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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RSP | RSP-main/Object Detection/configs/fcos/fcos_r101_caffe_fpn_gn-head_4x4_1x_coco.py | _base_ = './fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron/resnet101_caffe',
backbone=dict(depth=101))
| 156 | 30.4 | 56 | py |
RSP | RSP-main/Object Detection/configs/fcos/fcos_r101_caffe_fpn_gn-head_mstrain_640-800_4x4_2x_coco.py | _base_ = './fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron/resnet101_caffe',
backbone=dict(depth=101))
img_norm_cfg = dict(
mean=[102.9801, 115.9465, 122.7717], std=[1.0, 1.0, 1.0], to_rgb=False)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(typ... | 1,446 | 31.155556 | 75 | py |
RSP | RSP-main/Object Detection/configs/fcos/fcos_x101_64x4d_fpn_gn-head_mstrain_640-800_4x2_2x_coco.py | _base_ = './fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py'
model = dict(
pretrained='open-mmlab://resnext101_64x4d',
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=di... | 1,883 | 30.4 | 77 | py |
RSP | RSP-main/Object Detection/configs/fcos/fcos_center_r50_caffe_fpn_gn-head_4x4_1x_coco.py | _base_ = './fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py'
model = dict(bbox_head=dict(center_sampling=True, center_sample_radius=1.5))
| 132 | 43.333333 | 76 | py |
RSP | RSP-main/Object Detection/configs/fcos/fcos_r101_caffe_fpn_gn-head_4x4_2x_coco.py | _base_ = ['./fcos_r50_caffe_fpn_gn-head_4x4_2x_coco.py']
model = dict(
pretrained='open-mmlab://detectron/resnet101_caffe',
backbone=dict(depth=101))
| 158 | 30.8 | 56 | py |
RSP | RSP-main/Object Detection/configs/fcos/fcos_r50_caffe_fpn_gn-head_mstrain_640-800_4x4_2x_coco.py | _base_ = './fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py'
img_norm_cfg = dict(
mean=[102.9801, 115.9465, 122.7717], std=[1.0, 1.0, 1.0], to_rgb=False)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='Resize',
img_scale=[(1333, 640)... | 1,299 | 31.5 | 75 | py |
RSP | RSP-main/Object Detection/configs/fcos/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_4x4_1x_coco.py | _base_ = 'fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(
dcn=dict(type='DCNv2', deformable_groups=1, fallback_on_stride=False),
stage_with_dcn=(False, True, True, True)),
bbox_head=dict(
norm_on_bbox=True,... | 1,836 | 32.4 | 78 | py |
RSP | RSP-main/Object Detection/configs/fcos/fcos_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 settings
model = dict(
type='FCOS',
pretrained='open-mmlab://detectron/resnet50_caffe',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
... | 3,140 | 28.632075 | 75 | py |
RSP | RSP-main/Object Detection/configs/fcos/fcos_r50_caffe_fpn_gn-head_4x4_2x_coco.py | _base_ = './fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py'
# learning policy
lr_config = dict(step=[16, 22])
total_epochs = 24
| 124 | 19.833333 | 54 | py |
RSP | RSP-main/Object Detection/configs/fcos/fcos_r50_caffe_fpn_4x4_1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# model settings
model = dict(
type='FCOS',
pretrained='open-mmlab://detectron/resnet50_caffe',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
... | 3,163 | 28.570093 | 75 | py |
RSP | RSP-main/Object Detection/configs/legacy_1.x/faster_rcnn_r50_fpn_1x_coco_v1.py | _base_ = [
'../_base_/models/faster_rcnn_r50_fpn.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
type='FasterRCNN',
pretrained='torchvision://resnet50',
rpn_head=dict(
type='RPNHead',
anchor_genera... | 1,268 | 35.257143 | 78 | py |
RSP | RSP-main/Object Detection/configs/legacy_1.x/cascade_mask_rcnn_r50_fpn_1x_coco_v1.py | _base_ = [
'../_base_/models/cascade_mask_rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
type='CascadeRCNN',
pretrained='torchvision://resnet50',
backbone=dict(
type='ResNet',
depth=50,... | 2,643 | 34.72973 | 79 | py |
RSP | RSP-main/Object Detection/configs/legacy_1.x/retinanet_r50_caffe_fpn_1x_coco_v1.py | _base_ = './retinanet_r50_fpn_1x_coco_v1.py'
