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 |
|---|---|---|---|---|---|---|
RSP | RSP-main/Object Detection/configs/retinanet/retinanet_r50_caffe_fpn_mstrain_2x_coco.py | _base_ = './retinanet_r50_caffe_fpn_mstrain_1x_coco.py'
# learning policy
lr_config = dict(step=[16, 23])
total_epochs = 24
| 124 | 24 | 55 | py |
RSP | RSP-main/Object Detection/configs/retinanet/retinanet_r50_caffe_fpn_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... | 1,329 | 34 | 75 | py |
RSP | RSP-main/Object Detection/configs/retinanet/retinanet_r101_fpn_2x_coco.py | _base_ = './retinanet_r50_fpn_2x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 119 | 39 | 76 | py |
RSP | RSP-main/Object Detection/configs/retinanet/retinanet_r50_caffe_fpn_mstrain_3x_coco.py | _base_ = './retinanet_r50_caffe_fpn_mstrain_1x_coco.py'
# learning policy
lr_config = dict(step=[28, 34])
total_epochs = 36
| 124 | 24 | 55 | py |
RSP | RSP-main/Object Detection/configs/retinanet/retinanet_x101_64x4d_fpn_1x_coco.py | _base_ = './retinanet_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',... | 368 | 25.357143 | 53 | py |
RSP | RSP-main/Object Detection/configs/retinanet/retinanet_r101_fpn_1x_coco.py | _base_ = './retinanet_r50_fpn_1x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 119 | 39 | 76 | py |
RSP | RSP-main/Object Detection/configs/retinanet/retinanet_x101_32x4d_fpn_2x_coco.py | _base_ = './retinanet_r50_fpn_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,
norm_cfg=dict(type='BN',... | 368 | 25.357143 | 53 | py |
RSP | RSP-main/Object Detection/configs/free_anchor/retinanet_free_anchor_x101_32x4d_fpn_1x_coco.py | _base_ = './retinanet_free_anchor_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,
style='pytor... | 326 | 24.153846 | 53 | py |
RSP | RSP-main/Object Detection/configs/free_anchor/retinanet_free_anchor_r101_fpn_1x_coco.py | _base_ = './retinanet_free_anchor_r50_fpn_1x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 131 | 43 | 76 | py |
RSP | RSP-main/Object Detection/configs/faster_rcnn/faster_rcnn_r101_caffe_fpn_1x_coco.py | _base_ = './faster_rcnn_r50_caffe_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnet101_caffe',
backbone=dict(depth=101))
| 152 | 29.6 | 57 | py |
RSP | RSP-main/Object Detection/configs/faster_rcnn/faster_rcnn_x101_32x4d_fpn_1x_coco.py | _base_ = './faster_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... | 370 | 25.5 | 53 | py |
RSP | RSP-main/Object Detection/configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_1x_coco.py | _base_ = './faster_rcnn_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=Fa... | 1,475 | 33.325581 | 75 | py |
RSP | RSP-main/Object Detection/configs/faster_rcnn/faster_rcnn_r101_fpn_2x_coco.py | _base_ = './faster_rcnn_r50_fpn_2x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 121 | 39.666667 | 76 | py |
RSP | RSP-main/Object Detection/configs/faster_rcnn/faster_rcnn_x101_64x4d_fpn_1x_coco.py | _base_ = './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(type='BN... | 370 | 25.5 | 53 | py |
RSP | RSP-main/Object Detection/configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_2x_coco.py | _base_ = './faster_rcnn_r50_caffe_fpn_mstrain_1x_coco.py'
# learning policy
lr_config = dict(step=[16, 23])
total_epochs = 24
| 126 | 24.4 | 57 | py |
RSP | RSP-main/Object Detection/configs/faster_rcnn/faster_rcnn_r101_fpn_1x_coco.py | _base_ = './faster_rcnn_r50_fpn_1x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 121 | 39.666667 | 76 | py |
RSP | RSP-main/Object Detection/configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_1x_coco.py | _base_ = './faster_rcnn_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=Fa... | 1,331 | 34.052632 | 75 | py |
RSP | RSP-main/Object Detection/configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_3x_coco.py | _base_ = './faster_rcnn_r50_caffe_fpn_mstrain_1x_coco.py'
