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/pascal_voc/faster-rcnn_r50_fpn_1x_voc0712-cocofmt.py | configs/pascal_voc/faster-rcnn_r50_fpn_1x_voc0712-cocofmt.py | _base_ = [
'../_base_/models/faster-rcnn_r50_fpn.py', '../_base_/datasets/voc0712.py',
'../_base_/default_runtime.py'
]
model = dict(roi_head=dict(bbox_head=dict(num_classes=20)))
METAINFO = {
'classes':
('aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat',
'chair', 'cow', 'dinin... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/pascal_voc/faster-rcnn_r50-caffe-c4_ms-18k_voc0712.py | configs/pascal_voc/faster-rcnn_r50-caffe-c4_ms-18k_voc0712.py | _base_ = [
'../_base_/models/faster-rcnn_r50-caffe-c4.py',
'../_base_/schedules/schedule_1x.py', '../_base_/datasets/voc0712.py',
'../_base_/default_runtime.py'
]
model = dict(roi_head=dict(bbox_head=dict(num_classes=20)))
# dataset settings
train_pipeline = [
dict(type='LoadImageFromFile', backend_arg... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/pascal_voc/faster-rcnn_r50_fpn_1x_voc0712.py | configs/pascal_voc/faster-rcnn_r50_fpn_1x_voc0712.py | _base_ = [
'../_base_/models/faster-rcnn_r50_fpn.py', '../_base_/datasets/voc0712.py',
'../_base_/default_runtime.py'
]
model = dict(roi_head=dict(bbox_head=dict(num_classes=20)))
# training schedule, voc dataset is repeated 3 times, in
# `_base_/datasets/voc0712.py`, so the actual epoch = 4 * 3 = 12
max_epoch... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/pascal_voc/ssd300_voc0712.py | configs/pascal_voc/ssd300_voc0712.py | _base_ = [
'../_base_/models/ssd300.py', '../_base_/datasets/voc0712.py',
'../_base_/schedules/schedule_2x.py', '../_base_/default_runtime.py'
]
model = dict(
bbox_head=dict(
num_classes=20, anchor_generator=dict(basesize_ratio_range=(0.2,
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/pascal_voc/retinanet_r50_fpn_1x_voc0712.py | configs/pascal_voc/retinanet_r50_fpn_1x_voc0712.py | _base_ = [
'../_base_/models/retinanet_r50_fpn.py', '../_base_/datasets/voc0712.py',
'../_base_/default_runtime.py'
]
model = dict(bbox_head=dict(num_classes=20))
# training schedule, voc dataset is repeated 3 times, in
# `_base_/datasets/voc0712.py`, so the actual epoch = 4 * 3 = 12
max_epochs = 4
train_cfg =... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/htc/htc-without-semantic_r50_fpn_1x_coco.py | configs/htc/htc-without-semantic_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='HybridTaskCascade',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/htc/htc_r50_fpn_1x_coco.py | configs/htc/htc_r50_fpn_1x_coco.py | _base_ = './htc-without-semantic_r50_fpn_1x_coco.py'
model = dict(
data_preprocessor=dict(pad_seg=True),
roi_head=dict(
semantic_roi_extractor=dict(
type='SingleRoIExtractor',
roi_layer=dict(type='RoIAlign', output_size=14, sampling_ratio=0),
out_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/htc/htc_x101-32x4d_fpn_16xb1-20e_coco.py | configs/htc/htc_x101-32x4d_fpn_16xb1-20e_coco.py | _base_ = './htc_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=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/htc/htc_x101-64x4d_fpn_16xb1-20e_coco.py | configs/htc/htc_x101-64x4d_fpn_16xb1-20e_coco.py | _base_ = './htc_x101-32x4d_fpn_16xb1-20e_coco.py'
model = dict(
backbone=dict(
type='ResNeXt',
groups=64,
init_cfg=dict(
type='Pretrained', checkpoint='open-mmlab://resnext101_64x4d')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/htc/htc_r101_fpn_20e_coco.py | configs/htc/htc_r101_fpn_20e_coco.py | _base_ = './htc_r50_fpn_20e_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/htc/htc_x101-64x4d-dconv-c3-c5_fpn_ms-400-1400-16xb1-20e_coco.py | configs/htc/htc_x101-64x4d-dconv-c3-c5_fpn_ms-400-1400-16xb1-20e_coco.py | _base_ = './htc_x101-64x4d_fpn_16xb1-20e_coco.py'
model = dict(
backbone=dict(
dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False),
stage_with_dcn=(False, True, True, True)))
# dataset settings
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='LoadAnnotatio... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/htc/htc_r50_fpn_20e_coco.py | configs/htc/htc_r50_fpn_20e_coco.py | _base_ = './htc_r50_fpn_1x_coco.py'
# learning policy
max_epochs = 20
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, 19],
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/dyhead/atss_r50_fpn_dyhead_1x_coco.py | configs/dyhead/atss_r50_fpn_dyhead_1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
type='ATSS',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
bgr_to_rgb... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/dyhead/atss_r50-caffe_fpn_dyhead_1x_coco.py | configs/dyhead/atss_r50-caffe_fpn_dyhead_1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
type='ATSS',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[103.530, 116.280, 123.675],
std=[1.0, 1.0, 1.0],
bgr_to_rgb=False... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/dyhead/atss_swin-l-p4-w12_fpn_dyhead_ms-2x_coco.py | configs/dyhead/atss_swin-l-p4-w12_fpn_dyhead_ms-2x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_large_patch4_window12_384_22k.pth' # noqa
model = dict(
type='ATSS',