model = dict(
pretrained='open-mmlab://detectron/resnet50_caffe',
backbone=dict(
norm_cfg=dict(requires_grad=False), norm_eval=True, style='caffe'))
# use caffe img_norm
img_norm_cfg = dict(
mean=[102.9801, 115.9465, 122.7717], std=[1.0, 1.0, 1.0], to_rgb... | 1,334 | 34.131579 | 75 | py |
RSP | RSP-main/Object Detection/configs/ms_rcnn/ms_rcnn_r50_caffe_fpn_1x_coco.py | _base_ = '../mask_rcnn/mask_rcnn_r50_caffe_fpn_1x_coco.py'
model = dict(
type='MaskScoringRCNN',
roi_head=dict(
type='MaskScoringRoIHead',
mask_iou_head=dict(
type='MaskIoUHead',
num_convs=4,
num_fcs=2,
roi_feat_size=14,
in_channels=256... | 508 | 28.941176 | 58 | py |
RSP | RSP-main/Object Detection/configs/ms_rcnn/ms_rcnn_x101_64x4d_fpn_1x_coco.py | _base_ = './ms_rcnn_r50_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://resnext101_64x4d',
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', r... | 366 | 25.214286 | 53 | py |
RSP | RSP-main/Object Detection/configs/ms_rcnn/ms_rcnn_r50_caffe_fpn_2x_coco.py | _base_ = './ms_rcnn_r50_caffe_fpn_1x_coco.py'
# learning policy
lr_config = dict(step=[16, 22])
total_epochs = 24
| 114 | 22 | 45 | py |
RSP | RSP-main/Object Detection/configs/ms_rcnn/ms_rcnn_x101_32x4d_fpn_1x_coco.py | _base_ = './ms_rcnn_r50_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://resnext101_32x4d',
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', r... | 366 | 25.214286 | 53 | py |
RSP | RSP-main/Object Detection/configs/ms_rcnn/ms_rcnn_r101_caffe_fpn_2x_coco.py | _base_ = './ms_rcnn_r101_caffe_fpn_1x_coco.py'
# learning policy
lr_config = dict(step=[16, 22])
total_epochs = 24
| 115 | 22.2 | 46 | py |
RSP | RSP-main/Object Detection/configs/ms_rcnn/ms_rcnn_r101_caffe_fpn_1x_coco.py | _base_ = './ms_rcnn_r50_caffe_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnet101_caffe',
backbone=dict(depth=101))
| 148 | 28.8 | 57 | py |
RSP | RSP-main/Object Detection/configs/fast_rcnn/fast_rcnn_r101_fpn_2x_coco.py | _base_ = './fast_rcnn_r50_fpn_2x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 119 | 39 | 76 | py |
RSP | RSP-main/Object Detection/configs/fast_rcnn/fast_rcnn_r101_fpn_1x_coco.py | _base_ = './fast_rcnn_r50_fpn_1x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 119 | 39 | 76 | py |
RSP | RSP-main/Object Detection/configs/fast_rcnn/fast_rcnn_r101_caffe_fpn_1x_coco.py | _base_ = './fast_rcnn_r50_caffe_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnet101_caffe',
backbone=dict(depth=101))
| 150 | 29.2 | 57 | py |
RSP | RSP-main/Object Detection/configs/fast_rcnn/fast_rcnn_r50_caffe_fpn_1x_coco.py | _base_ = './fast_rcnn_r50_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(
norm_cfg=dict(type='BN', requires_grad=False), style='caffe'))
# use caffe img_norm
img_norm_cfg = dict(
mean=[103.530, 116.280, 123.675], std=[1.0, 1.0, 1.0], to_rgb=False)
... | 1,639 | 34.652174 | 78 | py |
RSP | RSP-main/Object Detection/configs/hrnet/fcos_hrnetv2p_w32_gn-head_4x4_1x_coco.py | _base_ = '../fcos/fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py'
model = dict(
pretrained='open-mmlab://msra/hrnetv2_w32',
backbone=dict(
_delete_=True,
type='HRNet',
extra=dict(
stage1=dict(
num_modules=1,
num_branches=1,
block='BO... | 1,176 | 29.179487 | 60 | py |
RSP | RSP-main/Object Detection/configs/foveabox/fovea_r50_fpn_4x4_1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# model settings
model = dict(
type='FOVEA',
pretrained='torchvision://resnet50',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indice... | 1,542 | 28.113208 | 78 | py |
RSP | RSP-main/Object Detection/configs/foveabox/fovea_r101_fpn_4x4_2x_coco.py | _base_ = './fovea_r50_fpn_4x4_2x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 119 | 39 | 76 | py |
RSP | RSP-main/Object Detection/configs/foveabox/fovea_align_r101_fpn_gn-head_mstrain_640-800_4x4_2x_coco.py | _base_ = './fovea_r50_fpn_4x4_1x_coco.py'
model = dict(
pretrained='torchvision://resnet101',