# learning policy
lr_config = dict(step=[28, 34])
total_epochs = 36
| 126 | 24.4 | 57 | py |
RSP | RSP-main/Object Detection/configs/faster_rcnn/faster_rcnn_x101_32x4d_fpn_2x_coco.py | _base_ = './faster_rcnn_r50_fpn_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,
norm_cfg=dict(type='BN... | 370 | 25.5 | 53 | py |
RSP | RSP-main/Object Detection/configs/faster_rcnn/faster_rcnn_r50_caffe_c4_1x_coco.py | _base_ = [
'../_base_/models/faster_rcnn_r50_caffe_c4.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# 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)
train_pipeline = [
... | 1,388 | 33.725 | 72 | py |
RSP | RSP-main/Object Detection/configs/faster_rcnn/faster_rcnn_x101_64x4d_fpn_2x_coco.py | _base_ = './faster_rcnn_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... | 370 | 25.5 | 53 | py |
RSP | RSP-main/Object Detection/configs/mask_rcnn/mask_rcnn_x101_32x4d_fpn_2x_coco.py | _base_ = './mask_rcnn_r101_fpn_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,
norm_cfg=dict(type='BN'... | 369 | 25.428571 | 53 | py |
RSP | RSP-main/Object Detection/configs/mask_rcnn/mask_rcnn_r101_fpn_1x_coco.py | _base_ = './mask_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/mask_rcnn/mask_rcnn_x101_32x8d_fpn_1x_coco.py | _base_ = './mask_rcnn_r101_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnext101_32x8d',
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=dic... | 2,069 | 31.34375 | 77 | py |
RSP | RSP-main/Object Detection/configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_mstrain-poly_1x_coco.py | _base_ = './mask_rcnn_r50_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(norm_cfg=dict(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)
train_pipeline = [
... | 1,526 | 32.195652 | 77 | py |
RSP | RSP-main/Object Detection/configs/mask_rcnn/mask_rcnn_x101_32x8d_fpn_mstrain-poly_1x_coco.py | _base_ = './mask_rcnn_r101_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnext101_32x8d',
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=dic... | 1,775 | 29.101695 | 77 | py |
RSP | RSP-main/Object Detection/configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_mstrain-poly_2x_coco.py | _base_ = './mask_rcnn_r50_caffe_fpn_mstrain-poly_1x_coco.py'
# learning policy
lr_config = dict(step=[16, 23])
total_epochs = 24
| 129 | 25 | 60 | py |
RSP | RSP-main/Object Detection/configs/mask_rcnn/mask_rcnn_x101_64x4d_fpn_2x_coco.py | _base_ = './mask_rcnn_x101_32x4d_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(typ... | 375 | 25.857143 | 53 | py |
RSP | RSP-main/Object Detection/configs/mask_rcnn/mask_rcnn_r101_caffe_fpn_1x_coco.py | _base_ = './mask_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/mask_rcnn/mask_rcnn_r50_caffe_c4_1x_coco.py | _base_ = [
'../_base_/models/mask_rcnn_r50_caffe_c4.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# 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)
train_pipeline = [
dic... | 1,413 | 34.35 | 77 | py |
RSP | RSP-main/Object Detection/configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_mstrain_1x_coco.py | _base_ = './mask_rcnn_r50_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(norm_cfg=dict(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)
train_pipeline = [
... | 1,476 | 34.166667 | 77 | py |
RSP | RSP-main/Object Detection/configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_poly_1x_coco_v1.py | _base_ = './mask_rcnn_r50_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://resnet50_caffe_bgr',
backbone=dict(norm_cfg=dict(requires_grad=False), style='caffe'),
rpn_head=dict(
loss_bbox=dict(type='SmoothL1Loss', beta=1.0 / 9.0, loss_weight=1.0)),
roi_head=dict(
bbox_roi_extractor=... | 1,869 | 34.961538 | 78 | py |
RSP | RSP-main/Object Detection/configs/mask_rcnn/mask_rcnn_x101_32x8d_fpn_mstrain-poly_3x_coco.py | _base_ = './mask_rcnn_r101_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnext101_32x8d',