data_preprocessor=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/atss/atss_r50_fpn_8xb8-amp-lsj-200e_coco.py | configs/atss/atss_r50_fpn_8xb8-amp-lsj-200e_coco.py | _base_ = '../common/lsj-200e_coco-detection.py'
image_size = (1024, 1024)
batch_augments = [dict(type='BatchFixedSizePad', size=image_size)]
model = dict(
type='ATSS',
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/atss/atss_r18_fpn_8xb8-amp-lsj-200e_coco.py | configs/atss/atss_r18_fpn_8xb8-amp-lsj-200e_coco.py | _base_ = './atss_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/atss/atss_r101_fpn_1x_coco.py | configs/atss/atss_r101_fpn_1x_coco.py | _base_ = './atss_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/atss/atss_r50_fpn_1x_coco.py | configs/atss/atss_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='ATSS',
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/atss/atss_r101_fpn_8xb8-amp-lsj-200e_coco.py | configs/atss/atss_r101_fpn_8xb8-amp-lsj-200e_coco.py | _base_ = './atss_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/resnet_strikes_back/retinanet_r50-rsb-pre_fpn_1x_coco.py | configs/resnet_strikes_back/retinanet_r50-rsb-pre_fpn_1x_coco.py | _base_ = [
'../_base_/models/retinanet_r50_fpn.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
checkpoint = 'https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb256-rsb-a1-600e_in1k_20211228-20e21305.pth' # noqa
model = ... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/resnet_strikes_back/mask-rcnn_r50-rsb-pre_fpn_1x_coco.py | configs/resnet_strikes_back/mask-rcnn_r50-rsb-pre_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'
]
checkpoint = 'https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb256-rsb-a1-600e_in1k_20211228-20e21305.pth' # noqa
model = 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/resnet_strikes_back/faster-rcnn_r50-rsb-pre_fpn_1x_coco.py | configs/resnet_strikes_back/faster-rcnn_r50-rsb-pre_fpn_1x_coco.py | _base_ = [
'../_base_/models/faster-rcnn_r50_fpn.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
checkpoint = 'https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb256-rsb-a1-600e_in1k_20211228-20e21305.pth' # noqa
model ... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/resnet_strikes_back/cascade-mask-rcnn_r50-rsb-pre_fpn_1x_coco.py | configs/resnet_strikes_back/cascade-mask-rcnn_r50-rsb-pre_fpn_1x_coco.py | _base_ = [
'../_base_/models/cascade-mask-rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
checkpoint = 'https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb256-rsb-a1-600e_in1k_20211228-20e21305.pth' # noqa
m... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/convnext/cascade-mask-rcnn_convnext-s-p4-w7_fpn_4conv1fc-giou_amp-ms-crop-3x_coco.py | configs/convnext/cascade-mask-rcnn_convnext-s-p4-w7_fpn_4conv1fc-giou_amp-ms-crop-3x_coco.py | _base_ = './cascade-mask-rcnn_convnext-t-p4-w7_fpn_4conv1fc-giou_amp-ms-crop-3x_coco.py' # noqa
# please install mmpretrain
# import mmpretrain.models to trigger register_module in mmpretrain
custom_imports = dict(
imports=['mmpretrain.models'], allow_failed_imports=False)
checkpoint_file = 'https://download.open... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/convnext/mask-rcnn_convnext-t-p4-w7_fpn_amp-ms-crop-3x_coco.py | configs/convnext/mask-rcnn_convnext-t-p4-w7_fpn_amp-ms-crop-3x_coco.py | _base_ = [
'../_base_/models/mask-rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# please install mmpretrain
# import mmpretrain.models to trigger register_module in mmpretrain
custom_imports = dict(
imports=['mmpretrain.m... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/convnext/cascade-mask-rcnn_convnext-t-p4-w7_fpn_4conv1fc-giou_amp-ms-crop-3x_coco.py | configs/convnext/cascade-mask-rcnn_convnext-t-p4-w7_fpn_4conv1fc-giou_amp-ms-crop-3x_coco.py | _base_ = [
'../_base_/models/cascade-mask-rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# please install mmpretrain
# import mmpretrain.models to trigger register_module in mmpretrain
custom_imports = dict(
imports=['mmpr... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/grounding_dino_swin-t_finetune_8xb4_20e_cat.py | configs/mm_grounding_dino/grounding_dino_swin-t_finetune_8xb4_20e_cat.py | _base_ = 'grounding_dino_swin-t_pretrain_obj365.py'
data_root = 'data/cat/'
class_name = ('cat', )
num_classes = len(class_name)
metainfo = dict(classes=class_name, palette=[(220, 20, 60)])
model = dict(bbox_head=dict(num_classes=num_classes))
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='Loa... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/grounding_dino_swin-t_pretrain_obj365.py | configs/mm_grounding_dino/grounding_dino_swin-t_pretrain_obj365.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_tiny_patch4_window7_224.pth' # noqa
lang_model_name = 'bert-base-uncased'
model = dict(
type='Gro... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/grounding_dino_swin-l_pretrain_obj365_goldg.py | configs/mm_grounding_dino/grounding_dino_swin-l_pretrain_obj365_goldg.py | _base_ = 'grounding_dino_swin-t_pretrain_obj365.py'
pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_large_patch4_window12_384_22k.pth' # noqa
num_levels = 5
model = dict(
use_autocast=True,