backbone=dict(depth=101),
bbox_head=dict(
with_deform=True,
norm_cfg=dict(type='GN', num_groups=32, requires_grad=True)))
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12,... | 937 | 32.5 | 77 | py |
RSP | RSP-main/Object Detection/configs/foveabox/fovea_r101_fpn_4x4_1x_coco.py | _base_ = './fovea_r50_fpn_4x4_1x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 119 | 39 | 76 | py |
RSP | RSP-main/Object Detection/configs/foveabox/fovea_align_r101_fpn_gn-head_4x4_2x_coco.py | _base_ = './fovea_r50_fpn_4x4_1x_coco.py'
model = dict(
pretrained='torchvision://resnet101',
backbone=dict(depth=101),
bbox_head=dict(
with_deform=True,
norm_cfg=dict(type='GN', num_groups=32, requires_grad=True)))
# learning policy
lr_config = dict(step=[16, 22])
total_epochs = 24
| 312 | 27.454545 | 69 | py |
RSP | RSP-main/Object Detection/configs/regnet/mask_rcnn_regnetx-8GF_fpn_1x_coco.py | _base_ = './mask_rcnn_regnetx-3.2GF_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://regnetx_8.0gf',
backbone=dict(
type='RegNet',
arch='regnetx_8.0gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
... | 470 | 26.705882 | 53 | py |
RSP | RSP-main/Object Detection/configs/regnet/retinanet_regnetx-1.6GF_fpn_1x_coco.py | _base_ = './retinanet_regnetx-3.2GF_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://regnetx_1.6gf',
backbone=dict(
type='RegNet',
arch='regnetx_1.6gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
... | 469 | 26.647059 | 53 | py |
RSP | RSP-main/Object Detection/configs/regnet/mask_rcnn_regnetx-12GF_fpn_1x_coco.py | _base_ = './mask_rcnn_regnetx-3.2GF_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://regnetx_12gf',
backbone=dict(
type='RegNet',
arch='regnetx_12gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
... | 469 | 26.647059 | 53 | py |
RSP | RSP-main/Object Detection/configs/regnet/faster_rcnn_regnetx-3.2GF_fpn_2x_coco.py | _base_ = [
'../_base_/models/faster_rcnn_r50_fpn.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_2x.py', '../_base_/default_runtime.py'
]
model = dict(
pretrained='open-mmlab://regnetx_3.2gf',
backbone=dict(
_delete_=True,
type='RegNet',
arch='regne... | 1,886 | 32.105263 | 73 | py |
RSP | RSP-main/Object Detection/configs/regnet/retinanet_regnetx-800MF_fpn_1x_coco.py | _base_ = './retinanet_regnetx-3.2GF_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://regnetx_800mf',
backbone=dict(
type='RegNet',
arch='regnetx_800mf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
... | 469 | 26.647059 | 53 | py |
RSP | RSP-main/Object Detection/configs/regnet/mask_rcnn_regnetx-4GF_fpn_1x_coco.py | _base_ = './mask_rcnn_regnetx-3.2GF_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://regnetx_4.0gf',
backbone=dict(
type='RegNet',
arch='regnetx_4.0gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
... | 470 | 26.705882 | 53 | py |
RSP | RSP-main/Object Detection/configs/regnet/faster_rcnn_regnetx-3.2GF_fpn_mstrain_3x_coco.py | _base_ = [
'../_base_/models/faster_rcnn_r50_fpn.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
pretrained='open-mmlab://regnetx_3.2gf',
backbone=dict(
_delete_=True,
type='RegNet',
arch='regne... | 2,081 | 31.53125 | 73 | py |
RSP | RSP-main/Object Detection/configs/regnet/mask_rcnn_regnetx-3.2GF_fpn_mdconv_c3-c5_1x_coco.py | _base_ = [
'../_base_/models/mask_rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
pretrained='open-mmlab://regnetx_3.2gf',
backbone=dict(
_delete_=True,
type='RegNet',
arch='regnetx_... | 2,110 | 34.183333 | 78 | py |
RSP | RSP-main/Object Detection/configs/regnet/retinanet_regnetx-3.2GF_fpn_1x_coco.py | _base_ = [
'../_base_/models/retinanet_r50_fpn.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
pretrained='open-mmlab://regnetx_3.2gf',
backbone=dict(
_delete_=True,
type='RegNet',
arch='regnetx... | 1,970 | 32.40678 | 73 | py |
RSP | RSP-main/Object Detection/configs/regnet/faster_rcnn_regnetx-3GF_fpn_mstrain_3x_coco.py | _base_ = [
