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/_base_/schedules/schedule_1x.py | configs/_base_/schedules/schedule_1x.py | # training schedule for 1x
train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=12, val_interval=1)
val_cfg = dict(type='ValLoop')
test_cfg = dict(type='TestLoop')
# learning rate
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='Mu... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/coco_panoptic.py | configs/_base_/datasets/coco_panoptic.py | # dataset settings
dataset_type = 'CocoPanopticDataset'
data_root = 'data/coco/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detection/coco/'
# Meth... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/cityscapes_detection.py | configs/_base_/datasets/cityscapes_detection.py | # dataset settings
dataset_type = 'CityscapesDataset'
data_root = 'data/cityscapes/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/segmentation/citysca... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/refcocog.py | configs/_base_/datasets/refcocog.py | # dataset settings
dataset_type = 'RefCocoDataset'
data_root = 'data/coco/'
backend_args = None
test_pipeline = [
dict(type='LoadImageFromFile', backend_args=backend_args),
dict(type='Resize', scale=(1333, 800), keep_ratio=True),
dict(
type='LoadAnnotations',
with_mask=True,
with_b... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/mot_challenge_det.py | configs/_base_/datasets/mot_challenge_det.py | # dataset settings
dataset_type = 'CocoDataset'
data_root = 'data/MOT17/'
backend_args = None
train_pipeline = [
dict(type='LoadImageFromFile', backend_args=backend_args, to_float32=True),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='RandomResize',
scale=(1088, 1088),
r... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/mot_challenge.py | configs/_base_/datasets/mot_challenge.py | # dataset settings
dataset_type = 'MOTChallengeDataset'
data_root = 'data/MOT17/'
img_scale = (1088, 1088)
backend_args = None
# data pipeline
train_pipeline = [
dict(
type='UniformRefFrameSample',
num_ref_imgs=1,
frame_range=10,
filter_key_img=True),
dict(
type='Transfo... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/openimages_detection.py | configs/_base_/datasets/openimages_detection.py | # dataset settings
dataset_type = 'OpenImagesDataset'
data_root = 'data/OpenImages/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detection/coco/'
# ... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/ade20k_semantic.py | configs/_base_/datasets/ade20k_semantic.py | dataset_type = 'ADE20KSegDataset'
data_root = 'data/ADEChallengeData2016/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detection/ADEChallengeData2016... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/voc0712.py | configs/_base_/datasets/voc0712.py | # dataset settings
dataset_type = 'VOCDataset'
data_root = 'data/VOCdevkit/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically Infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detection/segmentation/VOCde... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/deepfashion.py | configs/_base_/datasets/deepfashion.py | # dataset settings
dataset_type = 'DeepFashionDataset'
data_root = 'data/DeepFashion/In-shop/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detection/... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/ade20k_panoptic.py | configs/_base_/datasets/ade20k_panoptic.py | # dataset settings
dataset_type = 'ADE20KPanopticDataset'
data_root = 'data/ADEChallengeData2016/'
backend_args = None
test_pipeline = [
dict(type='LoadImageFromFile', backend_args=backend_args),
dict(type='Resize', scale=(2560, 640), keep_ratio=True),
dict(type='LoadPanopticAnnotations', backend_args=bac... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/lvis_v1_instance.py | configs/_base_/datasets/lvis_v1_instance.py | # dataset settings
_base_ = 'lvis_v0.5_instance.py'
dataset_type = 'LVISV1Dataset'
data_root = 'data/lvis_v1/'
train_dataloader = dict(
dataset=dict(
dataset=dict(
type=dataset_type,
data_root=data_root,
ann_file='annotations/lvis_v1_train.json',
data_prefix=... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/youtube_vis.py | configs/_base_/datasets/youtube_vis.py | dataset_type = 'YouTubeVISDataset'