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=dic... | 1,826 | 28.467742 | 77 | py |
RSP | RSP-main/Object Detection/configs/mask_rcnn/mask_rcnn_r101_fpn_2x_coco.py | _base_ = './mask_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/mask_rcnn/mask_rcnn_x101_32x4d_fpn_1x_coco.py | _base_ = './mask_rcnn_r101_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'... | 369 | 25.428571 | 53 | py |
RSP | RSP-main/Object Detection/configs/mask_rcnn/mask_rcnn_x101_64x4d_fpn_1x_coco.py | _base_ = './mask_rcnn_x101_32x4d_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(typ... | 375 | 25.857143 | 53 | py |
RSP | RSP-main/Object Detection/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])
total_epochs = 36
| 129 | 25 | 60 | py |
RSP | RSP-main/Object Detection/configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_1x_coco.py | _base_ = './mask_rcnn_r50_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(norm_cfg=dict(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)
train_pipeline = [
... | 1,332 | 35.027027 | 77 | py |
RSP | RSP-main/Object Detection/configs/cascade_rcnn/cascade_mask_rcnn_x101_32x4d_fpn_20e_coco.py | _base_ = './cascade_mask_rcnn_r50_fpn_20e_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(t... | 377 | 26 | 53 | py |
RSP | RSP-main/Object Detection/configs/cascade_rcnn/cascade_rcnn_r50_caffe_fpn_1x_coco.py | _base_ = './cascade_rcnn_r50_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(norm_cfg=dict(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)
train_pipeline = ... | 1,309 | 32.589744 | 72 | py |
RSP | RSP-main/Object Detection/configs/cascade_rcnn/cascade_mask_rcnn_r50_caffe_fpn_1x_coco.py | _base_ = ['./cascade_mask_rcnn_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'))
img_norm_cfg = dict(
mean=[103.530, 116.280, 123.675], std=[1.0, 1.0, 1.0], to_rgb=False)
train_... | 1,348 | 33.589744 | 77 | py |
RSP | RSP-main/Object Detection/configs/cascade_rcnn/cascade_rcnn_x101_32x4d_fpn_20e_coco.py | _base_ = './cascade_rcnn_r50_fpn_20e_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='... | 372 | 25.642857 | 53 | py |
RSP | RSP-main/Object Detection/configs/cascade_rcnn/cascade_rcnn_r101_fpn_1x_coco.py | _base_ = './cascade_rcnn_r50_fpn_1x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 122 | 40 | 76 | py |
RSP | RSP-main/Object Detection/configs/cascade_rcnn/cascade_mask_rcnn_r101_fpn_20e_coco.py | _base_ = './cascade_mask_rcnn_r50_fpn_20e_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 128 | 42 | 76 | py |
RSP | RSP-main/Object Detection/configs/cascade_rcnn/cascade_mask_rcnn_r101_caffe_fpn_1x_coco.py | _base_ = './cascade_mask_rcnn_r50_caffe_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnet101_caffe',
backbone=dict(depth=101))
| 158 | 30.8 | 57 | py |
RSP | RSP-main/Object Detection/configs/cascade_rcnn/cascade_rcnn_x101_64x4d_fpn_1x_coco.py | _base_ = './cascade_rcnn_r50_fpn_1x_coco.py'
model = dict(
type='CascadeRCNN',
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,
... | 395 | 25.4 | 53 | py |
RSP | RSP-main/Object Detection/configs/cascade_rcnn/cascade_mask_rcnn_x101_64x4d_fpn_1x_coco.py | _base_ = './cascade_mask_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/cascade_rcnn/cascade_rcnn_x101_64x4d_fpn_20e_coco.py | _base_ = './cascade_rcnn_r50_fpn_20e_coco.py'
model = dict(
type='CascadeRCNN',
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,
... | 396 | 25.466667 | 53 | py |
RSP | RSP-main/Object Detection/configs/cascade_rcnn/cascade_rcnn_x101_32x4d_fpn_1x_coco.py | _base_ = './cascade_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='B... | 371 | 25.571429 | 53 | py |
RSP | RSP-main/Object Detection/configs/cascade_rcnn/cascade_rcnn_r101_caffe_fpn_1x_coco.py | _base_ = './cascade_rcnn_r50_caffe_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnet101_caffe',