'../_base_/models/faster_rcnn_r50_fpn.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
pretrained='open-mmlab://regnetx_3.2gf',
backbone=dict(
_delete_=True,
type='RegNet',
arch='regne... | 2,079 | 31.5 | 73 | py |
RSP | RSP-main/Object Detection/configs/regnet/faster_rcnn_regnetx-3.2GF_fpn_1x_coco.py | _base_ = [
'../_base_/models/faster_rcnn_r50_fpn.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
pretrained='open-mmlab://regnetx_3.2gf',
backbone=dict(
_delete_=True,
type='RegNet',
arch='regne... | 1,887 | 32.122807 | 73 | py |
RSP | RSP-main/Object Detection/configs/regnet/mask_rcnn_regnetx-3.2GF_fpn_1x_coco.py | _base_ = [
'../_base_/models/mask_rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
pretrained='open-mmlab://regnetx_3.2gf',
backbone=dict(
_delete_=True,
type='RegNet',
arch='regnetx_... | 1,981 | 33.172414 | 77 | py |
RSP | RSP-main/Object Detection/configs/regnet/mask_rcnn_regnetx-3.2GF_fpn_mstrain_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'
]
model = dict(
pretrained='open-mmlab://regnetx_3.2gf',
backbone=dict(
_delete_=True,
type='RegNet',
arch='regnetx_... | 2,261 | 32.761194 | 77 | py |
RSP | RSP-main/Object Detection/configs/regnet/mask_rcnn_regnetx-6.4GF_fpn_1x_coco.py | _base_ = './mask_rcnn_regnetx-3.2GF_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://regnetx_6.4gf',
backbone=dict(
type='RegNet',
arch='regnetx_6.4gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
... | 471 | 26.764706 | 53 | py |
RSP | RSP-main/Object Detection/configs/fsaf/fsaf_x101_64x4d_fpn_1x_coco.py | _base_ = './fsaf_r50_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://resnext101_64x4d',
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', requ... | 363 | 25 | 53 | py |
RSP | RSP-main/Object Detection/configs/fsaf/fsaf_r101_fpn_1x_coco.py | _base_ = './fsaf_r50_fpn_1x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 114 | 37.333333 | 76 | py |
RSP | RSP-main/Object Detection/configs/grid_rcnn/grid_rcnn_r101_fpn_gn-head_2x_coco.py | _base_ = './grid_rcnn_r50_fpn_gn-head_2x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 128 | 31.25 | 76 | py |
RSP | RSP-main/Object Detection/configs/grid_rcnn/grid_rcnn_x101_64x4d_fpn_gn-head_2x_coco.py | _base_ = './grid_rcnn_x101_32x4d_fpn_gn-head_2x_coco.py'
model = dict(
pretrained='open-mmlab://resnext101_64x4d',
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
style='py... | 329 | 24.384615 | 56 | py |
RSP | RSP-main/Object Detection/configs/grid_rcnn/grid_rcnn_x101_32x4d_fpn_gn-head_2x_coco.py | _base_ = './grid_rcnn_r50_fpn_gn-head_2x_coco.py'
model = dict(
pretrained='open-mmlab://resnext101_32x4d',
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
style='pytorch')... | 610 | 24.458333 | 72 | py |
RSP | RSP-main/Object Detection/configs/grid_rcnn/grid_rcnn_r50_fpn_gn-head_2x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py', '../_base_/default_runtime.py'
]
# model settings
model = dict(
type='GridRCNN',
pretrained='torchvision://resnet50',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1... | 4,055 | 29.268657 | 78 | py |
RSP | RSP-main/Object Detection/configs/_base_/models/retinanet_r50_fpn.py | # model settings
model = dict(
type='RetinaNet',
pretrained='torchvision://resnet50',
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,
... | 1,651 | 26.081967 | 56 | py |
RSP | RSP-main/Object Detection/configs/_base_/models/faster_rcnn_r50_fpn.py | model = dict(
type='FasterRCNN',
pretrained='torchvision://resnet50',
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'... | 3,380 | 29.736364 | 77 | py |
RSP | RSP-main/Object Detection/configs/_base_/models/cascade_rcnn_r50_fpn.py | # model settings
model = dict(
type='CascadeRCNN',
pretrained='torchvision://resnet50',
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,
... | 5,972 | 31.818681 | 79 | py |
RSP | RSP-main/Object Detection/configs/_base_/models/rpn_r50_caffe_c4.py | # model settings
model = dict(
type='RPN',