data_root = 'data/youtube_vis_2019/'
dataset_version = data_root[-5:-1] # 2019 or 2021
backend_args = None
# dataset settings
train_pipeline = [
dict(
type='UniformRefFrameSample',
num_ref_imgs=1,
frame_range=100,
filter_key_img=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/_base_/datasets/objects365v1_detection.py | configs/_base_/datasets/objects365v1_detection.py | # dataset settings
dataset_type = 'Objects365V1Dataset'
data_root = 'data/Objects365/Obj365_v1/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detectio... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/mot_challenge_reid.py | configs/_base_/datasets/mot_challenge_reid.py | # dataset settings
dataset_type = 'ReIDDataset'
data_root = 'data/MOT17/'
backend_args = None
# data pipeline
train_pipeline = [
dict(
type='TransformBroadcaster',
share_random_params=False,
transforms=[
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/_base_/datasets/coco_caption.py | configs/_base_/datasets/coco_caption.py | # data settings
dataset_type = 'CocoCaptionDataset'
data_root = 'data/coco/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detection/coco/'
# Method ... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/coco_semantic.py | configs/_base_/datasets/coco_semantic.py | # dataset settings
dataset_type = 'CocoSegDataset'
data_root = 'data/coco/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detection/coco/'
# Method 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/_base_/datasets/coco_instance_semantic.py | configs/_base_/datasets/coco_instance_semantic.py | # dataset settings
dataset_type = 'CocoDataset'
data_root = 'data/coco/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detection/coco/'
# Method 2: Us... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/v3det.py | configs/_base_/datasets/v3det.py | # dataset settings
dataset_type = 'V3DetDataset'
data_root = 'data/V3Det/'
backend_args = None
train_pipeline = [
dict(type='LoadImageFromFile', backend_args=backend_args),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='RandomChoiceResize',
scales=[(1333, 640), (1333, 672), (133... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/ade20k_instance.py | configs/_base_/datasets/ade20k_instance.py | # dataset settings
dataset_type = 'ADE20KInstanceDataset'
data_root = 'data/ADEChallengeData2016/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detect... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/wider_face.py | configs/_base_/datasets/wider_face.py | # dataset settings
dataset_type = 'WIDERFaceDataset'
data_root = 'data/WIDERFace/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detection/cityscapes/'
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/dsdl.py | configs/_base_/datasets/dsdl.py | dataset_type = 'DSDLDetDataset'
data_root = 'path to dataset folder'
train_ann = 'path to train yaml file'
val_ann = 'path to val yaml file'
backend_args = None
# backend_args = dict(
# backend='petrel',
# path_mapping=dict({
# './data/': "s3://open_data/",
# 'data/': "s3://open_data/"
# })... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/coco_detection.py | configs/_base_/datasets/coco_detection.py | # dataset settings
dataset_type = 'CocoDataset'
data_root = 'data/coco/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detection/coco/'
# Method 2: Us... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/isaid_instance.py | configs/_base_/datasets/isaid_instance.py | # dataset settings
dataset_type = 'iSAIDDataset'
data_root = 'data/iSAID/'
backend_args = None
# Please see `projects/iSAID/README.md` for data preparation
train_pipeline = [
dict(type='LoadImageFromFile', backend_args=backend_args),
dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
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/_base_/datasets/refcoco+.py | configs/_base_/datasets/refcoco+.py | # dataset settings
dataset_type = 'RefCocoDataset'
data_root = 'data/coco/'
backend_args = None
test_pipeline = [
dict(type='LoadImageFromFile', backend_args=backend_args),
dict(type='Resize', scale=(1333, 800), keep_ratio=True),
dict(
type='LoadAnnotations',
