repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gn/mask-rcnn_r50_fpn_gn-all_3x_coco.py | configs/gn/mask-rcnn_r50_fpn_gn-all_3x_coco.py | _base_ = './mask-rcnn_r50_fpn_gn-all_2x_coco.py'
# learning policy
max_epochs = 36
train_cfg = dict(max_epochs=max_epochs)
# learning rate
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
begin=0,
end=ma... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/scratch/mask-rcnn_r50-scratch_fpn_gn-all_6x_coco.py | configs/scratch/mask-rcnn_r50-scratch_fpn_gn-all_6x_coco.py | _base_ = [
'../_base_/models/mask-rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
norm_cfg = dict(type='GN', num_groups=32, requires_grad=True)
model = dict(
backbone=dict(
frozen_stages=-1,
zero_init_residua... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/scratch/faster-rcnn_r50-scratch_fpn_gn-all_6x_coco.py | configs/scratch/faster-rcnn_r50-scratch_fpn_gn-all_6x_coco.py | _base_ = [
'../_base_/models/faster-rcnn_r50_fpn.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
norm_cfg = dict(type='GN', num_groups=32, requires_grad=True)
model = dict(
backbone=dict(
frozen_stages=-1,
zero_init_resi... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/panoptic_fpn/panoptic-fpn_r101_fpn_ms-3x_coco.py | configs/panoptic_fpn/panoptic-fpn_r101_fpn_ms-3x_coco.py | _base_ = './panoptic-fpn_r50_fpn_ms-3x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/panoptic_fpn/panoptic-fpn_r50_fpn_ms-3x_coco.py | configs/panoptic_fpn/panoptic-fpn_r50_fpn_ms-3x_coco.py | _base_ = './panoptic-fpn_r50_fpn_1x_coco.py'
# In mstrain 3x config, img_scale=[(1333, 640), (1333, 800)],
# multiscale_mode='range'
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='LoadPanopticAnnotations',
with_bbox=True,
with_mask=True,
with_seg=True),
dict(... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/panoptic_fpn/panoptic-fpn_r101_fpn_1x_coco.py | configs/panoptic_fpn/panoptic-fpn_r101_fpn_1x_coco.py | _base_ = './panoptic-fpn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/panoptic_fpn/panoptic-fpn_r50_fpn_1x_coco.py | configs/panoptic_fpn/panoptic-fpn_r50_fpn_1x_coco.py | _base_ = [
'../_base_/models/mask-rcnn_r50_fpn.py',
'../_base_/datasets/coco_panoptic.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
type='PanopticFPN',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/solov2/solov2_x101-dcn_fpn_ms-3x_coco.py | configs/solov2/solov2_x101-dcn_fpn_ms-3x_coco.py | _base_ = './solov2_r50_fpn_ms-3x_coco.py'
# model settings
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
dcn=dict(type='DCNv2', deformable_groups=1, fallback_on_stride=False),
stage_with_dcn=(False, True, True, True),
init_c... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/solov2/solov2-light_r18_fpn_ms-3x_coco.py | configs/solov2/solov2-light_r18_fpn_ms-3x_coco.py | _base_ = './solov2-light_r50_fpn_ms-3x_coco.py'
# model settings
model = dict(
backbone=dict(
depth=18, init_cfg=dict(checkpoint='torchvision://resnet18')),
neck=dict(in_channels=[64, 128, 256, 512]))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/solov2/solov2_r101-dcn_fpn_ms-3x_coco.py | configs/solov2/solov2_r101-dcn_fpn_ms-3x_coco.py | _base_ = './solov2_r50_fpn_ms-3x_coco.py'
# model settings
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(checkpoint='torchvision://resnet101'),
dcn=dict(type='DCNv2', deformable_groups=1, fallback_on_stride=False),
stage_with_dcn=(False, True, True, True)),
mask_head=dic... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/solov2/solov2_r101_fpn_ms-3x_coco.py | configs/solov2/solov2_r101_fpn_ms-3x_coco.py | _base_ = './solov2_r50_fpn_ms-3x_coco.py'
# model settings
model = dict(
backbone=dict(
depth=101, init_cfg=dict(checkpoint='torchvision://resnet101')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/solov2/solov2-light_r34_fpn_ms-3x_coco.py | configs/solov2/solov2-light_r34_fpn_ms-3x_coco.py | _base_ = './solov2-light_r50_fpn_ms-3x_coco.py'
# model settings
model = dict(
backbone=dict(
depth=34, init_cfg=dict(checkpoint='torchvision://resnet34')),
neck=dict(in_channels=[64, 128, 256, 512]))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/solov2/solov2_r50_fpn_1x_coco.py | configs/solov2/solov2_r50_fpn_1x_coco.py | _base_ = [