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(
type='ResNet',
depth=50,
num_stages=3,
strides=(1, 2, 2),
dilations=(1, 1, 1),
out_indices=(2, ),
frozen_stages=1,
norm_cfg=dict(type... | 1,655 | 27.067797 | 72 | py |
RSP | RSP-main/Object Detection/configs/_base_/models/cascade_mask_rcnn_r50_fpn.py | # model settings
model = dict(
type='CascadeRCNN',
pretrained='torchvision://resnet50',
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,
... | 6,590 | 31.791045 | 79 | py |
RSP | RSP-main/Object Detection/configs/_base_/models/fast_rcnn_r50_fpn.py | # model settings
model = dict(
type='FastRCNN',
pretrained='torchvision://resnet50',
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,
... | 1,903 | 30.213115 | 77 | py |
RSP | RSP-main/Object Detection/configs/_base_/models/mask_rcnn_r50_fpn.py | # model settings
model = dict(
type='MaskRCNN',
pretrained='torchvision://resnet50',
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,
... | 3,838 | 29.712 | 77 | py |
RSP | RSP-main/Object Detection/configs/_base_/models/rpn_r50_fpn.py | # model settings
model = dict(
type='RPN',
pretrained='torchvision://resnet50',
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... | 1,699 | 26.868852 | 72 | py |
RSP | RSP-main/Object Detection/configs/_base_/models/ssd300.py | # model settings
input_size = 300
model = dict(
type='SingleStageDetector',
pretrained='open-mmlab://vgg16_caffe',
backbone=dict(
type='SSDVGG',
input_size=input_size,
depth=16,
with_last_pool=False,
ceil_mode=True,
out_indices=(3, 4),
out_feature_indi... | 1,389 | 26.8 | 60 | py |
RSP | RSP-main/Object Detection/configs/_base_/models/faster_rcnn_r50_caffe_c4.py | # model settings
norm_cfg = dict(type='BN', requires_grad=False)
model = dict(
type='FasterRCNN',
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(
type='ResNet',
depth=50,
num_stages=3,
strides=(1, 2, 2),
dilations=(1, 1, 1),
out_indices=(2,... | 3,452 | 29.026087 | 77 | py |
RSP | RSP-main/Object Detection/configs/_base_/models/mask_rcnn_r50_caffe_c4.py | # model settings
norm_cfg = dict(type='BN', requires_grad=False)
model = dict(
type='MaskRCNN',
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(
type='ResNet',
depth=50,
num_stages=3,
strides=(1, 2, 2),
dilations=(1, 1, 1),
out_indices=(2, )... | 3,827 | 28.90625 | 77 | py |
RSP | RSP-main/Object Detection/configs/obb/fcos_obb/fcos_obb_r50_caffe_fpn_gn-head_4x4_1x_dota10.py | _base_ = [
'../_base_/datasets/dota.py',
'../_base_/schedules/schedule_1x.py',
'../../_base_/default_runtime.py'
]
# model settings
model = dict(
type='FCOSOBB',
pretrained='open-mmlab://detectron/resnet50_caffe',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
... | 3,697 | 30.338983 | 81 | py |
RSP | RSP-main/Object Detection/configs/obb/gliding_vertex/gliding_vertex_r101_fpn_1x_dota10.py | _base_ = './gliding_vertex_r50_fpn_1x_dota10.py'
# model
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 135 | 26.2 | 76 | py |
RSP | RSP-main/Object Detection/configs/obb/gliding_vertex/gliding_vertex_r101_fpn_3x_hrsc.py | _base_ = './gliding_vertex_r50_fpn_3x_hrsc.py'
# model
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 133 | 25.8 | 76 | py |
RSP | RSP-main/Object Detection/configs/obb/gliding_vertex/gliding_vertex_r50_fpn_1x_dota10.py | _base_ = [
'../_base_/schedules/schedule_1x.py',
'../../_base_/default_runtime.py'
]
model = dict(
type='GlidingVertex',
pretrained='torchvision://resnet50',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
... | 6,759 | 31.344498 | 82 | py |
RSP | RSP-main/Object Detection/configs/obb/gliding_vertex/gliding_vertex_r50_fpn_3x_hrsc.py | _base_ = [
'../_base_/schedules/schedule_3x.py',
'../../_base_/default_runtime.py'
]
# default runtime
checkpoint_config = dict(interval=3)
model = dict(
type='GlidingVertex',
pretrained='torchvision://resnet50',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
... | 6,872 | 31.885167 | 82 | py |
RSP | RSP-main/Object Detection/configs/obb/retinanet_obb/retinanet_obb_r50_fpn_3x_hrsc.py | _base_ = [