num_feature_levels=num_levels,
backbone=dict(
_delete_=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/mm_grounding_dino/grounding_dino_swin-t_pretrain_obj365_goldg.py | configs/mm_grounding_dino/grounding_dino_swin-t_pretrain_obj365_goldg.py | _base_ = 'grounding_dino_swin-t_pretrain_obj365.py'
o365v1_od_dataset = dict(
type='ODVGDataset',
data_root='data/objects365v1/',
ann_file='o365v1_train_odvg.json',
label_map_file='o365v1_label_map.json',
data_prefix=dict(img='train/'),
filter_cfg=dict(filter_empty_gt=False),
pipeline=_base... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/grounding_dino_swin-t_pretrain_pseudo-labeling_cat.py | configs/mm_grounding_dino/grounding_dino_swin-t_pretrain_pseudo-labeling_cat.py | _base_ = 'grounding_dino_swin-t_pretrain_obj365.py'
test_pipeline = [
dict(
type='LoadImageFromFile', backend_args=None,
imdecode_backend='pillow'),
dict(
type='FixScaleResize',
scale=(800, 1333),
keep_ratio=True,
backend='pillow'),
dict(type='LoadTextAnnotat... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/grounding_dino_swin-t_pretrain_obj365_goldg_grit9m_v3det.py | configs/mm_grounding_dino/grounding_dino_swin-t_pretrain_obj365_goldg_grit9m_v3det.py | _base_ = 'grounding_dino_swin-t_pretrain_obj365.py'
o365v1_od_dataset = dict(
type='ODVGDataset',
data_root='data/objects365v1/',
ann_file='o365v1_train_odvg.json',
label_map_file='o365v1_label_map.json',
data_prefix=dict(img='train/'),
filter_cfg=dict(filter_empty_gt=False),
pipeline=_base... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/grounding_dino_swin-b_pretrain_obj365_goldg_v3det.py | configs/mm_grounding_dino/grounding_dino_swin-b_pretrain_obj365_goldg_v3det.py | _base_ = 'grounding_dino_swin-t_pretrain_obj365.py'
pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_base_patch4_window12_384_22k.pth' # noqa
model = dict(
use_autocast=True,
backbone=dict(
_delete_=True,
type='SwinTransformer',
pretrain_img_size=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/mm_grounding_dino/grounding_dino_swin-t_pretrain_pseudo-labeling_flickr30k.py | configs/mm_grounding_dino/grounding_dino_swin-t_pretrain_pseudo-labeling_flickr30k.py | _base_ = 'grounding_dino_swin-t_pretrain_obj365.py'
test_pipeline = [
dict(
type='LoadImageFromFile', backend_args=None,
imdecode_backend='pillow'),
dict(
type='FixScaleResize',
scale=(800, 1333),
keep_ratio=True,
backend='pillow'),
dict(type='LoadTextAnnotat... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/grounding_dino_swin-t_pretrain_obj365_goldg_grit9m.py | configs/mm_grounding_dino/grounding_dino_swin-t_pretrain_obj365_goldg_grit9m.py | _base_ = 'grounding_dino_swin-t_pretrain_obj365.py'
o365v1_od_dataset = dict(
type='ODVGDataset',
data_root='data/objects365v1/',
ann_file='o365v1_train_odvg.json',
label_map_file='o365v1_label_map.json',
data_prefix=dict(img='train/'),
filter_cfg=dict(filter_empty_gt=False),
pipeline=_base... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/grounding_dino_swin-b_pretrain_all.py | configs/mm_grounding_dino/grounding_dino_swin-b_pretrain_all.py | _base_ = 'grounding_dino_swin-t_pretrain_obj365.py'
load_from = 'https://download.openmmlab.com/mmdetection/v3.0/mm_grounding_dino/grounding_dino_swin-b_pretrain_obj365_goldg_v3det/grounding_dino_swin-b_pretrain_obj365_goldg_v3de-f83eef00.pth' # noqa
model = dict(
use_autocast=True,
backbone=dict(
_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/mm_grounding_dino/grounding_dino_swin-l_pretrain_all.py | configs/mm_grounding_dino/grounding_dino_swin-l_pretrain_all.py | _base_ = 'grounding_dino_swin-t_pretrain_obj365.py'
load_from = 'https://download.openmmlab.com/mmdetection/v3.0/mm_grounding_dino/grounding_dino_swin-l_pretrain_obj365_goldg/grounding_dino_swin-l_pretrain_obj365_goldg-34dcdc53.pth' # noqa
num_levels = 5
model = dict(
use_autocast=True,
num_feature_levels=nu... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/grounding_dino_swin-t_pretrain_obj365_goldg_v3det.py | configs/mm_grounding_dino/grounding_dino_swin-t_pretrain_obj365_goldg_v3det.py | _base_ = 'grounding_dino_swin-t_pretrain_obj365.py'
o365v1_od_dataset = dict(
type='ODVGDataset',
data_root='data/objects365v1/',
ann_file='o365v1_train_odvg.json',
label_map_file='o365v1_label_map.json',
data_prefix=dict(img='train/'),
filter_cfg=dict(filter_empty_gt=False),
pipeline=_base... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/people_in_painting/grounding_dino_swin-t_finetune_8xb4_50e_people_in_painting.py | configs/mm_grounding_dino/people_in_painting/grounding_dino_swin-t_finetune_8xb4_50e_people_in_painting.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
# https://universe.roboflow.com/roboflow-100/people-in-paintings/dataset/2
data_root = 'data/people_in_painting_v2/'
class_name = ('Human', )
palette = [(220, 20, 60)]
metainfo = dict(classes=class_name, palette=palette)
train_pipeline = [
dict(type='LoadIma... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/brain_tumor/grounding_dino_swin-t_finetune_8xb4_50e_brain_tumor.py | configs/mm_grounding_dino/brain_tumor/grounding_dino_swin-t_finetune_8xb4_50e_brain_tumor.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
