bbox_head=dict(type='PISASSDHead'),
train_cfg=dict(isr=dict(k=2., bias=0.), carl=dict(k=1., bias=0.2)))
optimizer_config = dict(
_delete_=True, grad_clip=dict(max_norm=35, norm_type=2))
| 247 | 26.555556 | 71 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/pisa/pisa_ssd300_coco.py | _base_ = '../ssd/ssd300_coco.py'
model = dict(
bbox_head=dict(type='PISASSDHead'),
train_cfg=dict(isr=dict(k=2., bias=0.), carl=dict(k=1., bias=0.2)))
optimizer_config = dict(
_delete_=True, grad_clip=dict(max_norm=35, norm_type=2))
| 247 | 26.555556 | 71 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/pisa/pisa_faster_rcnn_x101_32x4d_fpn_1x_coco.py | _base_ = '../faster_rcnn/faster_rcnn_x101_32x4d_fpn_1x_coco.py'
model = dict(
roi_head=dict(
type='PISARoIHead',
bbox_head=dict(
loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=1.0))),
train_cfg=dict(
rpn_proposal=dict(
nms_pre=2000,
max_per... | 933 | 29.129032 | 77 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/pisa/pisa_mask_rcnn_r50_fpn_1x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'
model = dict(
roi_head=dict(
type='PISARoIHead',
bbox_head=dict(
loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=1.0))),
train_cfg=dict(
rpn_proposal=dict(
nms_pre=2000,
max_per_img=2000,
... | 922 | 28.774194 | 77 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_x101_32x4d_fpn_20e_coco.py | _base_ = './cascade_mask_rcnn_r50_fpn_20e_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='py... | 428 | 27.6 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_x101_32x4d_fpn_mstrain_3x_coco.py | _base_ = './cascade_mask_rcnn_r50_fpn_mstrain_3x_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),
st... | 435 | 28.066667 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_20e_coco.py | _base_ = [
'../_base_/models/cascade_mask_rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_20e.py', '../_base_/default_runtime.py'
]
| 183 | 29.666667 | 73 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_rcnn_r50_caffe_fpn_1x_coco.py | _base_ = './cascade_rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(requires_grad=False),
style='caffe',
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://detectron2/resnet50_caffe')))
# use caffe img_norm
img_norm_cfg = dict(
mean=[... | 1,389 | 31.325581 | 72 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_r50_caffe_fpn_1x_coco.py | _base_ = ['./cascade_mask_rcnn_r50_fpn_1x_coco.py']
model = dict(
backbone=dict(
norm_cfg=dict(requires_grad=False),
norm_eval=True,
style='caffe',
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://detectron2/resnet50_caffe')))
img_norm_cfg = dict(
... | 1,426 | 32.97619 | 77 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_x101_64x4d_fpn_mstrain_3x_coco.py | _base_ = './cascade_mask_rcnn_r50_fpn_mstrain_3x_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),
st... | 435 | 28.066667 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_rcnn_x101_32x4d_fpn_20e_coco.py | _base_ = './cascade_rcnn_r50_fpn_20e_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... | 423 | 27.266667 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_rcnn_r101_fpn_1x_coco.py | _base_ = './cascade_rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 200 | 27.714286 | 61 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_x101_32x8d_fpn_mstrain_3x_coco.py | _base_ = './cascade_mask_rcnn_r50_fpn_mstrain_3x_coco.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
base_width=8,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=False),
... | 1,878 | 29.803279 | 77 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_r101_fpn_mstrain_3x_coco.py | _base_ = './cascade_mask_rcnn_r50_fpn_mstrain_3x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 213 | 29.571429 | 61 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_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'
]
| 182 | 29.5 | 72 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_r101_fpn_20e_coco.py | _base_ = './cascade_mask_rcnn_r50_fpn_20e_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 206 | 28.571429 | 61 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_r101_caffe_fpn_1x_coco.py | _base_ = './cascade_mask_rcnn_r50_caffe_fpn_1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://detectron2/resnet101_caffe')))
| 230 | 27.875 | 67 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_rcnn_x101_64x4d_fpn_1x_coco.py | _base_ = './cascade_rcnn_r50_fpn_1x_coco.py'