with_mask=True,
with_b... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/lvis_v0.5_instance.py | configs/_base_/datasets/lvis_v0.5_instance.py | # dataset settings
dataset_type = 'LVISV05Dataset'
data_root = 'data/lvis_v0.5/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detection/lvis_v0.5/'
#... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/cityscapes_instance.py | configs/_base_/datasets/cityscapes_instance.py | # dataset settings
dataset_type = 'CityscapesDataset'
data_root = 'data/cityscapes/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/segmentation/citysca... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/coco_instance.py | configs/_base_/datasets/coco_instance.py | # dataset settings
dataset_type = 'CocoDataset'
data_root = 'data/coco/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detection/coco/'
# Method 2: Us... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/objects365v2_detection.py | configs/_base_/datasets/objects365v2_detection.py | # dataset settings
dataset_type = 'Objects365V2Dataset'
data_root = 'data/Objects365/Obj365_v2/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detectio... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/refcoco.py | configs/_base_/datasets/refcoco.py | # dataset settings
dataset_type = 'RefCocoDataset'
data_root = 'data/coco/'
backend_args = None
test_pipeline = [
dict(type='LoadImageFromFile', backend_args=backend_args),
dict(type='Resize', scale=(1333, 800), keep_ratio=True),
dict(
type='LoadAnnotations',
with_mask=True,
with_b... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/datasets/semi_coco_detection.py | configs/_base_/datasets/semi_coco_detection.py | # dataset settings
dataset_type = 'CocoDataset'
data_root = 'data/coco/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detection/coco/'
# Method 2: Us... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/models/faster-rcnn_r50-caffe-dc5.py | configs/_base_/models/faster-rcnn_r50-caffe-dc5.py | # model settings
norm_cfg = dict(type='BN', requires_grad=False)
model = dict(
type='FasterRCNN',
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(
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/models/rpn_r50-caffe-c4.py | configs/_base_/models/rpn_r50-caffe-c4.py | # model settings
model = dict(
type='RPN',
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(
type='ResNet',
depth=50,
num_stages=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/_base_/models/faster-rcnn_r50_fpn.py | configs/_base_/models/faster-rcnn_r50_fpn.py | # model settings
model = dict(
type='FasterRCNN',
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='ResNet',
depth=50,
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/_base_/models/ssd300.py | configs/_base_/models/ssd300.py | # model settings
input_size = 300
model = dict(
type='SingleStageDetector',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[1, 1, 1],
bgr_to_rgb=True,
pad_size_divisor=1),
backbone=dict(
type='SSDVGG',
depth=16,... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/models/faster-rcnn_r50-caffe-c4.py | configs/_base_/models/faster-rcnn_r50-caffe-c4.py | # model settings
norm_cfg = dict(type='BN', requires_grad=False)
model = dict(
type='FasterRCNN',
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(
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/models/rpn_r50_fpn.py | configs/_base_/models/rpn_r50_fpn.py | # model settings
model = dict(
type='RPN',
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='ResNet',
depth=50,
num_stage... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/models/cascade-mask-rcnn_r50_fpn.py | configs/_base_/models/cascade-mask-rcnn_r50_fpn.py | # model settings
model = dict(
type='CascadeRCNN',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
bgr_to_rgb=True,
pad_mask=True,
pad_size_divisor=32),
backbone=dict(
type='ResNet',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/models/mask-rcnn_r50_fpn.py | configs/_base_/models/mask-rcnn_r50_fpn.py | # model settings
model = dict(
type='MaskRCNN',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
bgr_to_rgb=True,
pad_mask=True,
pad_size_divisor=32),
backbone=dict(