# https://universe.roboflow.com/roboflow-100/brain-tumor-m2pbp/dataset/2
data_root = 'data/brain_tumor_v2/'
class_name = ('label0', 'label1', 'label2')
label_name = '_annotations.coco.json'
palette = [(220, 20, 60), (255, 0, 0), (0, 0, 142)]
metainfo = dict(clas... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/odinw/grounding_dino_swin-t_pretrain_odinw13.py | configs/mm_grounding_dino/odinw/grounding_dino_swin-t_pretrain_odinw13.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py' # noqa
dataset_type = 'CocoDataset'
data_root = 'data/odinw/'
base_test_pipeline = _base_.test_pipeline
base_test_pipeline[-1]['meta_keys'] = ('img_id', 'img_path', 'ori_shape',
'img_shape', 'scale_factor', 'text',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/odinw/grounding_dino_swin-t_pretrain_odinw35.py | configs/mm_grounding_dino/odinw/grounding_dino_swin-t_pretrain_odinw35.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py' # noqa
dataset_type = 'CocoDataset'
data_root = 'data/odinw/'
base_test_pipeline = _base_.test_pipeline
base_test_pipeline[-1]['meta_keys'] = ('img_id', 'img_path', 'ori_shape',
'img_shape', 'scale_factor', 'text',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/odinw/override_category.py | configs/mm_grounding_dino/odinw/override_category.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import mmengine
def parse_args():
parser = argparse.ArgumentParser(description='Override Category')
parser.add_argument('data_root')
return parser.parse_args()
def main():
args = parse_args()
ChessPieces = [{
'id': 1,
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/lvis/grounding_dino_swin-t_finetune_16xb4_1x_lvis.py | configs/mm_grounding_dino/lvis/grounding_dino_swin-t_finetune_16xb4_1x_lvis.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
data_root = 'data/coco/'
model = dict(test_cfg=dict(
max_per_img=300,
chunked_size=40,
))
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='RandomFlip', prob=0.5),
dict(
ty... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/lvis/grounding_dino_swin-t_pretrain_zeroshot_lvis.py | configs/mm_grounding_dino/lvis/grounding_dino_swin-t_pretrain_zeroshot_lvis.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
model = dict(test_cfg=dict(
max_per_img=300,
chunked_size=40,
))
dataset_type = 'LVISV1Dataset'
data_root = 'data/coco/'
val_dataloader = dict(
dataset=dict(
data_root=data_root,
type=dataset_type,
ann_file='annotations/lvis_o... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/lvis/grounding_dino_swin-t_finetune_16xb4_1x_lvis_866_337.py | configs/mm_grounding_dino/lvis/grounding_dino_swin-t_finetune_16xb4_1x_lvis_866_337.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
data_root = 'data/coco/'
model = dict(test_cfg=dict(
max_per_img=300,
chunked_size=40,
))
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='RandomFlip', prob=0.5),
dict(
ty... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/lvis/grounding_dino_swin-t_pretrain_zeroshot_mini-lvis.py | configs/mm_grounding_dino/lvis/grounding_dino_swin-t_pretrain_zeroshot_mini-lvis.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
model = dict(test_cfg=dict(
max_per_img=300,
chunked_size=40,
))
dataset_type = 'LVISV1Dataset'
data_root = 'data/coco/'
val_dataloader = dict(
dataset=dict(
data_root=data_root,
type=dataset_type,
ann_file='annotations/lvis_v... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/coco/grounding_dino_swin-t_finetune_16xb4_1x_coco.py | configs/mm_grounding_dino/coco/grounding_dino_swin-t_finetune_16xb4_1x_coco.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
data_root = 'data/coco/'
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='RandomFlip', prob=0.5),
dict(
type='RandomChoice',
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/mm_grounding_dino/coco/grounding_dino_swin-t_finetune_16xb4_1x_sft_coco.py | configs/mm_grounding_dino/coco/grounding_dino_swin-t_finetune_16xb4_1x_sft_coco.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
data_root = 'data/coco/'
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='RandomFlip', prob=0.5),
dict(
type='RandomChoice',
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/mm_grounding_dino/coco/grounding_dino_swin-t_finetune_16xb4_1x_coco_48_17.py | configs/mm_grounding_dino/coco/grounding_dino_swin-t_finetune_16xb4_1x_coco_48_17.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
data_root = 'data/coco/'
base_classes = ('person', 'bicycle', 'car', 'motorcycle', 'train', 'truck',
'boat', 'bench', 'bird', 'horse', 'sheep', 'bear', 'zebra',
'giraffe', 'backpack', 'handbag', 'suitcase', 'frisbee',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/ruod/grounding_dino_swin-t_finetune_8xb4_1x_ruod.py | configs/mm_grounding_dino/ruod/grounding_dino_swin-t_finetune_8xb4_1x_ruod.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
data_root = 'data/RUOD/'
class_name = ('holothurian', 'echinus', 'scallop', 'starfish', 'fish',
'corals', 'diver', 'cuttlefish', 'turtle', 'jellyfish')
palette = [(235, 211, 70), (106, 90, 205), (160, 32, 240), (176, 23, 31),