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# model settings
model = dict(
type='SOLOv2',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/solov2/solov2-light_r50-dcn_fpn_ms-3x_coco.py | configs/solov2/solov2-light_r50-dcn_fpn_ms-3x_coco.py | _base_ = './solov2-light_r50_fpn_ms-3x_coco.py'
# model settings
model = dict(
backbone=dict(
dcn=dict(type='DCNv2', deformable_groups=1, fallback_on_stride=False),
stage_with_dcn=(False, True, True, True)),
mask_head=dict(
feat_channels=256,
stacked_convs=3,
scale_range... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/solov2/solov2_r50_fpn_ms-3x_coco.py | configs/solov2/solov2_r50_fpn_ms-3x_coco.py | _base_ = './solov2_r50_fpn_1x_coco.py'
train_pipeline = [
dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}),
dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
dict(
type='RandomChoiceResize',
scales=[(1333, 800), (1333, 768), (1333, 736), (1333, 704),
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/solov2/solov2-light_r50_fpn_ms-3x_coco.py | configs/solov2/solov2-light_r50_fpn_ms-3x_coco.py | _base_ = './solov2_r50_fpn_1x_coco.py'
# model settings
model = dict(
mask_head=dict(
stacked_convs=2,
feat_channels=256,
scale_ranges=((1, 56), (28, 112), (56, 224), (112, 448), (224, 896)),
mask_feature_head=dict(out_channels=128)))
# dataset settings
train_pipeline = [
dict(... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gn+ws/mask-rcnn_r50_fpn_gn-ws-all_20-23-24e_coco.py | configs/gn+ws/mask-rcnn_r50_fpn_gn-ws-all_20-23-24e_coco.py | _base_ = './mask-rcnn_r50_fpn_gn-ws-all_2x_coco.py'
# learning policy
max_epochs = 24
train_cfg = dict(max_epochs=max_epochs)
# learning rate
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
begin=0,
end=... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gn+ws/faster-rcnn_x101-32x4d_fpn_gn-ws-all_1x_coco.py | configs/gn+ws/faster-rcnn_x101-32x4d_fpn_gn-ws-all_1x_coco.py | _base_ = './faster-rcnn_r50_fpn_gn-ws-all_1x_coco.py'
conv_cfg = dict(type='ConvWS')
norm_cfg = dict(type='GN', num_groups=32, requires_grad=True)
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gn+ws/faster-rcnn_r101_fpn_gn-ws-all_1x_coco.py | configs/gn+ws/faster-rcnn_r101_fpn_gn-ws-all_1x_coco.py | _base_ = './faster-rcnn_r50_fpn_gn-ws-all_1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(
type='Pretrained', checkpoint='open-mmlab://jhu/resnet101_gn_ws')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gn+ws/mask-rcnn_r101_fpn_gn-ws-all_2x_coco.py | configs/gn+ws/mask-rcnn_r101_fpn_gn-ws-all_2x_coco.py | _base_ = './mask-rcnn_r50_fpn_gn-ws-all_2x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(
type='Pretrained', checkpoint='open-mmlab://jhu/resnet101_gn_ws')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gn+ws/mask-rcnn_r50_fpn_gn-ws-all_2x_coco.py | configs/gn+ws/mask-rcnn_r50_fpn_gn-ws-all_2x_coco.py | _base_ = '../mask_rcnn/mask-rcnn_r50_fpn_1x_coco.py'
conv_cfg = dict(type='ConvWS')
norm_cfg = dict(type='GN', num_groups=32, requires_grad=True)
model = dict(
backbone=dict(
conv_cfg=conv_cfg,
norm_cfg=norm_cfg,
init_cfg=dict(
type='Pretrained', checkpoint='open-mmlab://jhu/resn... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gn+ws/mask-rcnn_x50-32x4d_fpn_gn-ws-all_2x_coco.py | configs/gn+ws/mask-rcnn_x50-32x4d_fpn_gn-ws-all_2x_coco.py | _base_ = './mask-rcnn_r50_fpn_gn-ws-all_2x_coco.py'
# model settings
conv_cfg = dict(type='ConvWS')
norm_cfg = dict(type='GN', num_groups=32, requires_grad=True)
model = dict(
backbone=dict(
type='ResNeXt',
depth=50,
groups=32,
base_width=4,
num_stages=4,
out_indices=... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gn+ws/mask-rcnn_x101-32x4d_fpn_gn-ws-all_2x_coco.py | configs/gn+ws/mask-rcnn_x101-32x4d_fpn_gn-ws-all_2x_coco.py | _base_ = './mask-rcnn_r50_fpn_gn-ws-all_2x_coco.py'
# model settings
conv_cfg = dict(type='ConvWS')
norm_cfg = dict(type='GN', num_groups=32, requires_grad=True)
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
base_width=4,
num_stages=4,
out_indices... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gn+ws/mask-rcnn_x50-32x4d_fpn_gn-ws-all_20-23-24e_coco.py | configs/gn+ws/mask-rcnn_x50-32x4d_fpn_gn-ws-all_20-23-24e_coco.py | _base_ = './mask-rcnn_x50-32x4d_fpn_gn-ws-all_2x_coco.py'