model = dict(
type='CascadeRCNN',
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),... | 446 | 26.9375 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_x101_64x4d_fpn_1x_coco.py | _base_ = './cascade_mask_rcnn_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='pyt... | 427 | 27.533333 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_rcnn_x101_64x4d_fpn_20e_coco.py | _base_ = './cascade_rcnn_r50_fpn_20e_coco.py'
model = dict(
type='CascadeRCNN',
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)... | 447 | 27 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_rcnn_r50_fpn_20e_coco.py | _base_ = './cascade_rcnn_r50_fpn_1x_coco.py'
# learning policy
lr_config = dict(step=[16, 19])
runner = dict(type='EpochBasedRunner', max_epochs=20)
| 149 | 29 | 53 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_rcnn_x101_32x4d_fpn_1x_coco.py | _base_ = './cascade_rcnn_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 |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_mstrain_3x_coco.py | _base_ = [
'../common/mstrain_3x_coco_instance.py',
'../_base_/models/cascade_mask_rcnn_r50_fpn.py'
]
| 110 | 21.2 | 51 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_r101_caffe_fpn_mstrain_3x_coco.py | _base_ = './cascade_mask_rcnn_r50_caffe_fpn_mstrain_3x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://detectron2/resnet101_caffe')))
| 238 | 28.875 | 67 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.py | _base_ = [
'../_base_/models/cascade_rcnn_r50_fpn.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
| 178 | 28.833333 | 72 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_rcnn_r101_caffe_fpn_1x_coco.py | _base_ = './cascade_rcnn_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 |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_x101_64x4d_fpn_20e_coco.py | _base_ = './cascade_mask_rcnn_r50_fpn_20e_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='py... | 428 | 27.6 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_x101_32x4d_fpn_1x_coco.py | _base_ = './cascade_mask_rcnn_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='pyt... | 427 | 27.533333 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_rcnn_r101_fpn_20e_coco.py | _base_ = './cascade_rcnn_r50_fpn_20e_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 201 | 27.857143 | 61 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_r101_fpn_1x_coco.py | _base_ = './cascade_mask_rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 205 | 28.428571 | 61 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/cascade_rcnn/cascade_mask_rcnn_r50_caffe_fpn_mstrain_3x_coco.py | _base_ = ['./cascade_mask_rcnn_r50_fpn_mstrain_3x_coco.py']
model = dict(
backbone=dict(
norm_cfg=dict(requires_grad=False),
norm_eval=True,
style='caffe',
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://detectron2/resnet50_caffe')))
# use caffe im... | 1,631 | 31.64 | 77 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/nas_fcos/nas_fcos_nashead_r50_caffe_fpn_gn-head_4x4_1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
type='NASFCOS',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_c... | 2,990 | 28.91 | 73 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/nas_fcos/nas_fcos_fcoshead_r50_caffe_fpn_gn-head_4x4_1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
type='NASFCOS',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_c... | 3,012 | 28.831683 | 73 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/rpn/rpn_x101_64x4d_fpn_2x_coco.py | _base_ = './rpn_r50_fpn_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),
style='pytorch',
... | 413 | 26.6 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/rpn/rpn_x101_32x4d_fpn_2x_coco.py | _base_ = './rpn_r50_fpn_2x_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',
... | 413 | 26.6 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/rpn/rpn_x101_64x4d_fpn_1x_coco.py | _base_ = './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',
... | 413 | 26.6 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/rpn/rpn_r50_fpn_1x_coco.py | _base_ = [
'../_base_/models/rpn_r50_fpn.py', '../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile'),
... | 776 | 39.894737 | 78 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/rpn/rpn_r50_caffe_c4_1x_coco.py | _base_ = [
'../_base_/models/rpn_r50_caffe_c4.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# dataset settings
img_norm_cfg = dict(