backbone=dict(depth=101))
| 153 | 29.8 | 57 | py |
RSP | RSP-main/Object Detection/configs/cascade_rcnn/cascade_mask_rcnn_x101_64x4d_fpn_20e_coco.py | _base_ = './cascade_mask_rcnn_r50_fpn_20e_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(t... | 377 | 26 | 53 | py |
RSP | RSP-main/Object Detection/configs/cascade_rcnn/cascade_mask_rcnn_x101_32x4d_fpn_1x_coco.py | _base_ = './cascade_mask_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(ty... | 376 | 25.928571 | 53 | py |
RSP | RSP-main/Object Detection/configs/cascade_rcnn/cascade_rcnn_r101_fpn_20e_coco.py | _base_ = './cascade_rcnn_r50_fpn_20e_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 123 | 40.333333 | 76 | py |
RSP | RSP-main/Object Detection/configs/cascade_rcnn/cascade_mask_rcnn_r101_fpn_1x_coco.py | _base_ = './cascade_mask_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/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',
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indi... | 2,864 | 27.939394 | 73 | py |
RSP | RSP-main/Object Detection/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',
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indi... | 2,886 | 27.87 | 73 | py |
RSP | RSP-main/Object Detection/configs/rpn/rpn_x101_64x4d_fpn_2x_coco.py | _base_ = './rpn_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', requi... | 362 | 24.928571 | 53 | py |
RSP | RSP-main/Object Detection/configs/rpn/rpn_x101_32x4d_fpn_2x_coco.py | _base_ = './rpn_r50_fpn_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,
norm_cfg=dict(type='BN', requi... | 362 | 24.928571 | 53 | py |
RSP | RSP-main/Object Detection/configs/rpn/rpn_x101_64x4d_fpn_1x_coco.py | _base_ = './rpn_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', requi... | 362 | 24.928571 | 53 | py |
RSP | RSP-main/Object Detection/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 |
RSP | RSP-main/Object Detection/configs/rpn/rpn_r50_caffe_fpn_1x_coco.py | _base_ = './rpn_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=False)
tra... | 1,328 | 33.973684 | 75 | py |
RSP | RSP-main/Object Detection/configs/rpn/rpn_r101_fpn_1x_coco.py | _base_ = './rpn_r50_fpn_1x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 113 | 37 | 76 | py |
RSP | RSP-main/Object Detection/configs/rpn/rpn_x101_32x4d_fpn_1x_coco.py | _base_ = './rpn_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', requi... | 362 | 24.928571 | 53 | py |
RSP | RSP-main/Object Detection/configs/rpn/rpn_r101_caffe_fpn_1x_coco.py | _base_ = './rpn_r50_caffe_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnet101_caffe',
backbone=dict(depth=101))
| 144 | 28 | 57 | py |
RSP | RSP-main/Object Detection/configs/rpn/rpn_r101_fpn_2x_coco.py | _base_ = './rpn_r50_fpn_2x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 113 | 37 | 76 | py |
RSP | RSP-main/Object Detection/configs/lvis/mask_rcnn_x101_32x4d_fpn_sample1e-3_mstrain_2x_lvis.py | _base_ = './mask_rcnn_r50_fpn_sample1e-3_mstrain_2x_lvis.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_... | 387 | 26.714286 | 60 | py |
RSP | RSP-main/Object Detection/configs/lvis/mask_rcnn_r101_fpn_sample1e-3_mstrain_2x_lvis.py | _base_ = './mask_rcnn_r50_fpn_sample1e-3_mstrain_2x_lvis.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 138 | 45.333333 | 76 | py |
RSP | RSP-main/Object Detection/configs/lvis/mask_rcnn_x101_64x4d_fpn_sample1e-3_mstrain_2x_lvis.py | _base_ = './mask_rcnn_r50_fpn_sample1e-3_mstrain_2x_lvis.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_... | 387 | 26.714286 | 60 | py |
RSP | RSP-main/Object Detection/configs/instaboost/mask_rcnn_x101_64x4d_fpn_instaboost_4x_coco.py | _base_ = './mask_rcnn_r50_fpn_instaboost_4x_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... | 379 | 26.142857 | 53 | py |