# learning policy
max_epochs = 24
train_cfg = dict(max_epochs=max_epochs)
# learning rate
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
begin=0,
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gn+ws/faster-rcnn_r50_fpn_gn-ws-all_1x_coco.py | configs/gn+ws/faster-rcnn_r50_fpn_gn-ws-all_1x_coco.py | _base_ = '../faster_rcnn/faster-rcnn_r50_fpn_1x_coco.py'
conv_cfg = dict(type='ConvWS')
norm_cfg = dict(type='GN', num_groups=32, requires_grad=True)
model = dict(
backbone=dict(
conv_cfg=conv_cfg,
norm_cfg=norm_cfg,
init_cfg=dict(
type='Pretrained', checkpoint='open-mmlab://jhu/... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gn+ws/mask-rcnn_r101_fpn_gn-ws-all_20-23-24e_coco.py | configs/gn+ws/mask-rcnn_r101_fpn_gn-ws-all_20-23-24e_coco.py | _base_ = './mask-rcnn_r101_fpn_gn-ws-all_2x_coco.py'
# learning policy
max_epochs = 24
train_cfg = dict(max_epochs=max_epochs)
# learning rate
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
begin=0,
end... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gn+ws/mask-rcnn_x101-32x4d_fpn_gn-ws-all_20-23-24e_coco.py | configs/gn+ws/mask-rcnn_x101-32x4d_fpn_gn-ws-all_20-23-24e_coco.py | _base_ = './mask-rcnn_x101-32x4d_fpn_gn-ws-all_2x_coco.py'
# learning policy
max_epochs = 24
train_cfg = dict(max_epochs=max_epochs)
# learning rate
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
begin=0,
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gn+ws/faster-rcnn_x50-32x4d_fpn_gn-ws-all_1x_coco.py | configs/gn+ws/faster-rcnn_x50-32x4d_fpn_gn-ws-all_1x_coco.py | _base_ = './faster-rcnn_r50_fpn_gn-ws-all_1x_coco.py'
conv_cfg = dict(type='ConvWS')
norm_cfg = dict(type='GN', num_groups=32, requires_grad=True)
model = dict(
backbone=dict(
type='ResNeXt',
depth=50,
groups=32,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/paa/paa_r101_fpn_ms-3x_coco.py | configs/paa/paa_r101_fpn_ms-3x_coco.py | _base_ = './paa_r50_fpn_ms-3x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/paa/paa_r50_fpn_ms-3x_coco.py | configs/paa/paa_r50_fpn_ms-3x_coco.py | _base_ = './paa_r50_fpn_1x_coco.py'
max_epochs = 36
# learning rate
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
begin=0,
end=max_epochs,
by_epoch=True,
milestones=[28, 34],
ga... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/paa/paa_r101_fpn_2x_coco.py | configs/paa/paa_r101_fpn_2x_coco.py | _base_ = './paa_r101_fpn_1x_coco.py'
max_epochs = 24
# learning rate
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
begin=0,
end=max_epochs,
by_epoch=True,
milestones=[16, 22],
g... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/paa/paa_r101_fpn_1x_coco.py | configs/paa/paa_r101_fpn_1x_coco.py | _base_ = './paa_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/paa/paa_r50_fpn_1x_coco.py | configs/paa/paa_r50_fpn_1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# model settings
model = dict(
type='PAA',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/paa/paa_r50_fpn_2x_coco.py | configs/paa/paa_r50_fpn_2x_coco.py | _base_ = './paa_r50_fpn_1x_coco.py'
max_epochs = 24
# learning rate
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
begin=0,
end=max_epochs,
by_epoch=True,
milestones=[16, 22],
ga... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/paa/paa_r50_fpn_1.5x_coco.py | configs/paa/paa_r50_fpn_1.5x_coco.py | _base_ = './paa_r50_fpn_1x_coco.py'
max_epochs = 18
# learning rate
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
begin=0,
end=max_epochs,
by_epoch=True,
milestones=[12, 16],
ga... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask2former/mask2former_swin-l-p4-w12-384-in21k_16xb1-lsj-100e_coco-panoptic.py | configs/mask2former/mask2former_swin-l-p4-w12-384-in21k_16xb1-lsj-100e_coco-panoptic.py | _base_ = ['./mask2former_swin-b-p4-w12-384_8xb2-lsj-50e_coco-panoptic.py']
pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_large_patch4_window12_384_22k.pth' # noqa
model = dict(
backbone=dict(
embed_dims=192,
num_heads=[6, 12, 24, 48],