(142, 0, 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/mm_grounding_dino/rtts/grounding_dino_swin-t_finetune_8xb4_1x_rtts.py | configs/mm_grounding_dino/rtts/grounding_dino_swin-t_finetune_8xb4_1x_rtts.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
data_root = 'data/RTTS/'
class_name = ('bicycle', 'bus', 'car', 'motorbike', 'person')
palette = [(255, 97, 0), (0, 201, 87), (176, 23, 31), (138, 43, 226),
(30, 144, 255)]
metainfo = dict(classes=class_name, palette=palette)
train_pipeline = [
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/mm_grounding_dino/flickr30k/grounding_dino_swin-t-pretrain_flickr30k.py | configs/mm_grounding_dino/flickr30k/grounding_dino_swin-t-pretrain_flickr30k.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
dataset_type = 'Flickr30kDataset'
data_root = 'data/flickr30k_entities/'
test_pipeline = [
dict(
type='LoadImageFromFile', backend_args=None,
imdecode_backend='pillow'),
dict(
type='FixScaleResize',
scale=(800, 1333),
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/dod/grounding_dino_swin-t_pretrain_zeroshot_parallel_dod.py | configs/mm_grounding_dino/dod/grounding_dino_swin-t_pretrain_zeroshot_parallel_dod.py | _base_ = 'grounding_dino_swin-t_pretrain_zeroshot_concat_dod.py'
model = dict(test_cfg=dict(chunked_size=1))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/dod/grounding_dino_swin-t_pretrain_zeroshot_concat_dod.py | configs/mm_grounding_dino/dod/grounding_dino_swin-t_pretrain_zeroshot_concat_dod.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
data_root = 'data/d3/'
test_pipeline = [
dict(
type='LoadImageFromFile', backend_args=None,
imdecode_backend='pillow'),
dict(
type='FixScaleResize',
scale=(800, 1333),
keep_ratio=True,
backend='pillow'),
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/refcoco/grounding_dino_swin-t_finetune_8xb4_5e_grefcoco.py | configs/mm_grounding_dino/refcoco/grounding_dino_swin-t_finetune_8xb4_5e_grefcoco.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
data_root = 'data/coco/'
train_pipeline = [
dict(type='LoadImageFromFile', backend_args=_base_.backend_args),
dict(type='LoadAnnotations', with_bbox=True),
# change this
dict(type='RandomFlip', prob=0.0),
dict(
type='RandomChoice',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/refcoco/grounding_dino_swin-t_finetune_8xb4_5e_refcocog.py | configs/mm_grounding_dino/refcoco/grounding_dino_swin-t_finetune_8xb4_5e_refcocog.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
data_root = 'data/coco/'
train_pipeline = [
dict(type='LoadImageFromFile', backend_args=_base_.backend_args),
dict(type='LoadAnnotations', with_bbox=True),
# change this
dict(type='RandomFlip', prob=0.0),
dict(
type='RandomChoice',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/refcoco/grounding_dino_swin-t_finetune_8xb4_5e_refcoco.py | configs/mm_grounding_dino/refcoco/grounding_dino_swin-t_finetune_8xb4_5e_refcoco.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
data_root = 'data/coco/'
train_pipeline = [
dict(type='LoadImageFromFile', backend_args=_base_.backend_args),
dict(type='LoadAnnotations', with_bbox=True),
# change this
dict(type='RandomFlip', prob=0.0),
dict(
type='RandomChoice',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/refcoco/grounding_dino_swin-t_finetune_8xb4_5e_refcoco_plus.py | configs/mm_grounding_dino/refcoco/grounding_dino_swin-t_finetune_8xb4_5e_refcoco_plus.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
data_root = 'data/coco/'
train_pipeline = [
dict(type='LoadImageFromFile', backend_args=_base_.backend_args),
dict(type='LoadAnnotations', with_bbox=True),
# change this
dict(type='RandomFlip', prob=0.0),
dict(
type='RandomChoice',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/refcoco/grounding_dino_swin-t_pretrain_zeroshot_refexp.py | configs/mm_grounding_dino/refcoco/grounding_dino_swin-t_pretrain_zeroshot_refexp.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
# 30 is an empirical value, just set it to the maximum value
# without affecting the evaluation result
model = dict(test_cfg=dict(max_per_img=30))
data_root = 'data/coco/'
test_pipeline = [
dict(
type='LoadImageFromFile', backend_args=None,
i... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/mm_grounding_dino/cityscapes/grounding_dino_swin-t_finetune_8xb4_50e_cityscapes.py | configs/mm_grounding_dino/cityscapes/grounding_dino_swin-t_finetune_8xb4_50e_cityscapes.py | _base_ = '../grounding_dino_swin-t_pretrain_obj365.py'
data_root = 'data/cityscapes/'
class_name = ('person', 'rider', 'car', 'truck', 'bus', 'train', 'motorcycle',
'bicycle')
palette = [(220, 20, 60), (255, 0, 0), (0, 0, 142), (0, 0, 70), (0, 60, 100),
(0, 80, 100), (0, 0, 230), (119, 11, 32)... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/ddod/ddod_r50_fpn_1x_coco.py | configs/ddod/ddod_r50_fpn_1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
type='DDOD',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
bgr_to_rg... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/cornernet/cornernet_hourglass104_10xb5-crop511-210e-mstest_coco.py | configs/cornernet/cornernet_hourglass104_10xb5-crop511-210e-mstest_coco.py | _base_ = './cornernet_hourglass104_8xb6-210e-mstest_coco.py'
train_dataloader = dict(batch_size=5)
