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/retinanet/retinanet_r50-caffe_fpn_ms-3x_coco.py | configs/retinanet/retinanet_r50-caffe_fpn_ms-3x_coco.py | _base_ = './retinanet_r50-caffe_fpn_ms-1x_coco.py'
# training schedule for 2x
train_cfg = dict(max_epochs=36)
# learning rate policy
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
begin=0,
end=36,
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/retinanet/retinanet_r101_fpn_8xb8-amp-lsj-200e_coco.py | configs/retinanet/retinanet_r101_fpn_8xb8-amp-lsj-200e_coco.py | _base_ = './retinanet_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/retinanet/retinanet_r50-caffe_fpn_1x_coco.py | configs/retinanet/retinanet_r50-caffe_fpn_1x_coco.py | _base_ = './retinanet_r50_fpn_1x_coco.py'
model = dict(
data_preprocessor=dict(
type='DetDataPreprocessor',
# use caffe img_norm
mean=[103.530, 116.280, 123.675],
std=[1.0, 1.0, 1.0],
bgr_to_rgb=False,
pad_size_divisor=32),
backbone=dict(
norm_cfg=dict(req... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/retinanet/retinanet_r18_fpn_1xb8-1x_coco.py | configs/retinanet/retinanet_r18_fpn_1xb8-1x_coco.py | _base_ = [
'../_base_/models/retinanet_r50_fpn.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# data
train_dataloader = dict(batch_size=8)
# model
model = dict(
backbone=dict(
depth=18,
init_cfg=dict(type='Pretrained'... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/retinanet/retinanet_r50_fpn_8xb8-amp-lsj-200e_coco.py | configs/retinanet/retinanet_r50_fpn_8xb8-amp-lsj-200e_coco.py | _base_ = [
'../_base_/models/retinanet_r50_fpn.py',
'../common/lsj-200e_coco-detection.py'
]
image_size = (1024, 1024)
batch_augments = [dict(type='BatchFixedSizePad', size=image_size)]
model = dict(data_preprocessor=dict(batch_augments=batch_augments))
train_dataloader = dict(batch_size=8, 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/retinanet/retinanet_r18_fpn_1x_coco.py | configs/retinanet/retinanet_r18_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
model = dict(
backbone=dict(
depth=18,
init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet18')),
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/retinanet/retinanet_r50_fpn_90k_coco.py | configs/retinanet/retinanet_r50_fpn_90k_coco.py | _base_ = 'retinanet_r50_fpn_1x_coco.py'
# training schedule for 90k
train_cfg = dict(
_delete_=True,
type='IterBasedTrainLoop',
max_iters=90000,
val_interval=10000)
# learning rate policy
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
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/retinanet/retinanet_r101-caffe_fpn_ms-3x_coco.py | configs/retinanet/retinanet_r101-caffe_fpn_ms-3x_coco.py | _base_ = './retinanet_r50-caffe_fpn_ms-3x_coco.py'
# learning policy
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://detectron2/resnet101_caffe')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/retinanet/retinanet_r50_fpn_1x_coco.py | configs/retinanet/retinanet_r50_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',
'./retinanet_tta.py'
]
# optimizer
optim_wrapper = dict(
optimizer=dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/retinanet/retinanet_r101_fpn_2x_coco.py | configs/retinanet/retinanet_r101_fpn_2x_coco.py | _base_ = './retinanet_r50_fpn_2x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/retinanet/retinanet_x101-32x4d_fpn_2x_coco.py | configs/retinanet/retinanet_x101-32x4d_fpn_2x_coco.py | _base_ = './retinanet_r50_fpn_2x_coco.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
style='pytorch',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/retinanet/retinanet_x101-64x4d_fpn_ms-640-800-3x_coco.py | configs/retinanet/retinanet_x101-64x4d_fpn_ms-640-800-3x_coco.py | _base_ = ['../_base_/models/retinanet_r50_fpn.py', '../common/ms_3x_coco.py']
# optimizer
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
init_cfg=dict(
type='Pretrained', checkpoint='open-mmlab://resnext101_64x4d')))