type='ResNet',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/models/mask-rcnn_r50-caffe-c4.py | configs/_base_/models/mask-rcnn_r50-caffe-c4.py | # model settings
norm_cfg = dict(type='BN', requires_grad=False)
model = dict(
type='MaskRCNN',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[103.530, 116.280, 123.675],
std=[1.0, 1.0, 1.0],
bgr_to_rgb=False,
pad_mask=True,
pad_size_divisor=32),
ba... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/models/cascade-rcnn_r50_fpn.py | configs/_base_/models/cascade-rcnn_r50_fpn.py | # model settings
model = dict(
type='CascadeRCNN',
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='ResNet',
depth=50,
n... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/models/retinanet_r50_fpn.py | configs/_base_/models/retinanet_r50_fpn.py | # model settings
model = dict(
type='RetinaNet',
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='ResNet',
depth=50,
num... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/_base_/models/fast-rcnn_r50_fpn.py | configs/_base_/models/fast-rcnn_r50_fpn.py | # model settings
model = dict(
type='FastRCNN',
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='ResNet',
depth=50,
num_... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/point_rend/point-rend_r50-caffe_fpn_ms-3x_coco.py | configs/point_rend/point-rend_r50-caffe_fpn_ms-3x_coco.py | _base_ = './point-rend_r50-caffe_fpn_ms-1x_coco.py'
max_epochs = 36
# learning policy
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=[... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/point_rend/point-rend_r50-caffe_fpn_ms-1x_coco.py | configs/point_rend/point-rend_r50-caffe_fpn_ms-1x_coco.py | _base_ = '../mask_rcnn/mask-rcnn_r50-caffe_fpn_ms-1x_coco.py'
# model settings
model = dict(
type='PointRend',
roi_head=dict(
type='PointRendRoIHead',
mask_roi_extractor=dict(
type='GenericRoIExtractor',
aggregation='concat',
roi_layer=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/empirical_attention/faster-rcnn_r50-attn0010_fpn_1x_coco.py | configs/empirical_attention/faster-rcnn_r50-attn0010_fpn_1x_coco.py | _base_ = '../faster_rcnn/faster-rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(plugins=[
dict(
cfg=dict(
type='GeneralizedAttention',
spatial_range=-1,
num_heads=8,
attention_type='0010',
kv_stride=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/empirical_attention/faster-rcnn_r50-attn1111_fpn_1x_coco.py | configs/empirical_attention/faster-rcnn_r50-attn1111_fpn_1x_coco.py | _base_ = '../faster_rcnn/faster-rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(plugins=[
dict(
cfg=dict(
type='GeneralizedAttention',
spatial_range=-1,
num_heads=8,
attention_type='1111',
kv_stride=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/empirical_attention/faster-rcnn_r50-attn0010-dcn_fpn_1x_coco.py | configs/empirical_attention/faster-rcnn_r50-attn0010-dcn_fpn_1x_coco.py | _base_ = '../faster_rcnn/faster-rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
plugins=[
dict(
cfg=dict(
type='GeneralizedAttention',
spatial_range=-1,
num_heads=8,
attention_type='0010',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/empirical_attention/faster-rcnn_r50-attn1111-dcn_fpn_1x_coco.py | configs/empirical_attention/faster-rcnn_r50-attn1111-dcn_fpn_1x_coco.py | _base_ = '../faster_rcnn/faster-rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
plugins=[
dict(
cfg=dict(
type='GeneralizedAttention',
spatial_range=-1,
num_heads=8,
attention_type='1111',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/regnet/cascade-mask-rcnn_regnetx-800MF_fpn_ms-3x_coco.py | configs/regnet/cascade-mask-rcnn_regnetx-800MF_fpn_ms-3x_coco.py | _base_ = 'cascade-mask-rcnn_regnetx-3.2GF_fpn_ms-3x_coco.py'
model = dict(
backbone=dict(
type='RegNet',
arch='regnetx_800mf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
ini... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/regnet/mask-rcnn_regnetx-12GF_fpn_1x_coco.py | configs/regnet/mask-rcnn_regnetx-12GF_fpn_1x_coco.py | _base_ = './mask-rcnn_regnetx-3.2GF_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='RegNet',
arch='regnetx_12gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