RSP | RSP-main/Object Detection/configs/instaboost/mask_rcnn_r101_fpn_instaboost_4x_coco.py | _base_ = './mask_rcnn_r50_fpn_instaboost_4x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 130 | 42.666667 | 76 | py |
RSP | RSP-main/Object Detection/configs/instaboost/cascade_mask_rcnn_r101_fpn_instaboost_4x_coco.py | _base_ = './cascade_mask_rcnn_r50_fpn_instaboost_4x_coco.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 139 | 34 | 76 | py |
RSP | RSP-main/Object Detection/configs/instaboost/cascade_mask_rcnn_x101_64x4d_fpn_instaboost_4x_coco.py | _base_ = './cascade_mask_rcnn_r50_fpn_instaboost_4x_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_... | 387 | 26.714286 | 60 | py |
RSP | RSP-main/Object Detection/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',
pretrained='torchvision://resnet50',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
... | 1,835 | 28.142857 | 73 | py |
RSP | RSP-main/Object Detection/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(
pretrained='open-mmlab://jhu/resnext50_32x4d_gn_ws',
backbone=dict(
type='ResNeXt',
depth=50,
groups=32,
base_width=4,
... | 481 | 27.352941 | 61 | py |
RSP | RSP-main/Object Detection/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(
pretrained='open-mmlab://jhu/resnext101_32x4d_gn_ws',
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
... | 498 | 26.722222 | 61 | py |
RSP | RSP-main/Object Detection/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(
pretrained='open-mmlab://jhu/resnext101_32x4d_gn_ws',
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
base_width=4... | 483 | 27.470588 | 61 | py |
RSP | RSP-main/Object Detection/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(
pretrained='open-mmlab://jhu/resnext50_32x4d_gn_ws',
backbone=dict(
type='ResNeXt',
depth=50,
groups=32,
... | 496 | 26.611111 | 61 | py |
RSP | RSP-main/Object Detection/configs/guided_anchoring/ga_faster_x101_64x4d_fpn_1x_coco.py | _base_ = './ga_faster_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',... | 368 | 25.357143 | 53 | py |
RSP | RSP-main/Object Detection/configs/guided_anchoring/ga_faster_x101_32x4d_fpn_1x_coco.py | _base_ = './ga_faster_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/guided_anchoring/ga_retinanet_x101_32x4d_fpn_1x_coco.py | _base_ = './ga_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='B... | 371 | 25.571429 | 53 | py |
RSP | RSP-main/Object Detection/configs/guided_anchoring/ga_rpn_x101_32x4d_fpn_1x_coco.py | _base_ = './ga_rpn_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', re... | 365 | 25.142857 | 53 | py |
RSP | RSP-main/Object Detection/configs/guided_anchoring/ga_rpn_r101_caffe_fpn_1x_coco.py | _base_ = './ga_rpn_r50_caffe_fpn_1x_coco.py'
# model settings
model = dict(
pretrained='open-mmlab://detectron2/resnet101_caffe',
backbone=dict(depth=101))
| 164 | 26.5 | 57 | py |
RSP | RSP-main/Object Detection/configs/guided_anchoring/ga_retinanet_x101_64x4d_fpn_1x_coco.py | _base_ = './ga_retinanet_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='B... | 371 | 25.571429 | 53 | py |
RSP | RSP-main/Object Detection/configs/guided_anchoring/ga_faster_r101_caffe_fpn_1x_coco.py | _base_ = './ga_faster_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/guided_anchoring/ga_rpn_x101_64x4d_fpn_1x_coco.py | _base_ = './ga_rpn_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', re... | 365 | 25.142857 | 53 | py |
RSP | RSP-main/Object Detection/configs/guided_anchoring/ga_fast_r50_caffe_fpn_1x_coco.py | _base_ = '../fast_rcnn/fast_rcnn_r50_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnet50_caffe',
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),
... | 2,322 | 35.296875 | 78 | py |
RSP | RSP-main/Object Detection/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... | 2,271 | 33.953846 | 77 | py |
RSP | RSP-main/Object Detection/configs/guided_anchoring/ga_retinanet_r101_caffe_fpn_1x_coco.py | _base_ = './ga_retinanet_r50_caffe_fpn_1x_coco.py'