init_cfg=dict(... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask2former/mask2former_swin-b-p4-w12-384-in21k_8xb2-lsj-50e_coco-panoptic.py | configs/mask2former/mask2former_swin-b-p4-w12-384-in21k_8xb2-lsj-50e_coco-panoptic.py | _base_ = ['./mask2former_swin-b-p4-w12-384_8xb2-lsj-50e_coco-panoptic.py']
pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_base_patch4_window12_384_22k.pth' # noqa
model = dict(
backbone=dict(init_cfg=dict(type='Pretrained', checkpoint=pretrained)))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask2former/mask2former_swin-t-p4-w7-224_8xb2-lsj-50e_coco.py | configs/mask2former/mask2former_swin-t-p4-w7-224_8xb2-lsj-50e_coco.py | _base_ = ['./mask2former_r50_8xb2-lsj-50e_coco.py']
pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_tiny_patch4_window7_224.pth' # noqa
depths = [2, 2, 6, 2]
model = dict(
type='Mask2Former',
backbone=dict(
_delete_=True,
type='SwinTransformer',
em... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask2former/mask2former_swin-t-p4-w7-224_8xb2-lsj-50e_coco-panoptic.py | configs/mask2former/mask2former_swin-t-p4-w7-224_8xb2-lsj-50e_coco-panoptic.py | _base_ = ['./mask2former_r50_8xb2-lsj-50e_coco-panoptic.py']
pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_tiny_patch4_window7_224.pth' # noqa
depths = [2, 2, 6, 2]
model = dict(
type='Mask2Former',
backbone=dict(
_delete_=True,
type='SwinTransformer',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask2former/mask2former_r101_8xb2-lsj-50e_coco.py | configs/mask2former/mask2former_r101_8xb2-lsj-50e_coco.py | _base_ = ['./mask2former_r50_8xb2-lsj-50e_coco.py']
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask2former/mask2former_r50_8xb2-lsj-50e_coco-panoptic.py | configs/mask2former/mask2former_r50_8xb2-lsj-50e_coco-panoptic.py | _base_ = [
'../_base_/datasets/coco_panoptic.py', '../_base_/default_runtime.py'
]
image_size = (1024, 1024)
batch_augments = [
dict(
type='BatchFixedSizePad',
size=image_size,
img_pad_value=0,
pad_mask=True,
mask_pad_value=0,
pad_seg=True,
seg_pad_value=2... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask2former/mask2former_swin-s-p4-w7-224_8xb2-lsj-50e_coco.py | configs/mask2former/mask2former_swin-s-p4-w7-224_8xb2-lsj-50e_coco.py | _base_ = ['./mask2former_swin-t-p4-w7-224_8xb2-lsj-50e_coco.py']
pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_small_patch4_window7_224.pth' # noqa
depths = [2, 2, 18, 2]
model = dict(
backbone=dict(
depths=depths, init_cfg=dict(type='Pretrained',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask2former/mask2former_r50_8xb2-lsj-50e_coco.py | configs/mask2former/mask2former_r50_8xb2-lsj-50e_coco.py | _base_ = ['./mask2former_r50_8xb2-lsj-50e_coco-panoptic.py']
num_things_classes = 80
num_stuff_classes = 0
num_classes = num_things_classes + num_stuff_classes
image_size = (1024, 1024)
batch_augments = [
dict(
type='BatchFixedSizePad',
size=image_size,
img_pad_value=0,
pad_mask=Tru... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask2former/mask2former_swin-b-p4-w12-384_8xb2-lsj-50e_coco-panoptic.py | configs/mask2former/mask2former_swin-b-p4-w12-384_8xb2-lsj-50e_coco-panoptic.py | _base_ = ['./mask2former_swin-t-p4-w7-224_8xb2-lsj-50e_coco-panoptic.py']
pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_base_patch4_window12_384.pth' # noqa
depths = [2, 2, 18, 2]
model = dict(
backbone=dict(
pretrain_img_size=384,
embed_dims=128,
d... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask2former/mask2former_swin-s-p4-w7-224_8xb2-lsj-50e_coco-panoptic.py | configs/mask2former/mask2former_swin-s-p4-w7-224_8xb2-lsj-50e_coco-panoptic.py | _base_ = ['./mask2former_swin-t-p4-w7-224_8xb2-lsj-50e_coco-panoptic.py']
pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_small_patch4_window7_224.pth' # noqa
depths = [2, 2, 18, 2]
model = dict(
backbone=dict(
depths=depths, init_cfg=dict(type='Pretrained',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask2former/mask2former_r101_8xb2-lsj-50e_coco-panoptic.py | configs/mask2former/mask2former_r101_8xb2-lsj-50e_coco-panoptic.py | _base_ = './mask2former_r50_8xb2-lsj-50e_coco-panoptic.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/yolox/yolox_nano_8xb8-300e_coco.py | configs/yolox/yolox_nano_8xb8-300e_coco.py | _base_ = './yolox_tiny_8xb8-300e_coco.py'
# model settings
model = dict(