# NOTE: `auto_scale_lr` is for automatically scaling LR,
# USER SHOULD NOT CHANGE ITS VALUES.
# base_batch_size = (10 GPUs) x (5 samples per GPU)
auto_scale_lr = dict(base_batch_size=50)
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/cornernet/cornernet_hourglass104_32xb3-210e-mstest_coco.py | configs/cornernet/cornernet_hourglass104_32xb3-210e-mstest_coco.py | _base_ = './cornernet_hourglass104_8xb6-210e-mstest_coco.py'
train_dataloader = dict(batch_size=3)
# NOTE: `auto_scale_lr` is for automatically scaling LR,
# USER SHOULD NOT CHANGE ITS VALUES.
# base_batch_size = (32 GPUs) x (3 samples per GPU)
auto_scale_lr = dict(base_batch_size=96)
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/cornernet/cornernet_hourglass104_8xb6-210e-mstest_coco.py | configs/cornernet/cornernet_hourglass104_8xb6-210e-mstest_coco.py | _base_ = [
'../_base_/default_runtime.py', '../_base_/datasets/coco_detection.py'
]
data_preprocessor = dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
bgr_to_rgb=True)
# model settings
model = dict(
type='CornerNet',
data_preprocessor=data_pr... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/tood/tood_r50_fpn_anchor-based_1x_coco.py | configs/tood/tood_r50_fpn_anchor-based_1x_coco.py | _base_ = './tood_r50_fpn_1x_coco.py'
model = dict(bbox_head=dict(anchor_type='anchor_based'))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/tood/tood_r50_fpn_1x_coco.py | configs/tood/tood_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='TOOD',
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/tood/tood_r101-dconv-c3-c5_fpn_ms-2x_coco.py | configs/tood/tood_r101-dconv-c3-c5_fpn_ms-2x_coco.py | _base_ = './tood_r101_fpn_ms-2x_coco.py'
model = dict(
backbone=dict(
dcn=dict(type='DCNv2', deformable_groups=1, fallback_on_stride=False),
stage_with_dcn=(False, True, True, True)),
bbox_head=dict(num_dcn=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/tood/tood_x101-64x4d-dconv-c4-c5_fpn_ms-2x_coco.py | configs/tood/tood_x101-64x4d-dconv-c4-c5_fpn_ms-2x_coco.py | _base_ = './tood_x101-64x4d_fpn_ms-2x_coco.py'
model = dict(
backbone=dict(
dcn=dict(type='DCNv2', deformable_groups=1, fallback_on_stride=False),
stage_with_dcn=(False, False, True, True),
),
bbox_head=dict(num_dcn=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/tood/tood_r101_fpn_ms-2x_coco.py | configs/tood/tood_r101_fpn_ms-2x_coco.py | _base_ = './tood_r50_fpn_ms-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/tood/tood_r50_fpn_ms-2x_coco.py | configs/tood/tood_r50_fpn_ms-2x_coco.py | _base_ = './tood_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],
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/tood/tood_x101-64x4d_fpn_ms-2x_coco.py | configs/tood/tood_x101-64x4d_fpn_ms-2x_coco.py | _base_ = './tood_r50_fpn_ms-2x_coco.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/fcos/fcos_r50-dcn-caffe_fpn_gn-head-center-normbbox-centeronreg-giou_1x_coco.py | configs/fcos/fcos_r50-dcn-caffe_fpn_gn-head-center-normbbox-centeronreg-giou_1x_coco.py | _base_ = 'fcos_r50-caffe_fpn_gn-head_1x_coco.py'
# model settings
model = dict(
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[103.530, 116.280, 123.675],
std=[1.0, 1.0, 1.0],
bgr_to_rgb=False,
pad_size_divisor=32),
backbone=dict(
dcn=dict(type='DCNv2'... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/fcos/fcos_r101-caffe_fpn_gn-head-1x_coco.py | configs/fcos/fcos_r101-caffe_fpn_gn-head-1x_coco.py | _base_ = './fcos_r50-caffe_fpn_gn-head_1x_coco.py'
# model settings
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://detectron/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/fcos/fcos_r50-caffe_fpn_gn-head_4xb4-1x_coco.py | configs/fcos/fcos_r50-caffe_fpn_gn-head_4xb4-1x_coco.py | # TODO: Remove this config after benchmarking all related configs