'../_base_/datasets/hrsc.py',
'../_base_/schedules/schedule_3x.py',
'../../_base_/default_runtime.py'
]
# default runtime
checkpoint_config = dict(interval=3)
# lr schedule
optimizer = dict(type='SGD', lr=0.0025, momentum=0.9, weight_decay=0.0001)
# RetinaNet nms is slow in early stage, disable... | 2,115 | 26.480519 | 74 | py |
RSP | RSP-main/Object Detection/configs/obb/retinanet_obb/retinanet_obb_r50_fpn_1x_dota10.py | _base_ = [
'../_base_/datasets/dota.py',
'../_base_/schedules/schedule_1x.py',
'../../_base_/default_runtime.py'
]
optimizer = dict(type='SGD', lr=0.0025, momentum=0.9, weight_decay=0.0001)
# RetinaNet nms is slow in early stage, disable every epoch evaluation
evaluation = None
model = dict(
type='Re... | 2,047 | 26.675676 | 74 | py |
RSP | RSP-main/Object Detection/configs/obb/retinanet_obb/retinanet_obb_r101_fpn_1x_dota10.py | _base_ = './retinanet_obb_r50_fpn_1x_dota10.py'
# model
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 134 | 26 | 76 | py |
RSP | RSP-main/Object Detection/configs/obb/retinanet_obb/retinanet_obb_r101_fpn_3x_hrsc.py | _base_ = './retinanet_obb_r50_fpn_3x_hrsc.py'
# model
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 132 | 25.6 | 76 | py |
RSP | RSP-main/Object Detection/configs/obb/roi_transformer/faster_rcnn_roitrans_r50_fpn_3x_hrsc.py | _base_ = [
'../_base_/datasets/hrsc.py',
'../_base_/schedules/schedule_3x.py',
'../../_base_/default_runtime.py'
]
# default runtime
checkpoint_config = dict(interval=3)
model = dict(
type='RoITransformer',
pretrained='torchvision://resnet50',
backbone=dict(
type='ResNet',
dept... | 5,646 | 31.454023 | 81 | py |
RSP | RSP-main/Object Detection/configs/obb/roi_transformer/faster_rcnn_roitrans_r101_fpn_3x_hrsc.py | _base_ = './faster_rcnn_roitrans_r50_fpn_3x_hrsc.py'
# model
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 139 | 27 | 76 | py |
RSP | RSP-main/Object Detection/configs/obb/roi_transformer/faster_rcnn_roitrans_r101_fpn_1x_dota10.py | _base_ = './faster_rcnn_roitrans_r50_fpn_1x_dota10.py'
# model
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 141 | 27.4 | 76 | py |
RSP | RSP-main/Object Detection/configs/obb/roi_transformer/faster_rcnn_roitrans_r50_fpn_1x_dota10.py | _base_ = [
'../_base_/datasets/dota.py',
'../_base_/schedules/schedule_1x.py',
'../../_base_/default_runtime.py'
]
model = dict(
type='RoITransformer',
pretrained='torchvision://resnet50',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, ... | 5,593 | 31.523256 | 81 | py |
RSP | RSP-main/Object Detection/configs/obb/poly_iou_loss/retinanet_obb_r50_fpn_giouloss_1x_dota.py | _base_ = [
'../_base_/datasets/dota.py',
'../_base_/schedules/schedule_1x.py',
'../../_base_/default_runtime.py'
]
optimizer = dict(type='SGD', lr=0.0025, momentum=0.9, weight_decay=0.0001)
# RetinaNet nms is slow in early stage, disable every epoch evaluation
evaluation = None
model = dict(
type='Re... | 2,084 | 26.8 | 74 | py |
RSP | RSP-main/Object Detection/configs/obb/poly_iou_loss/retinanet_obb_r50_fpn_iouloss_1x_dota.py | _base_ = [
'../_base_/datasets/dota.py',
'../_base_/schedules/schedule_1x.py',
'../../_base_/default_runtime.py'
]
optimizer = dict(type='SGD', lr=0.0025, momentum=0.9, weight_decay=0.0001)
# RetinaNet nms is slow in early stage, disable every epoch evaluation
evaluation = None
model = dict(
type='Re... | 2,083 | 26.786667 | 74 | py |
RSP | RSP-main/Object Detection/configs/obb/faster_rcnn_obb/faster_rcnn_obb_r50_fpn_3x_hrsc.py | _base_ = [
'../_base_/datasets/hrsc.py',
'../_base_/schedules/schedule_3x.py',
'../../_base_/default_runtime.py'
]
# default runtime
checkpoint_config = dict(interval=3)
model = dict(
type='FasterRCNNOBB',
pretrained='torchvision://resnet50',
backbone=dict(
type='ResNet',
depth... | 3,696 | 29.303279 | 81 | py |
RSP | RSP-main/Object Detection/configs/obb/faster_rcnn_obb/faster_rcnn_obb_r101_fpn_3x_hrsc.py | _base_ = './faster_rcnn_obb_r50_fpn_3x_hrsc.py'