backbone=dict(deepen_factor=0.33, widen_factor=0.25, use_depthwise=True),
neck=dict(
in_channels=[64, 128, 256],
out_channels=64,
num_csp_blocks=1,
use_depthwise=True),
bbox_head=dict(in_channels=64, fe... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/yolox/yolox_tta.py | configs/yolox/yolox_tta.py | tta_model = dict(
type='DetTTAModel',
tta_cfg=dict(nms=dict(type='nms', iou_threshold=0.65), max_per_img=100))
img_scales = [(640, 640), (320, 320), (960, 960)]
tta_pipeline = [
dict(type='LoadImageFromFile', backend_args=None),
dict(
type='TestTimeAug',
transforms=[
[
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/yolox/yolox_x_8xb8-300e_coco.py | configs/yolox/yolox_x_8xb8-300e_coco.py | _base_ = './yolox_s_8xb8-300e_coco.py'
# model settings
model = dict(
backbone=dict(deepen_factor=1.33, widen_factor=1.25),
neck=dict(
in_channels=[320, 640, 1280], out_channels=320, num_csp_blocks=4),
bbox_head=dict(in_channels=320, feat_channels=320))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/yolox/yolox_m_8xb8-300e_coco.py | configs/yolox/yolox_m_8xb8-300e_coco.py | _base_ = './yolox_s_8xb8-300e_coco.py'
# model settings
model = dict(
backbone=dict(deepen_factor=0.67, widen_factor=0.75),
neck=dict(in_channels=[192, 384, 768], out_channels=192, num_csp_blocks=2),
bbox_head=dict(in_channels=192, feat_channels=192),
)
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/yolox/yolox_l_8xb8-300e_coco.py | configs/yolox/yolox_l_8xb8-300e_coco.py | _base_ = './yolox_s_8xb8-300e_coco.py'
# model settings
model = dict(
backbone=dict(deepen_factor=1.0, widen_factor=1.0),
neck=dict(
in_channels=[256, 512, 1024], out_channels=256, num_csp_blocks=3),
bbox_head=dict(in_channels=256, feat_channels=256))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/yolox/yolox_tiny_8xb8-300e_coco.py | configs/yolox/yolox_tiny_8xb8-300e_coco.py | _base_ = './yolox_s_8xb8-300e_coco.py'
# model settings
model = dict(
data_preprocessor=dict(batch_augments=[
dict(
type='BatchSyncRandomResize',
random_size_range=(320, 640),
size_divisor=32,
interval=10)
]),
backbone=dict(deepen_factor=0.33, widen_f... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/yolox/yolox_s_8xb8-300e_coco.py | configs/yolox/yolox_s_8xb8-300e_coco.py | _base_ = [
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py',
'./yolox_tta.py'
]
img_scale = (640, 640) # width, height
# model settings
model = dict(
type='YOLOX',
data_preprocessor=dict(
type='DetDataPreprocessor',
pad_size_divisor=32,
batch_augments=[
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r50-caffe-c4_1x_coco.py | 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'
]
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r50-caffe_fpn_1x_coco.py | configs/mask_rcnn/mask-rcnn_r50-caffe_fpn_1x_coco.py | _base_ = './mask-rcnn_r50_fpn_1x_coco.py'
model = dict(
# use caffe img_norm
data_preprocessor=dict(
mean=[103.530, 116.280, 123.675],
std=[1.0, 1.0, 1.0],
bgr_to_rgb=False),
backbone=dict(
norm_cfg=dict(requires_grad=False),
style='caffe',
init_cfg=dict(
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r50-caffe_fpn_ms-poly-1x_coco.py | configs/mask_rcnn/mask-rcnn_r50-caffe_fpn_ms-poly-1x_coco.py | _base_ = './mask-rcnn_r50_fpn_1x_coco.py'
model = dict(
# use caffe img_norm
data_preprocessor=dict(
mean=[103.530, 116.280, 123.675],
std=[1.0, 1.0, 1.0],
bgr_to_rgb=False),
backbone=dict(
norm_cfg=dict(requires_grad=False),
style='caffe',
init_cfg=dict(
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r101-caffe_fpn_1x_coco.py | configs/mask_rcnn/mask-rcnn_r101-caffe_fpn_1x_coco.py | _base_ = './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')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r50_fpn_2x_coco.py | 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'
]
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r50_fpn_ms-poly-3x_coco.py | configs/mask_rcnn/mask-rcnn_r50_fpn_ms-poly-3x_coco.py | _base_ = [
'../common/ms-poly_3x_coco-instance.py',
'../_base_/models/mask-rcnn_r50_fpn.py'
]
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_x101-32x8d_fpn_1x_coco.py | configs/mask_rcnn/mask-rcnn_x101-32x8d_fpn_1x_coco.py | _base_ = './mask-rcnn_r101_fpn_1x_coco.py'