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/regnet/mask-rcnn_regnetx-3.2GF_fpn_1x_coco.py | configs/regnet/mask-rcnn_regnetx-3.2GF_fpn_1x_coco.py | _base_ = [
'../_base_/models/mask-rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
data_preprocessor=dict(
# The mean and std are used in PyCls when training RegNets
mean=[103.53, 116.28, 123.675... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/regnet/cascade-mask-rcnn_regnetx-4GF_fpn_ms-3x_coco.py | configs/regnet/cascade-mask-rcnn_regnetx-4GF_fpn_ms-3x_coco.py | _base_ = 'cascade-mask-rcnn_regnetx-3.2GF_fpn_ms-3x_coco.py'
model = dict(
backbone=dict(
type='RegNet',
arch='regnetx_4.0gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
ini... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/regnet/cascade-mask-rcnn_regnetx-1.6GF_fpn_ms-3x_coco.py | configs/regnet/cascade-mask-rcnn_regnetx-1.6GF_fpn_ms-3x_coco.py | _base_ = 'cascade-mask-rcnn_regnetx-3.2GF_fpn_ms-3x_coco.py'
model = dict(
backbone=dict(
type='RegNet',
arch='regnetx_1.6gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
ini... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/regnet/mask-rcnn_regnetx-400MF_fpn_ms-poly-3x_coco.py | configs/regnet/mask-rcnn_regnetx-400MF_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(
_delete_=True,
type='RegNet',
arch='regnetx_400mf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=Tr... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/regnet/mask-rcnn_regnetx-3.2GF_fpn_ms-3x_coco.py | configs/regnet/mask-rcnn_regnetx-3.2GF_fpn_ms-3x_coco.py | _base_ = [
'../_base_/models/mask-rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
data_preprocessor=dict(
# The mean and std are used in PyCls when training RegNets
mean=[103.53, 116.28, 123.675... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/regnet/faster-rcnn_regnetx-4GF_fpn_ms-3x_coco.py | configs/regnet/faster-rcnn_regnetx-4GF_fpn_ms-3x_coco.py | _base_ = 'faster-rcnn_regnetx-3.2GF_fpn_ms-3x_coco.py'
model = dict(
backbone=dict(
type='RegNet',
arch='regnetx_4.0gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
init_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/regnet/faster-rcnn_regnetx-800MF_fpn_ms-3x_coco.py | configs/regnet/faster-rcnn_regnetx-800MF_fpn_ms-3x_coco.py | _base_ = 'faster-rcnn_regnetx-3.2GF_fpn_ms-3x_coco.py'
model = dict(
backbone=dict(
type='RegNet',
arch='regnetx_800mf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
init_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/regnet/mask-rcnn_regnetx-3.2GF-mdconv-c3-c5_fpn_1x_coco.py | configs/regnet/mask-rcnn_regnetx-3.2GF-mdconv-c3-c5_fpn_1x_coco.py | _base_ = 'mask-rcnn_regnetx-3.2GF_fpn_1x_coco.py'
model = dict(
backbone=dict(
dcn=dict(type='DCNv2', deform_groups=1, fallback_on_stride=False),
stage_with_dcn=(False, True, True, True),
init_cfg=dict(
type='Pretrained', checkpoint='open-mmlab://regnetx_3.2gf')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/regnet/retinanet_regnetx-1.6GF_fpn_1x_coco.py | configs/regnet/retinanet_regnetx-1.6GF_fpn_1x_coco.py | _base_ = './retinanet_regnetx-3.2GF_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='RegNet',
arch='regnetx_1.6gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
init_cfg=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/regnet/mask-rcnn_regnetx-8GF_fpn_1x_coco.py | configs/regnet/mask-rcnn_regnetx-8GF_fpn_1x_coco.py | _base_ = './mask-rcnn_regnetx-3.2GF_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='RegNet',
arch='regnetx_8.0gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
init_cfg=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/regnet/mask-rcnn_regnetx-4GF_fpn_1x_coco.py | configs/regnet/mask-rcnn_regnetx-4GF_fpn_1x_coco.py | _base_ = './mask-rcnn_regnetx-3.2GF_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='RegNet',
arch='regnetx_4.0gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
init_cfg=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/regnet/faster-rcnn_regnetx-3.2GF_fpn_ms-3x_coco.py | configs/regnet/faster-rcnn_regnetx-3.2GF_fpn_ms-3x_coco.py | _base_ = ['../common/ms_3x_coco.py', '../_base_/models/faster-rcnn_r50_fpn.py']
model = dict(
data_preprocessor=dict(