model = dict(
pretrained='open-mmlab://detectron2/resnet101_caffe',
backbone=dict(depth=101))
| 153 | 29.8 | 57 | py |
RSP | RSP-main/Object Detection/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',
... | 1,988 | 30.571429 | 74 | py |
RSP | RSP-main/Object Detection/configs/guided_anchoring/ga_retinanet_r101_caffe_fpn_mstrain_2x.py | # model settings
model = dict(
type='RetinaNet',
pretrained='open-mmlab://detectron2/resnet101_caffe',
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... | 5,149 | 28.768786 | 74 | py |
RSP | RSP-main/Object Detection/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,... | 1,913 | 32 | 74 | py |
RSP | RSP-main/Object Detection/mmdet/apis/inference.py | import warnings
import matplotlib.pyplot as plt
import mmcv
import torch
from mmcv.parallel import collate, scatter
from mmcv.runner import load_checkpoint
from mmdet.core import get_classes
from mmdet.datasets.pipelines import Compose
from mmdet.models import build_detector
from mmdet.ops import RoIAlign, RoIPool
... | 5,587 | 33.282209 | 79 | py |
RSP | RSP-main/Object Detection/mmdet/apis/test.py | import os.path as osp
import pickle
import shutil
import tempfile
import time
import mmcv
import torch
import torch.distributed as dist
from mmcv.runner import get_dist_info
from mmdet.core import encode_mask_results, tensor2imgs
def single_gpu_test(model,
data_loader,
show=F... | 6,682 | 34.547872 | 79 | py |
RSP | RSP-main/Object Detection/mmdet/apis/train.py | import random
import numpy as np
import torch
from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
from mmcv.runner import (DistSamplerSeedHook, EpochBasedRunner, OptimizerHook,
build_optimizer)
from mmdet.core import DistEvalHook, EvalHook, Fp16OptimizerHook, RandomFPHook
from... | 4,831 | 35.059701 | 79 | py |
RSP | RSP-main/Object Detection/mmdet/apis/obb/huge_img_inference.py | import mmcv
import json
import torch
import warnings
import numpy as np
import os.path as osp
import BboxToolkit as bt
from math import ceil
from itertools import product
from mmcv.parallel import collate, scatter
from mmdet.datasets.pipelines import Compose
from mmdet.ops import RoIAlign, RoIPool, nms, nms_rotated
... | 5,913 | 33.584795 | 77 | py |
RSP | RSP-main/Object Detection/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... | 4,942 | 37.92126 | 76 | py |
RSP | RSP-main/Object Detection/mmdet/core/post_processing/merge_augs.py | import numpy as np
import torch
from mmdet.ops import nms
from ..bbox import bbox_mapping_back
def merge_aug_proposals(aug_proposals, img_metas, rpn_test_cfg):
"""Merge augmented proposals (multiscale, flip, etc.)
Args:
aug_proposals (list[Tensor]): proposals from different testing
schem... | 4,171 | 34.965517 | 78 | py |
RSP | RSP-main/Object Detection/mmdet/core/post_processing/bbox_nms.py | import torch
from mmdet.ops.nms import batched_nms
def multiclass_nms(multi_bboxes,
multi_scores,
score_thr,
nms_cfg,
max_num=-1,
score_factors=None):
"""NMS for multi-class bboxes.
Args:
multi_bboxes (Ten... | 1,892 | 31.637931 | 78 | py |
RSP | RSP-main/Object Detection/mmdet/core/post_processing/obb/obb_merge_augs.py | import numpy as np
import torch
from mmdet.ops import nms, obb_nms, poly_nms
from mmdet.core import regular_theta, choice_by_type
from mmdet.core import hbb_mapping_back, obb_mapping_back, poly_mapping_back
pi = 3.141592
def merge_rotate_aug_proposals(aug_proposals, img_metas, rpn_test_cfg):
recovered_proposals... | 8,721 | 39.009174 | 83 | py |
RSP | RSP-main/Object Detection/mmdet/core/post_processing/obb/obb_nms.py | import torch
from mmdet.ops.nms_rotated import arb_batched_nms
from mmdet.core.bbox.transforms_obb import get_bbox_dim
def multiclass_arb_nms(multi_bboxes,
multi_scores,
score_thr,
nms_cfg,
max_num=-1,
... | 1,349 | 30.395349 | 72 | py |
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