_base_ = 'fcos_r50-caffe_fpn_gn-head_1x_coco.py'
# dataset settings
train_dataloader = dict(batch_size=4, num_workers=4)
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/fcos/fcos_r50-caffe_fpn_gn-head-center_1x_coco.py | configs/fcos/fcos_r50-caffe_fpn_gn-head-center_1x_coco.py | _base_ = './fcos_r50-caffe_fpn_gn-head_1x_coco.py'
# model settings
model = dict(bbox_head=dict(center_sampling=True, center_sample_radius=1.5))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/fcos/fcos_r50-caffe_fpn_gn-head-center-normbbox-centeronreg-giou_1x_coco.py | configs/fcos/fcos_r50-caffe_fpn_gn-head-center-normbbox-centeronreg-giou_1x_coco.py | _base_ = 'fcos_r50-caffe_fpn_gn-head_1x_coco.py'
# model setting
model = dict(
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[103.530, 116.280, 123.675],
std=[1.0, 1.0, 1.0],
bgr_to_rgb=False,
pad_size_divisor=32),
backbone=dict(
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/fcos/fcos_r18_fpn_gn-head-center-normbbox-centeronreg-giou_8xb8-amp-lsj-200e_coco.py | configs/fcos/fcos_r18_fpn_gn-head-center-normbbox-centeronreg-giou_8xb8-amp-lsj-200e_coco.py | _base_ = './fcos_r50_fpn_gn-head-center-normbbox-centeronreg-giou_8xb8-amp-lsj-200e_coco.py' # noqa
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/fcos/fcos_r50-caffe_fpn_gn-head_ms-640-800-2x_coco.py | configs/fcos/fcos_r50-caffe_fpn_gn-head_ms-640-800-2x_coco.py | _base_ = './fcos_r50-caffe_fpn_gn-head_1x_coco.py'
# dataset settings
train_pipeline = [
dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='RandomChoiceResize',
scales=[(1333, 640), (1333, 800)],
keep_ratio... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/fcos/fcos_r101_fpn_gn-head-center-normbbox-centeronreg-giou_8xb8-amp-lsj-200e_coco.py | configs/fcos/fcos_r101_fpn_gn-head-center-normbbox-centeronreg-giou_8xb8-amp-lsj-200e_coco.py | _base_ = './fcos_r50_fpn_gn-head-center-normbbox-centeronreg-giou_8xb8-amp-lsj-200e_coco.py' # noqa
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/fcos/fcos_r50_fpn_gn-head-center-normbbox-centeronreg-giou_8xb8-amp-lsj-200e_coco.py | configs/fcos/fcos_r50_fpn_gn-head-center-normbbox-centeronreg-giou_8xb8-amp-lsj-200e_coco.py | _base_ = '../common/lsj-200e_coco-detection.py'
image_size = (1024, 1024)
batch_augments = [dict(type='BatchFixedSizePad', size=image_size)]
# model settings
model = dict(
type='FCOS',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.1... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/fcos/fcos_r101-caffe_fpn_gn-head_ms-640-800-2x_coco.py | configs/fcos/fcos_r101-caffe_fpn_gn-head_ms-640-800-2x_coco.py | _base_ = './fcos_r50-caffe_fpn_gn-head_1x_coco.py'
# model settings
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://detectron/resnet101_caffe')))
# dataset settings
train_pipeline = [
dict(type='LoadImageFromFile', back... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/fcos/fcos_r50-caffe_fpn_gn-head_1x_coco.py | configs/fcos/fcos_r50-caffe_fpn_gn-head_1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# model settings
model = dict(
type='FCOS',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[102.9801, 115.9465, 122.7717],
std=[1.0, 1.0, 1.0],
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/fcos/fcos_x101-64x4d_fpn_gn-head_ms-640-800-2x_coco.py | configs/fcos/fcos_x101-64x4d_fpn_gn-head_ms-640-800-2x_coco.py | _base_ = './fcos_r50-caffe_fpn_gn-head_1x_coco.py'
# model settings
model = dict(
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
bgr_to_rgb=True,
pad_size_divisor=32),
backbone=dict(
type='ResNeXt'... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/yolof/yolof_r50-c5_8xb8-iter-1x_coco.py | configs/yolof/yolof_r50-c5_8xb8-iter-1x_coco.py | _base_ = './yolof_r50-c5_8xb8-1x_coco.py'