# The mean and std are used in PyCls when training RegNets
mean=[103.53, 116.28, 123.675],
std=[57.375, 57.12, 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/regnet/cascade-mask-rcnn_regnetx-3.2GF_fpn_ms-3x_coco.py | configs/regnet/cascade-mask-rcnn_regnetx-3.2GF_fpn_ms-3x_coco.py | _base_ = [
'../common/ms_3x_coco-instance.py',
'../_base_/models/cascade-mask-rcnn_r50_fpn.py'
]
model = dict(
data_preprocessor=dict(
# The mean and std are used in PyCls when training RegNets
mean=[103.53, 116.28, 123.675],
std=[57.375, 57.12, 58.395],
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/regnet/faster-rcnn_regnetx-3.2GF_fpn_1x_coco.py | configs/regnet/faster-rcnn_regnetx-3.2GF_fpn_1x_coco.py | _base_ = [
'../_base_/models/faster-rcnn_r50_fpn.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
data_preprocessor=dict(
# The mean and std are used in PyCls when training RegNets
mean=[103.53, 116.28, 123.... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/regnet/mask-rcnn_regnetx-1.6GF_fpn_ms-poly-3x_coco.py | configs/regnet/mask-rcnn_regnetx-1.6GF_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(
_delete_=True,
type='RegNet',
arch='regnetx_1.6gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=Tr... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/regnet/faster-rcnn_regnetx-400MF_fpn_ms-3x_coco.py | configs/regnet/faster-rcnn_regnetx-400MF_fpn_ms-3x_coco.py | _base_ = 'faster-rcnn_regnetx-3.2GF_fpn_ms-3x_coco.py'
model = dict(
backbone=dict(
type='RegNet',
arch='regnetx_400mf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
init_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/regnet/cascade-mask-rcnn_regnetx-400MF_fpn_ms-3x_coco.py | configs/regnet/cascade-mask-rcnn_regnetx-400MF_fpn_ms-3x_coco.py | _base_ = 'cascade-mask-rcnn_regnetx-3.2GF_fpn_ms-3x_coco.py'
model = dict(
backbone=dict(
type='RegNet',
arch='regnetx_400mf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
ini... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/regnet/faster-rcnn_regnetx-3.2GF_fpn_2x_coco.py | configs/regnet/faster-rcnn_regnetx-3.2GF_fpn_2x_coco.py | _base_ = './faster-rcnn_regnetx-3.2GF_fpn_1x_coco.py'
# learning policy
max_epochs = 24
train_cfg = dict(max_epochs=max_epochs)
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
begin=0,
end=max_epochs,
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/regnet/mask-rcnn_regnetx-4GF_fpn_ms-poly-3x_coco.py | configs/regnet/mask-rcnn_regnetx-4GF_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(
_delete_=True,
type='RegNet',
arch='regnetx_4.0gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=Tr... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/regnet/mask-rcnn_regnetx-800MF_fpn_ms-poly-3x_coco.py | configs/regnet/mask-rcnn_regnetx-800MF_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(
_delete_=True,
type='RegNet',
arch='regnetx_800mf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=Tr... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/regnet/mask-rcnn_regnetx-6.4GF_fpn_1x_coco.py | configs/regnet/mask-rcnn_regnetx-6.4GF_fpn_1x_coco.py | _base_ = './mask-rcnn_regnetx-3.2GF_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='RegNet',
arch='regnetx_6.4gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
init_cfg=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/regnet/retinanet_regnetx-800MF_fpn_1x_coco.py | configs/regnet/retinanet_regnetx-800MF_fpn_1x_coco.py | _base_ = './retinanet_regnetx-3.2GF_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='RegNet',
arch='regnetx_800mf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
init_cfg=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/regnet/retinanet_regnetx-3.2GF_fpn_1x_coco.py | configs/regnet/retinanet_regnetx-3.2GF_fpn_1x_coco.py | _base_ = [
'../_base_/models/retinanet_r50_fpn.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
data_preprocessor=dict(
# The mean and std are used in PyCls when training RegNets
mean=[103.53, 116.28, 123.67... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/regnet/faster-rcnn_regnetx-1.6GF_fpn_ms-3x_coco.py | configs/regnet/faster-rcnn_regnetx-1.6GF_fpn_ms-3x_coco.py | _base_ = 'faster-rcnn_regnetx-3.2GF_fpn_ms-3x_coco.py'
model = dict(
backbone=dict(