model = dict(
# ResNeXt-101-32x8d model trained with Caffe2 at FB,
# so the mean and std need to be changed.
data_preprocessor=dict(
mean=[103.530, 116.280, 123.675],
std=[57.375, 57.120, 58.395],
bgr_to_rgb=False),
backbone=dict(
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r101-caffe_fpn_ms-poly-3x_coco.py | configs/mask_rcnn/mask-rcnn_r101-caffe_fpn_ms-poly-3x_coco.py | _base_ = [
'../common/ms-poly_3x_coco-instance.py',
'../_base_/models/mask-rcnn_r50_fpn.py'
]
model = dict(
# use caffe img_norm
data_preprocessor=dict(
mean=[103.530, 116.280, 123.675],
std=[1.0, 1.0, 1.0],
bgr_to_rgb=False),
backbone=dict(
depth=101,
norm_c... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r101_fpn_2x_coco.py | configs/mask_rcnn/mask-rcnn_r101_fpn_2x_coco.py | _base_ = './mask-rcnn_r50_fpn_2x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_x101-32x8d_fpn_ms-poly-1x_coco.py | configs/mask_rcnn/mask-rcnn_x101-32x8d_fpn_ms-poly-1x_coco.py | _base_ = './mask-rcnn_r101_fpn_1x_coco.py'
model = dict(
# ResNeXt-101-32x8d model trained with Caffe2 at FB,
# so the mean and std need to be changed.
data_preprocessor=dict(
mean=[103.530, 116.280, 123.675],
std=[57.375, 57.120, 58.395],
bgr_to_rgb=False),
backbone=dict(
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r50_fpn_1x_coco.py | configs/mask_rcnn/mask-rcnn_r50_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'
]
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r50-caffe_fpn_ms-poly-2x_coco.py | configs/mask_rcnn/mask-rcnn_r50-caffe_fpn_ms-poly-2x_coco.py | _base_ = './mask-rcnn_r50-caffe_fpn_ms-poly-1x_coco.py'
train_cfg = dict(max_epochs=24)
# learning rate
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
begin=0,
end=24,
by_epoch=True,
mil... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r50_fpn_amp-1x_coco.py | configs/mask_rcnn/mask-rcnn_r50_fpn_amp-1x_coco.py | _base_ = './mask-rcnn_r50_fpn_1x_coco.py'
# Enable automatic-mixed-precision training with AmpOptimWrapper.
optim_wrapper = dict(type='AmpOptimWrapper')
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r18_fpn_8xb8-amp-lsj-200e_coco.py | configs/mask_rcnn/mask-rcnn_r18_fpn_8xb8-amp-lsj-200e_coco.py | _base_ = './mask-rcnn_r50_fpn_8xb8-amp-lsj-200e_coco.py'
model = dict(
backbone=dict(
depth=18,
init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet18')),
neck=dict(in_channels=[64, 128, 256, 512]))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r101_fpn_8xb8-amp-lsj-200e_coco.py | configs/mask_rcnn/mask-rcnn_r101_fpn_8xb8-amp-lsj-200e_coco.py | _base_ = './mask-rcnn_r50_fpn_8xb8-amp-lsj-200e_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r101_fpn_ms-poly-3x_coco.py | configs/mask_rcnn/mask-rcnn_r101_fpn_ms-poly-3x_coco.py | _base_ = [
'../common/ms-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')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_x101-32x4d_fpn_2x_coco.py | configs/mask_rcnn/mask-rcnn_x101-32x4d_fpn_2x_coco.py | _base_ = './mask-rcnn_r101_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',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r50-caffe_fpn_poly-1x_coco_v1.py | configs/mask_rcnn/mask-rcnn_r50-caffe_fpn_poly-1x_coco_v1.py | _base_ = './mask-rcnn_r50_fpn_1x_coco.py'
model = dict(
# use caffe img_norm
data_preprocessor=dict(
mean=[103.530, 116.280, 123.675],
std=[1.0, 1.0, 1.0],
bgr_to_rgb=False),
backbone=dict(