mean=[103.530, 116.280, 123.675], std=[1.0, 1.0, 1.0], to_rgb=False)
train_pipeline = [
dict(type=... | 1,352 | 33.692308 | 72 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/rpn/rpn_r50_caffe_fpn_1x_coco.py | _base_ = './rpn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(requires_grad=False),
norm_eval=True,
style='caffe',
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://detectron2/resnet50_caffe')))
# use caffe img_norm
img_norm_cfg = dic... | 1,407 | 32.52381 | 72 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/rpn/rpn_r101_fpn_1x_coco.py | _base_ = './rpn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 191 | 26.428571 | 61 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/rpn/rpn_r50_fpn_2x_coco.py | _base_ = './rpn_r50_fpn_1x_coco.py'
# learning policy
lr_config = dict(step=[16, 22])
runner = dict(type='EpochBasedRunner', max_epochs=24)
| 141 | 22.666667 | 53 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/rpn/rpn_x101_32x4d_fpn_1x_coco.py | _base_ = './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',
... | 413 | 26.6 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/rpn/rpn_r101_caffe_fpn_1x_coco.py | _base_ = './rpn_r50_caffe_fpn_1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://detectron2/resnet101_caffe')))
| 216 | 26.125 | 67 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/rpn/rpn_r101_fpn_2x_coco.py | _base_ = './rpn_r50_fpn_2x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 191 | 26.428571 | 61 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/deformable_detr/deformable_detr_r50_16x2_50e_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py', '../_base_/default_runtime.py'
]
model = dict(
type='DeformableDETR',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=False)... | 6,478 | 36.450867 | 79 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/deformable_detr/deformable_detr_refine_r50_16x2_50e_coco.py | _base_ = 'deformable_detr_r50_16x2_50e_coco.py'
model = dict(bbox_head=dict(with_box_refine=True))
| 99 | 32.333333 | 50 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/deformable_detr/deformable_detr_twostage_refine_r50_16x2_50e_coco.py | _base_ = 'deformable_detr_refine_r50_16x2_50e_coco.py'
model = dict(bbox_head=dict(as_two_stage=True))
| 103 | 33.666667 | 54 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/res2net/htc_r2_101_fpn_20e_coco.py | _base_ = '../htc/htc_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='Res2Net',
depth=101,
scales=4,
base_width=26,
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://res2net101_v1d_26w_4s')))
# learning policy
lr_config = dict(step=[16, ... | 379 | 26.142857 | 62 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/res2net/cascade_rcnn_r2_101_fpn_20e_coco.py | _base_ = '../cascade_rcnn/cascade_rcnn_r50_fpn_20e_coco.py'
model = dict(
backbone=dict(
type='Res2Net',
depth=101,
scales=4,
base_width=26,
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://res2net101_v1d_26w_4s')))
| 294 | 25.818182 | 62 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/res2net/mask_rcnn_r2_101_fpn_2x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_2x_coco.py'
model = dict(
backbone=dict(
type='Res2Net',
depth=101,
scales=4,
base_width=26,
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://res2net101_v1d_26w_4s')))
| 287 | 25.181818 | 62 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/res2net/faster_rcnn_r2_101_fpn_2x_coco.py | _base_ = '../faster_rcnn/faster_rcnn_r50_fpn_2x_coco.py'
model = dict(
backbone=dict(
type='Res2Net',
depth=101,
scales=4,
base_width=26,
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://res2net101_v1d_26w_4s')))
| 291 | 25.545455 | 62 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/res2net/cascade_mask_rcnn_r2_101_fpn_20e_coco.py | _base_ = '../cascade_rcnn/cascade_mask_rcnn_r50_fpn_20e_coco.py'
model = dict(
backbone=dict(
type='Res2Net',
depth=101,
scales=4,
base_width=26,
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://res2net101_v1d_26w_4s')))
| 299 | 26.272727 | 64 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/lvis/mask_rcnn_x101_64x4d_fpn_sample1e-3_mstrain_1x_lvis_v1.py | _base_ = './mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.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),