type='RegNet',
arch='regnetx_1.6gf',
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
style='pytorch',
init_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/wider_face/ssd300_8xb32-24e_widerface.py | configs/wider_face/ssd300_8xb32-24e_widerface.py | _base_ = [
'../_base_/models/ssd300.py', '../_base_/datasets/wider_face.py',
'../_base_/default_runtime.py', '../_base_/schedules/schedule_2x.py'
]
model = dict(bbox_head=dict(num_classes=1))
train_pipeline = [
dict(type='LoadImageFromFile', backend_args=_base_.backend_args),
dict(type='LoadAnnotations... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/wider_face/retinanet_r50_fpn_1x_widerface.py | configs/wider_face/retinanet_r50_fpn_1x_widerface.py | _base_ = [
'../_base_/models/retinanet_r50_fpn.py',
'../_base_/datasets/wider_face.py', '../_base_/schedules/schedule_1x.py',
'../_base_/default_runtime.py'
]
# model settings
model = dict(bbox_head=dict(num_classes=1))
# optimizer
optim_wrapper = dict(
optimizer=dict(type='SGD', lr=0.01, momentum=0.9, ... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/misc/d2_retinanet_r50-caffe_fpn_ms-90k_coco.py | configs/misc/d2_retinanet_r50-caffe_fpn_ms-90k_coco.py | _base_ = '../common/ms-90k_coco.py'
# model settings
model = dict(
type='Detectron2Wrapper',
bgr_to_rgb=False,
detector=dict(
# The settings in `d2_detector` will merged into default settings
# in detectron2. More details please refer to
# https://github.com/facebookresearch/detectr... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/misc/d2_mask-rcnn_r50-caffe_fpn_ms-90k_coco.py | configs/misc/d2_mask-rcnn_r50-caffe_fpn_ms-90k_coco.py | _base_ = '../common/ms-poly-90k_coco-instance.py'
# model settings
model = dict(
type='Detectron2Wrapper',
bgr_to_rgb=False,
detector=dict(
# The settings in `d2_detector` will merged into default settings
# in detectron2. More details please refer to
# https://github.com/facebookre... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/misc/d2_faster-rcnn_r50-caffe_fpn_ms-90k_coco.py | configs/misc/d2_faster-rcnn_r50-caffe_fpn_ms-90k_coco.py | _base_ = '../common/ms-90k_coco.py'
# model settings
model = dict(
type='Detectron2Wrapper',
bgr_to_rgb=False,
detector=dict(
# The settings in `d2_detector` will merged into default settings
# in detectron2. More details please refer to
# https://github.com/facebookresearch/detectr... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/centripetalnet/centripetalnet_hourglass104_16xb6-crop511-210e-mstest_coco.py | configs/centripetalnet/centripetalnet_hourglass104_16xb6-crop511-210e-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/ghm/retinanet_x101-32x4d_fpn_ghm-1x_coco.py | configs/ghm/retinanet_x101-32x4d_fpn_ghm-1x_coco.py | _base_ = './retinanet_r50_fpn_ghm-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/ghm/retinanet_x101-64x4d_fpn_ghm-1x_coco.py | configs/ghm/retinanet_x101-64x4d_fpn_ghm-1x_coco.py | _base_ = './retinanet_r50_fpn_ghm-1x_coco.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
style='pytorch... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/ghm/retinanet_r101_fpn_ghm-1x_coco.py | configs/ghm/retinanet_r101_fpn_ghm-1x_coco.py | _base_ = './retinanet_r50_fpn_ghm-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/ghm/retinanet_r50_fpn_ghm-1x_coco.py | configs/ghm/retinanet_r50_fpn_ghm-1x_coco.py | _base_ = '../retinanet/retinanet_r50_fpn_1x_coco.py'
model = dict(
bbox_head=dict(
loss_cls=dict(
_delete_=True,
type='GHMC',
bins=30,
momentum=0.75,
use_sigmoid=True,
loss_weight=1.0),
loss_bbox=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/gcnet/cascade-mask-rcnn_x101-32x4d-syncbn-r16-gcb-c3-c5_fpn_1x_coco.py | configs/gcnet/cascade-mask-rcnn_x101-32x4d-syncbn-r16-gcb-c3-c5_fpn_1x_coco.py | _base_ = '../cascade_rcnn/cascade-mask-rcnn_x101-32x4d_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 16),
stages=(False, True... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gcnet/cascade-mask-rcnn_x101-32x4d-syncbn-dconv-c3-c5_fpn_1x_coco.py | configs/gcnet/cascade-mask-rcnn_x101-32x4d-syncbn-dconv-c3-c5_fpn_1x_coco.py | _base_ = '../dcn/cascade-mask-rcnn_x101-32x4d-dconv-c3-c5_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=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/gcnet/mask-rcnn_x101-32x4d-syncbn-gcb-r4-c3-c5_fpn_1x_coco.py | configs/gcnet/mask-rcnn_x101-32x4d-syncbn-gcb-r4-c3-c5_fpn_1x_coco.py | _base_ = '../mask_rcnn/mask-rcnn_x101-32x4d_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 4),