# model
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 134 | 26 | 76 | py |
RSP | RSP-main/Object Detection/configs/obb/faster_rcnn_obb/faster_rcnn_obb_r50_fpn_1x_dota10.py | _base_ = [
'../_base_/datasets/dota.py',
'../_base_/schedules/schedule_1x.py',
'../../_base_/default_runtime.py'
]
model = dict(
type='FasterRCNNOBB',
pretrained='torchvision://resnet50',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2,... | 3,639 | 29.588235 | 81 | py |
RSP | RSP-main/Object Detection/configs/obb/faster_rcnn_obb/faster_rcnn_obb_r101_fpn_1x_dota10.py | _base_ = './faster_rcnn_obb_r50_fpn_1x_dota10.py'
# model
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 136 | 26.4 | 76 | py |
RSP | RSP-main/Object Detection/configs/obb/s2anet/s2anet_r50_fpn_1x_dota10.py | _base_ = [
'../_base_/datasets/dota.py',
'../_base_/schedules/schedule_1x.py',
'../../_base_/default_runtime.py'
]
optimizer = dict(type='SGD', lr=0.0025, momentum=0.9, weight_decay=0.0001)
# RetinaNet nms is slow in early stage, disable every epoch evaluation
evaluation = None
model = dict(
type='S2A... | 4,063 | 31.253968 | 109 | py |
RSP | RSP-main/Object Detection/configs/obb/oriented_rcnn/orpn_r101_fpn_1x_dota10.py | _base_ = './orpn_r50_fpn_1x_dota10.py'
# model
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 125 | 24.2 | 76 | py |
RSP | RSP-main/Object Detection/configs/obb/oriented_rcnn/faster_rcnn_orpn_rsp_r50_fpn_3x_hrsc.py | _base_ = [
'../_base_/datasets/hrsc.py',
'../_base_/schedules/schedule_3x.py',
'../../_base_/default_runtime.py'
]
model = dict(
type='OrientedRCNN',
pretrained = '/public/data3/users/wangdi153/RS_CV/RS_CLS_finetune/output/resnet_50_224/epoch300/millionAID_224_None/0.0005_0.05_128/resnet/100/ckpt.p... | 3,858 | 30.892562 | 157 | py |
RSP | RSP-main/Object Detection/configs/obb/oriented_rcnn/faster_rcnn_orpn_r101_fpn_3x_hrsc.py | _base_ = './faster_rcnn_orpn_r50_fpn_3x_hrsc.py'
# model
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 135 | 26.2 | 76 | py |
RSP | RSP-main/Object Detection/configs/obb/oriented_rcnn/faster_rcnn_orpn_rsp_r50_fpn_1x_dota10.py | _base_ = [
'../_base_/datasets/dota.py',
'../_base_/schedules/schedule_1x.py',
'../../_base_/default_runtime.py'
]
model = dict(
type='OrientedRCNN',
#pretrained='/public/data3/users/wangdi153/RS_CV/pretrain_model/resnet50-19c8e357.pth',
pretrained = '/public/data3/users/wangdi153/RS_CV/RS_CLS... | 3,951 | 31.130081 | 156 | py |
RSP | RSP-main/Object Detection/configs/obb/oriented_rcnn/orpn_r50_fpn_1x_dota10.py | _base_ = [
'../_base_/schedules/schedule_1x.py',
'../../_base_/default_runtime.py'
]
model = dict(
type='OBBRPN',
pretrained='torchvision://resnet50',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
no... | 4,966 | 30.04375 | 80 | py |
RSP | RSP-main/Object Detection/configs/obb/oriented_rcnn/faster_rcnn_orpn_seco_r50_fpn_1x_dota10.py | _base_ = [
'../_base_/datasets/dota.py',
'../_base_/schedules/schedule_1x.py',
'../../_base_/default_runtime.py'
]
model = dict(
type='OrientedRCNN',
pretrained = '/public/data3/users/wangdi153/RS_CV/pretrain_model/seco_resnet50_1m.pth',
backbone=dict(
type='ResNet',
depth=50,
... | 3,794 | 30.106557 | 91 | py |
RSP | RSP-main/Object Detection/configs/obb/oriented_rcnn/faster_rcnn_orpn_r101_fpn_1x_ms_rr_dota10.py | _base_ = './faster_rcnn_orpn_r50_fpn_1x_ms_rr_dota10.py'
# model
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 143 | 27.8 | 76 | py |
RSP | RSP-main/Object Detection/configs/obb/oriented_rcnn/faster_rcnn_orpn_r50_fpn_1x_dota10.py | _base_ = [
'../_base_/datasets/dota.py',
'../_base_/schedules/schedule_1x.py',
'../../_base_/default_runtime.py'
]
model = dict(
type='OrientedRCNN',
pretrained='../pretrain_model/resnet50-19c8e357.pth',
#pretrained = '/public/data3/users/wangdi153/RS_CV/RS_CLS_finetune/output/resnet_50_224/ep... | 3,919 | 30.869919 | 158 | py |
RSP | RSP-main/Object Detection/configs/obb/oriented_rcnn/faster_rcnn_orpn_r101_fpn_1x_dota10.py | _base_ = './faster_rcnn_orpn_r50_fpn_1x_dota10.py'