norm_cfg=dict(requires_grad=False),
style='caffe',
init_cfg=dict(
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r50-caffe_fpn_ms-1x_coco.py | configs/mask_rcnn/mask-rcnn_r50-caffe_fpn_ms-1x_coco.py | _base_ = './mask-rcnn_r50_fpn_1x_coco.py'
model = dict(
# use caffe img_norm
data_preprocessor=dict(
mean=[103.530, 116.280, 123.675],
std=[1.0, 1.0, 1.0],
bgr_to_rgb=False),
backbone=dict(
norm_cfg=dict(requires_grad=False),
style='caffe',
init_cfg=dict(
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_x101-32x4d_fpn_1x_coco.py | 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',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r101_fpn_1x_coco.py | configs/mask_rcnn/mask-rcnn_r101_fpn_1x_coco.py | _base_ = './mask-rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r50-caffe_fpn_ms-poly-3x_coco.py | configs/mask_rcnn/mask-rcnn_r50-caffe_fpn_ms-poly-3x_coco.py | _base_ = './mask-rcnn_r50-caffe_fpn_ms-poly-1x_coco.py'
train_cfg = dict(max_epochs=36)
# learning rate
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
begin=0,
end=24,
by_epoch=True,
mil... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r50_fpn_8xb8-amp-lsj-200e_coco.py | configs/mask_rcnn/mask-rcnn_r50_fpn_8xb8-amp-lsj-200e_coco.py | _base_ = [
'../_base_/models/mask-rcnn_r50_fpn.py',
'../common/lsj-100e_coco-instance.py'
]
image_size = (1024, 1024)
batch_augments = [
dict(type='BatchFixedSizePad', size=image_size, pad_mask=True)
]
model = dict(data_preprocessor=dict(batch_augments=batch_augments))
train_dataloader = dict(batch_size=8... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_x101-64x4d_fpn_1x_coco.py | 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... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r50_fpn_1x-wandb_coco.py | configs/mask_rcnn/mask-rcnn_r50_fpn_1x-wandb_coco.py | _base_ = [
'../_base_/models/mask-rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
vis_backends = [dict(type='LocalVisBackend'), dict(type='WandbVisBackend')]
visualizer = dict(vis_backends=vis_backends)
# MMEngine support the ... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_x101-64x4d_fpn_ms-poly_3x_coco.py | configs/mask_rcnn/mask-rcnn_x101-64x4d_fpn_ms-poly_3x_coco.py | _base_ = [
'../common/ms-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_cfg=di... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_x101-32x4d_fpn_ms-poly-3x_coco.py | configs/mask_rcnn/mask-rcnn_x101-32x4d_fpn_ms-poly-3x_coco.py | _base_ = [
'../common/ms-poly_3x_coco-instance.py',
'../_base_/models/mask-rcnn_r50_fpn.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=di... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_x101-64x4d_fpn_2x_coco.py | configs/mask_rcnn/mask-rcnn_x101-64x4d_fpn_2x_coco.py | _base_ = './mask-rcnn_x101-32x4d_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='pyto... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_r50_fpn_poly-1x_coco.py | configs/mask_rcnn/mask-rcnn_r50_fpn_poly-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'
]
train_pipeline = [
dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}),
dict(
type='LoadAnnotations',
wi... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mask_rcnn/mask-rcnn_x101-32x8d_fpn_ms-poly-3x_coco.py | configs/mask_rcnn/mask-rcnn_x101-32x8d_fpn_ms-poly-3x_coco.py | _base_ = [
'../common/ms-poly_3x_coco-instance.py',
'../_base_/models/mask-rcnn_r50_fpn.py'
]