# We implemented the iter-based config according to the source code.
# COCO dataset has 117266 images after filtering. We use 8 gpu and
# 8 batch size training, so 22500 is equivalent to
# 22500/(117266/(8x8))=12.3 epoch, 15000 is equivalent to 8.2 epoch,
# 20000 is equivalent... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/yolof/yolof_r50-c5_8xb8-1x_coco.py | configs/yolof/yolof_r50-c5_8xb8-1x_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
type='YOLOF',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[103.530, 116.280, 123.675],
std=[1.0, 1.0, 1.0],
bgr_to_rgb=Fals... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/lvis/mask-rcnn_x101-32x4d_fpn_sample1e-3_ms-2x_lvis-v0.5.py | configs/lvis/mask-rcnn_x101-32x4d_fpn_sample1e-3_ms-2x_lvis-v0.5.py | _base_ = './mask-rcnn_r50_fpn_sample1e-3_ms-2x_lvis-v0.5.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/lvis/mask-rcnn_r101_fpn_sample1e-3_ms-2x_lvis-v0.5.py | configs/lvis/mask-rcnn_r101_fpn_sample1e-3_ms-2x_lvis-v0.5.py | _base_ = './mask-rcnn_r50_fpn_sample1e-3_ms-2x_lvis-v0.5.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/lvis/mask-rcnn_x101-64x4d_fpn_sample1e-3_ms-1x_lvis-v1.py | configs/lvis/mask-rcnn_x101-64x4d_fpn_sample1e-3_ms-1x_lvis-v1.py | _base_ = './mask-rcnn_r50_fpn_sample1e-3_ms-1x_lvis-v1.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
s... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/lvis/mask-rcnn_r50_fpn_sample1e-3_ms-2x_lvis-v0.5.py | configs/lvis/mask-rcnn_r50_fpn_sample1e-3_ms-2x_lvis-v0.5.py | _base_ = [
'../_base_/models/mask-rcnn_r50_fpn.py',
'../_base_/datasets/lvis_v0.5_instance.py',
'../_base_/schedules/schedule_2x.py', '../_base_/default_runtime.py'
]
model = dict(
roi_head=dict(
bbox_head=dict(num_classes=1230), mask_head=dict(num_classes=1230)),
test_cfg=dict(
rcnn... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/lvis/mask-rcnn_x101-32x4d_fpn_sample1e-3_ms-1x_lvis-v1.py | configs/lvis/mask-rcnn_x101-32x4d_fpn_sample1e-3_ms-1x_lvis-v1.py | _base_ = './mask-rcnn_r50_fpn_sample1e-3_ms-1x_lvis-v1.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
s... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/lvis/mask-rcnn_r101_fpn_sample1e-3_ms-1x_lvis-v1.py | configs/lvis/mask-rcnn_r101_fpn_sample1e-3_ms-1x_lvis-v1.py | _base_ = './mask-rcnn_r50_fpn_sample1e-3_ms-1x_lvis-v1.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/lvis/mask-rcnn_r50_fpn_sample1e-3_ms-1x_lvis-v1.py | configs/lvis/mask-rcnn_r50_fpn_sample1e-3_ms-1x_lvis-v1.py | _base_ = [
'../_base_/models/mask-rcnn_r50_fpn.py',
'../_base_/datasets/lvis_v1_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
roi_head=dict(
bbox_head=dict(num_classes=1203), mask_head=dict(num_classes=1203)),
test_cfg=dict(
rcnn=d... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/lvis/mask-rcnn_x101-64x4d_fpn_sample1e-3_ms-2x_lvis-v0.5.py | configs/lvis/mask-rcnn_x101-64x4d_fpn_sample1e-3_ms-2x_lvis-v0.5.py | _base_ = './mask-rcnn_r50_fpn_sample1e-3_ms-2x_lvis-v0.5.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/conditional_detr/conditional-detr_r50_8xb2-50e_coco.py | configs/conditional_detr/conditional-detr_r50_8xb2-50e_coco.py | _base_ = ['../detr/detr_r50_8xb2-150e_coco.py']
model = dict(
type='ConditionalDETR',
num_queries=300,
decoder=dict(
num_layers=6,
layer_cfg=dict(
self_attn_cfg=dict(
_delete_=True,
embed_dims=256,
num_heads=8,
attn_... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/openimages/faster-rcnn_r50_fpn_32xb2-1x_openimages-challenge.py | configs/openimages/faster-rcnn_r50_fpn_32xb2-1x_openimages-challenge.py | _base_ = ['faster-rcnn_r50_fpn_32xb2-1x_openimages.py']
model = dict(
roi_head=dict(bbox_head=dict(num_classes=500)),
test_cfg=dict(rcnn=dict(score_thr=0.01)))
# dataset settings
dataset_type = 'OpenImagesChallengeDataset'
train_dataloader = dict(
dataset=dict(
type=dataset_type,
ann_file=... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/openimages/faster-rcnn_r50_fpn_32xb2-cas-1x_openimages.py | configs/openimages/faster-rcnn_r50_fpn_32xb2-cas-1x_openimages.py | _base_ = ['faster-rcnn_r50_fpn_32xb2-1x_openimages.py']
# Use ClassAwareSampler
train_dataloader = dict(
sampler=dict(_delete_=True, type='ClassAwareSampler', num_sample_class=1))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/openimages/ssd300_32xb8-36e_openimages.py | configs/openimages/ssd300_32xb8-36e_openimages.py | _base_ = [
'../_base_/models/ssd300.py', '../_base_/datasets/openimages_detection.py',
'../_base_/default_runtime.py', '../_base_/schedules/schedule_1x.py'
]
model = dict(
bbox_head=dict(
num_classes=601,
anchor_generator=dict(basesize_ratio_range=(0.2, 0.9))))
# dataset settings
dataset_typ... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/openimages/retinanet_r50_fpn_32xb2-1x_openimages.py | configs/openimages/retinanet_r50_fpn_32xb2-1x_openimages.py | _base_ = [
'../_base_/models/retinanet_r50_fpn.py',
'../_base_/datasets/openimages_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(bbox_head=dict(num_classes=601))
# learning rate
param_scheduler = [
dict(
type='LinearLR',
start_factor... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.