# model
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 137 | 26.6 | 76 | py |
RSP | RSP-main/Object Detection/configs/obb/oriented_rcnn/faster_rcnn_orpn_r50_fpn_3x_hrsc.py | _base_ = [
'../_base_/datasets/hrsc.py',
'../_base_/schedules/schedule_3x.py',
'../../_base_/default_runtime.py'
]
model = dict(
type='OrientedRCNN',
pretrained='/public/data3/users/wangdi153/RS_CV/pretrain_model/resnet50-19c8e357.pth',
backbone=dict(
type='ResNet',
depth=50,
... | 3,791 | 30.338843 | 90 | py |
RSP | RSP-main/Object Detection/configs/obb/oriented_rcnn/faster_rcnn_orpn_seco_r50_fpn_3x_hrsc.py | _base_ = [
'../_base_/datasets/hrsc.py',
'../_base_/schedules/schedule_3x.py',
'../../_base_/default_runtime.py'
]
model = dict(
type='OrientedRCNN',
pretrained = '/public/data3/users/wangdi153/RS_CV/pretrain_model/seco_resnet50_1m.pth',
backbone=dict(
type='ResNet',
depth=50,
... | 3,792 | 30.347107 | 91 | py |
RSP | RSP-main/Object Detection/configs/obb/random_fp/fcos_obb_r50_caffe_fpn_gn-head_4x4_1x_01fp_dota10.py | _base_ = [
'./datasets/01fp_dota10.py',
'../_base_/schedules/schedule_1x.py',
'../../_base_/default_runtime.py'
]
# model settings
model = dict(
type='FCOSOBB',
pretrained='open-mmlab://detectron/resnet50_caffe',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
... | 3,696 | 30.330508 | 81 | py |
RSP | RSP-main/Object Detection/configs/obb/random_fp/fcos_obb_r50_caffe_fpn_gn-head_4x4_1x_05fp_dota10.py | _base_ = [
'./datasets/05fp_dota10.py',
'../_base_/schedules/schedule_1x.py',
'../../_base_/default_runtime.py'
]
# model settings
model = dict(
type='FCOSOBB',
pretrained='open-mmlab://detectron/resnet50_caffe',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
... | 3,696 | 30.330508 | 81 | py |
RSP | RSP-main/Object Detection/configs/obb/random_fp/fcos_obb_r50_caffe_fpn_gn-head_4x4_1x_03fp_dota10.py | _base_ = [
'./datasets/03fp_dota10.py',
'../_base_/schedules/schedule_1x.py',
'../../_base_/default_runtime.py'
]
# model settings
model = dict(
type='FCOSOBB',
pretrained='open-mmlab://detectron/resnet50_caffe',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
... | 3,696 | 30.330508 | 81 | py |
RSP | RSP-main/Object Detection/configs/libra_rcnn/libra_faster_rcnn_r101_fpn_1x_coco.py | _base_ = './libra_faster_rcnn_r50_fpn_1x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 127 | 41.666667 | 76 | py |
RSP | RSP-main/Object Detection/configs/libra_rcnn/libra_faster_rcnn_x101_64x4d_fpn_1x_coco.py | _base_ = './libra_faster_rcnn_r50_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://resnext101_64x4d',
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(ty... | 376 | 25.928571 | 53 | py |
RSP | RSP-main/Object Detection/configs/retinanet/retinanet_r101_caffe_fpn_1x_coco.py | _base_ = './retinanet_r50_caffe_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnet101_caffe',
backbone=dict(depth=101))
| 150 | 29.2 | 57 | py |
RSP | RSP-main/Object Detection/configs/retinanet/retinanet_x101_64x4d_fpn_2x_coco.py | _base_ = './retinanet_r50_fpn_2x_coco.py'
model = dict(
pretrained='open-mmlab://resnext101_64x4d',
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',... | 368 | 25.357143 | 53 | py |
RSP | RSP-main/Object Detection/configs/retinanet/retinanet_x101_32x4d_fpn_1x_coco.py | _base_ = './retinanet_r50_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://resnext101_32x4d',
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',... | 368 | 25.357143 | 53 | py |
RSP | RSP-main/Object Detection/configs/retinanet/retinanet_r50_caffe_fpn_mstrain_1x_coco.py | _base_ = './retinanet_r50_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(
norm_cfg=dict(requires_grad=False), norm_eval=True, style='caffe'))
# use caffe img_norm
img_norm_cfg = dict(
mean=[103.530, 116.280, 123.675], std=[1.0, 1.0, 1.0], to_rgb=Fals... | 1,473 | 33.27907 | 75 | py |
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