model = dict(
# ResNeXt-101-32x8d model trained with Caffe2 at FB,
# so the mean and std need to be changed.
data_preprocessor=dict(
mean=[103.530, 116.280, 123.675],
std=[57.375, 57.120, 5... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/dynamic_rcnn/dynamic-rcnn_r50_fpn_1x_coco.py | configs/dynamic_rcnn/dynamic-rcnn_r50_fpn_1x_coco.py | _base_ = '../faster_rcnn/faster-rcnn_r50_fpn_1x_coco.py'
model = dict(
roi_head=dict(
type='DynamicRoIHead',
bbox_head=dict(
type='Shared2FCBBoxHead',
in_channels=256,
fc_out_channels=1024,
roi_feat_size=7,
num_classes=80,
bbox_... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/foveabox/fovea_r50_fpn_4xb4-2x_coco.py | configs/foveabox/fovea_r50_fpn_4xb4-2x_coco.py | _base_ = './fovea_r50_fpn_4xb4-1x_coco.py'
# learning policy
max_epochs = 24
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
begin=0,
end=max_epochs,
by_epoch=True,
milestones=[16, 22],
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/foveabox/fovea_r101_fpn_4xb4-1x_coco.py | configs/foveabox/fovea_r101_fpn_4xb4-1x_coco.py | _base_ = './fovea_r50_fpn_4xb4-1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/foveabox/fovea_r101_fpn_4xb4-2x_coco.py | configs/foveabox/fovea_r101_fpn_4xb4-2x_coco.py | _base_ = './fovea_r50_fpn_4xb4-2x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/foveabox/fovea_r50_fpn_gn-head-align_4xb4-2x_coco.py | configs/foveabox/fovea_r50_fpn_gn-head-align_4xb4-2x_coco.py | _base_ = './fovea_r50_fpn_4xb4-1x_coco.py'
model = dict(
bbox_head=dict(
with_deform=True,
norm_cfg=dict(type='GN', num_groups=32, requires_grad=True)))
# learning policy
max_epochs = 24
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/foveabox/fovea_r101_fpn_gn-head-align_ms-640-800-4xb4-2x_coco.py | configs/foveabox/fovea_r101_fpn_gn-head-align_ms-640-800-4xb4-2x_coco.py | _base_ = './fovea_r50_fpn_4xb4-1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')),
bbox_head=dict(
with_deform=True,
norm_cfg=dict(type='GN', num_groups=32, requires_grad=True)))
train_... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/foveabox/fovea_r50_fpn_gn-head-align_ms-640-800-4xb4-2x_coco.py | configs/foveabox/fovea_r50_fpn_gn-head-align_ms-640-800-4xb4-2x_coco.py | _base_ = './fovea_r50_fpn_4xb4-1x_coco.py'
model = dict(
bbox_head=dict(
with_deform=True,
norm_cfg=dict(type='GN', num_groups=32, requires_grad=True)))
train_pipeline = [
dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}),
dict(type='LoadAnnotations', with_bbox=True),
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/foveabox/fovea_r50_fpn_4xb4-1x_coco.py | configs/foveabox/fovea_r50_fpn_4xb4-1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# model settings
model = dict(
type='FOVEA',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/foveabox/fovea_r101_fpn_gn-head-align_4xb4-2x_coco.py | configs/foveabox/fovea_r101_fpn_gn-head-align_4xb4-2x_coco.py | _base_ = './fovea_r50_fpn_4xb4-1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')),
bbox_head=dict(
with_deform=True,
norm_cfg=dict(type='GN', num_groups=32, requires_grad=True)))
# lear... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/grid_rcnn/grid-rcnn_r101_fpn_gn-head_2x_coco.py | configs/grid_rcnn/grid-rcnn_r101_fpn_gn-head_2x_coco.py | _base_ = './grid-rcnn_r50_fpn_gn-head_2x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/grid_rcnn/grid-rcnn_x101-32x4d_fpn_gn-head_2x_coco.py | 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(
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',
init_cfg=dict(
type='Pretra... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/grid_rcnn/grid-rcnn_r50_fpn_gn-head_1x_coco.py | configs/grid_rcnn/grid-rcnn_r50_fpn_gn-head_1x_coco.py | _base_ = './grid-rcnn_r50_fpn_gn-head_2x_coco.py'
# training schedule
max_epochs = 12
train_cfg = dict(max_epochs=max_epochs)
# learning rate
param_scheduler = [
dict(
type='LinearLR', start_factor=0.0001, by_epoch=False, begin=0,
end=500),
dict(
type='MultiStepLR',
begin=0,
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/grid_rcnn/grid-rcnn_r50_fpn_gn-head_2x_coco.py | 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',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
bgr_to_rgb=True,
pad_si... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/grid_rcnn/grid-rcnn_x101-64x4d_fpn_gn-head_2x_coco.py | 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(
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
style='pytorch',
init_cfg=dict(
type=... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/retinanet/retinanet_r101_fpn_1x_coco.py | configs/retinanet/retinanet_r101_fpn_1x_coco.py | _base_ = './retinanet_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/retinanet/retinanet_tta.py | configs/retinanet/retinanet_tta.py | tta_model = dict(
type='DetTTAModel',
tta_cfg=dict(nms=dict(type='nms', iou_threshold=0.5), max_per_img=100))
img_scales = [(1333, 800), (666, 400), (2000, 1200)]
tta_pipeline = [
dict(type='LoadImageFromFile', backend_args=None),
dict(
type='TestTimeAug',
transforms=[[
dict... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/retinanet/retinanet_r18_fpn_8xb8-amp-lsj-200e_coco.py | configs/retinanet/retinanet_r18_fpn_8xb8-amp-lsj-200e_coco.py | _base_ = './retinanet_r50_fpn_8xb8-amp-lsj-200e_coco.py'
model = dict(
backbone=dict(
depth=18,
init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet18')),
neck=dict(in_channels=[64, 128, 256, 512]))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
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