... | 441 | 28.466667 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/lvis/mask_rcnn_r101_fpn_sample1e-3_mstrain_2x_lvis_v0.5.py | _base_ = './mask_rcnn_r50_fpn_sample1e-3_mstrain_2x_lvis_v0.5.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 221 | 30.714286 | 65 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/lvis/mask_rcnn_x101_64x4d_fpn_sample1e-3_mstrain_2x_lvis_v0.5.py | _base_ = './mask_rcnn_r50_fpn_sample1e-3_mstrain_2x_lvis_v0.5.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),
... | 443 | 28.6 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/lvis/mask_rcnn_r50_fpn_sample1e-3_mstrain_2x_lvis_v0.5.py | _base_ = [
'../_base_/models/mask_rcnn_r50_fpn.py',
'../_base_/datasets/lvis_v0.5_instance.py',
'../_base_/schedules/schedule_2x.py', '../_base_/default_runtime.py'
]
model = dict(
roi_head=dict(
bbox_head=dict(num_classes=1230), mask_head=dict(num_classes=1230)),
test_cfg=dict(
rcnn... | 1,162 | 35.34375 | 77 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/lvis/mask_rcnn_x101_32x4d_fpn_sample1e-3_mstrain_2x_lvis_v0.5.py | _base_ = './mask_rcnn_r50_fpn_sample1e-3_mstrain_2x_lvis_v0.5.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),
... | 443 | 28.6 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/lvis/mask_rcnn_x101_32x4d_fpn_sample1e-3_mstrain_1x_lvis_v1.py | _base_ = './mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.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),
... | 441 | 28.466667 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/lvis/mask_rcnn_r101_fpn_sample1e-3_mstrain_1x_lvis_v1.py | _base_ = './mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 219 | 30.428571 | 63 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/lvis/mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py | _base_ = [
'../_base_/models/mask_rcnn_r50_fpn.py',
'../_base_/datasets/lvis_v1_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
roi_head=dict(
bbox_head=dict(num_classes=1203), mask_head=dict(num_classes=1203)),
test_cfg=dict(
rcnn=d... | 1,160 | 35.28125 | 77 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/yolof/yolof_r50_c5_8x8_iter-1x_coco.py | _base_ = './yolof_r50_c5_8x8_1x_coco.py'
# We implemented the iter-based config according to the source code.
# COCO dataset has 117266 images after filtering. We use 8 gpu and
# 8 batch size training, so 22500 is equivalent to
# 22500/(117266/(8x8))=12.3 epoch, 15000 is equivalent to 8.2 epoch,
# 20000 is equivalent ... | 671 | 43.8 | 69 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/yolof/yolof_r50_c5_8x8_1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
type='YOLOF',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(3, ),
frozen_stages=1,
norm_cfg=dict(ty... | 3,279 | 29.943396 | 77 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_dconv_c3-c5_r16_gcb_c3-c5_1x_coco.py | _base_ = '../dcn/cascade_mask_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 16),
stages=(False, T... | 390 | 31.583333 | 73 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/mask_rcnn_r50_fpn_r4_gcb_c3-c5_1x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 4),
stages=(False, True, True, True),
position='after_conv3')
]))
| 256 | 27.555556 | 56 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/mask_rcnn_r50_fpn_syncbn-backbone_r16_gcb_c3-c5_1x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 16),
stages=(False, True, True, True),
... | 369 | 29.833333 | 61 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/mask_rcnn_r50_fpn_syncbn-backbone_1x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=False))
| 162 | 31.6 | 75 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/mask_rcnn_x101_32x4d_fpn_syncbn-backbone_1x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_x101_32x4d_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=False))
| 169 | 33 | 75 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/mask_rcnn_x101_32x4d_fpn_syncbn-backbone_r4_gcb_c3-c5_1x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_x101_32x4d_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 4),
stages=(False, True, True, True... | 375 | 30.333333 | 60 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_1x_coco.py | _base_ = '../cascade_rcnn/cascade_mask_rcnn_x101_32x4d_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=False))
| 180 | 35.2 | 75 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_r16_gcb_c3-c5_1x_coco.py | _base_ = '../cascade_rcnn/cascade_mask_rcnn_x101_32x4d_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 16),