stages=(False, True, True, True... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gcnet/cascade-mask-rcnn_x101-32x4d-syncbn-dconv-c3-c5-r16-gcb-c3-c5_fpn_1x_coco.py | configs/gcnet/cascade-mask-rcnn_x101-32x4d-syncbn-dconv-c3-c5-r16-gcb-c3-c5_fpn_1x_coco.py | _base_ = '../dcn/cascade-mask-rcnn_x101-32x4d-dconv-c3-c5_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 16),
stages=(False, T... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gcnet/cascade-mask-rcnn_x101-32x4d-syncbn_fpn_1x_coco.py | configs/gcnet/cascade-mask-rcnn_x101-32x4d-syncbn_fpn_1x_coco.py | _base_ = '../cascade_rcnn/cascade-mask-rcnn_x101-32x4d_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=False))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gcnet/mask-rcnn_r50-syncbn-gcb-r16-c3-c5_fpn_1x_coco.py | configs/gcnet/mask-rcnn_r50-syncbn-gcb-r16-c3-c5_fpn_1x_coco.py | _base_ = '../mask_rcnn/mask-rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 16),
stages=(False, True, True, True),
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gcnet/mask-rcnn_x101-32x4d-syncbn-gcb-r16-c3-c5_fpn_1x_coco.py | configs/gcnet/mask-rcnn_x101-32x4d-syncbn-gcb-r16-c3-c5_fpn_1x_coco.py | _base_ = '../mask_rcnn/mask-rcnn_x101-32x4d_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 16),
stages=(False, True, True, Tru... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gcnet/mask-rcnn_r50-syncbn-gcb-r4-c3-c5_fpn_1x_coco.py | configs/gcnet/mask-rcnn_r50-syncbn-gcb-r4-c3-c5_fpn_1x_coco.py | _base_ = '../mask_rcnn/mask-rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 4),
stages=(False, True, True, True),
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gcnet/mask-rcnn_r50-syncbn_fpn_1x_coco.py | configs/gcnet/mask-rcnn_r50-syncbn_fpn_1x_coco.py | _base_ = '../mask_rcnn/mask-rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=False))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gcnet/mask-rcnn_r101-syncbn_fpn_1x_coco.py | configs/gcnet/mask-rcnn_r101-syncbn_fpn_1x_coco.py | _base_ = '../mask_rcnn/mask-rcnn_r101_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=False))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gcnet/mask-rcnn_r101-syncbn-gcb-r4-c3-c5_fpn_1x_coco.py | configs/gcnet/mask-rcnn_r101-syncbn-gcb-r4-c3-c5_fpn_1x_coco.py | _base_ = '../mask_rcnn/mask-rcnn_r101_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 4),
stages=(False, True, True, True),
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gcnet/mask-rcnn_r50-gcb-r4-c3-c5_fpn_1x_coco.py | configs/gcnet/mask-rcnn_r50-gcb-r4-c3-c5_fpn_1x_coco.py | _base_ = '../mask_rcnn/mask-rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 4),
stages=(False, True, True, True),
position='after_conv3')
]))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gcnet/mask-rcnn_r50-gcb-r16-c3-c5_fpn_1x_coco.py | configs/gcnet/mask-rcnn_r50-gcb-r16-c3-c5_fpn_1x_coco.py | _base_ = '../mask_rcnn/mask-rcnn_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 16),
stages=(False, True, True, True),
position='after_conv3')
]))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gcnet/mask-rcnn_x101-32x4d-syncbn_fpn_1x_coco.py | configs/gcnet/mask-rcnn_x101-32x4d-syncbn_fpn_1x_coco.py | _base_ = '../mask_rcnn/mask-rcnn_x101-32x4d_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=False))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/gcnet/cascade-mask-rcnn_x101-32x4d-syncbn-dconv-c3-c5-r4-gcb-c3-c5_fpn_1x_coco.py | configs/gcnet/cascade-mask-rcnn_x101-32x4d-syncbn-dconv-c3-c5-r4-gcb-c3-c5_fpn_1x_coco.py | _base_ = '../dcn/cascade-mask-rcnn_x101-32x4d-dconv-c3-c5_fpn_1x_coco.py'
model = dict(
backbone=dict(
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
plugins=[
dict(
cfg=dict(type='ContextBlock', ratio=1. / 4),
stages=(False, Tr... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
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