stages=(False, True... | 387 | 31.333333 | 70 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/mask_rcnn_r101_fpn_syncbn-backbone_r16_gcb_c3-c5_1x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_r101_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 16),
stages=(False, True, True, True),
... | 370 | 29.916667 | 61 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/mask_rcnn_r50_fpn_r16_gcb_c3-c5_1x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 16),
stages=(False, True, True, True),
position='after_conv3')
]))
| 257 | 27.666667 | 57 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/mask_rcnn_r101_fpn_syncbn-backbone_r4_gcb_c3-c5_1x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_r101_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 4),
stages=(False, True, True, True),
... | 369 | 29.833333 | 60 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/mask_rcnn_r101_fpn_syncbn-backbone_1x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_r101_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=False))
| 163 | 31.8 | 75 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/mask_rcnn_r101_fpn_r16_gcb_c3-c5_1x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_r101_fpn_1x_coco.py'
model = dict(
backbone=dict(plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 16),
stages=(False, True, True, True),
position='after_conv3')
]))
| 258 | 27.777778 | 57 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_dconv_c3-c5_r4_gcb_c3-c5_1x_coco.py | _base_ = '../dcn/cascade_mask_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 4),
stages=(False, Tr... | 389 | 31.5 | 73 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_dconv_c3-c5_1x_coco.py | _base_ = '../dcn/cascade_mask_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=False))
| 183 | 35.8 | 75 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/mask_rcnn_x101_32x4d_fpn_syncbn-backbone_r16_gcb_c3-c5_1x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_x101_32x4d_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 16),
stages=(False, True, True, Tru... | 376 | 30.416667 | 61 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/mask_rcnn_r50_fpn_syncbn-backbone_r4_gcb_c3-c5_1x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 4),
stages=(False, True, True, True),
... | 368 | 29.75 | 60 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_r4_gcb_c3-c5_1x_coco.py | _base_ = '../cascade_rcnn/cascade_mask_rcnn_x101_32x4d_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 4),
stages=(False, True,... | 386 | 31.25 | 70 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/gcnet/mask_rcnn_r101_fpn_r4_gcb_c3-c5_1x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_r101_fpn_1x_coco.py'
model = dict(
backbone=dict(plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 4),
stages=(False, True, True, True),
position='after_conv3')
]))
| 257 | 27.666667 | 56 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/instaboost/mask_rcnn_x101_64x4d_fpn_instaboost_4x_coco.py | _base_ = './mask_rcnn_r50_fpn_instaboost_4x_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='... | 430 | 27.733333 | 76 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/instaboost/mask_rcnn_r101_fpn_instaboost_4x_coco.py | _base_ = './mask_rcnn_r50_fpn_instaboost_4x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 208 | 28.857143 | 61 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/instaboost/cascade_mask_rcnn_r101_fpn_instaboost_4x_coco.py | _base_ = './cascade_mask_rcnn_r50_fpn_instaboost_4x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| 217 | 26.25 | 61 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/instaboost/cascade_mask_rcnn_r50_fpn_instaboost_4x_coco.py | _base_ = '../cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.py'
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='InstaBoost',
action_candidate=('normal', 'horizontal', 'skip'),
... | 1,023 | 34.310345 | 77 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/instaboost/mask_rcnn_r50_fpn_instaboost_4x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='InstaBoost',
action_candidate=('normal', 'horizontal', 'skip'),
action_pr... | 1,012 | 33.931034 | 77 | py |
PseCo | PseCo-master/thirdparty/mmdetection/configs/instaboost/cascade_mask_rcnn_x101_64x4d_fpn_instaboost_4x_coco.py | _base_ = './cascade_mask_rcnn_r50_fpn_instaboost_4x_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),
... | 438 | 28.266667 | 76 | py |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.