optim_wrapper... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/retinanet/retinanet_x101-64x4d_fpn_2x_coco.py | configs/retinanet/retinanet_x101-64x4d_fpn_2x_coco.py | _base_ = './retinanet_r50_fpn_2x_coco.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
style='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/retinanet/retinanet_x101-64x4d_fpn_1x_coco.py | configs/retinanet/retinanet_x101-64x4d_fpn_1x_coco.py | _base_ = './retinanet_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
style='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/retinanet/retinanet_r101_fpn_ms-640-800-3x_coco.py | configs/retinanet/retinanet_r101_fpn_ms-640-800-3x_coco.py | _base_ = ['../_base_/models/retinanet_r50_fpn.py', '../common/ms_3x_coco.py']
# optimizer
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvision://resnet101')))
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/retinanet/retinanet_x101-32x4d_fpn_1x_coco.py | configs/retinanet/retinanet_x101-32x4d_fpn_1x_coco.py | _base_ = './retinanet_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),
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/retinanet/retinanet_r50_fpn_2x_coco.py | configs/retinanet/retinanet_r50_fpn_2x_coco.py | _base_ = [
'../_base_/models/retinanet_r50_fpn.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# training schedule for 2x
train_cfg = dict(max_epochs=24)
# learning rate policy
param_scheduler = [
dict(
type='LinearLR', start_... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/retinanet/retinanet_r50-caffe_fpn_ms-2x_coco.py | configs/retinanet/retinanet_r50-caffe_fpn_ms-2x_coco.py | _base_ = './retinanet_r50-caffe_fpn_ms-1x_coco.py'
# training schedule for 2x
train_cfg = dict(max_epochs=24)
# learning rate policy
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
begin=0,
end=24,
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/retinanet/retinanet_r50_fpn_amp-1x_coco.py | configs/retinanet/retinanet_r50_fpn_amp-1x_coco.py | _base_ = './retinanet_r50_fpn_1x_coco.py'
# MMEngine support the following two ways, users can choose
# according to convenience
# optim_wrapper = dict(type='AmpOptimWrapper')
_base_.optim_wrapper.type = 'AmpOptimWrapper'
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/retinanet/retinanet_r50-caffe_fpn_ms-1x_coco.py | configs/retinanet/retinanet_r50-caffe_fpn_ms-1x_coco.py | _base_ = './retinanet_r50-caffe_fpn_1x_coco.py'
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='RandomChoiceResize',
scales=[(1333, 640), (1333, 672), (1333, 704), (1333, 736),
(1333, 768), (1333, 800)],
ke... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/retinanet/retinanet_r50_fpn_ms-640-800-3x_coco.py | configs/retinanet/retinanet_r50_fpn_ms-640-800-3x_coco.py | _base_ = ['../_base_/models/retinanet_r50_fpn.py', '../common/ms_3x_coco.py']
# optimizer
optim_wrapper = dict(
optimizer=dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/retinanet/retinanet_r101-caffe_fpn_1x_coco.py | configs/retinanet/retinanet_r101-caffe_fpn_1x_coco.py | _base_ = './retinanet_r50-caffe_fpn_1x_coco.py'
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://detectron2/resnet101_caffe')))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/maskformer/maskformer_swin-l-p4-w12_64xb1-ms-300e_coco.py | configs/maskformer/maskformer_swin-l-p4-w12_64xb1-ms-300e_coco.py | _base_ = './maskformer_r50_ms-16xb1-75e_coco.py'
pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_large_patch4_window12_384_22k.pth' # noqa
depths = [2, 2, 18, 2]
model = dict(
backbone=dict(
_delete_=True,
type='SwinTransformer',
pretrain_img_size=384... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/maskformer/maskformer_r50_ms-16xb1-75e_coco.py | configs/maskformer/maskformer_r50_ms-16xb1-75e_coco.py | _base_ = [
'../_base_/datasets/coco_panoptic.py', '../_base_/default_runtime.py'
]
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=1,
pad_mask=True,
mask_pad_value=0,
pad_seg=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/efficientnet/retinanet_effb3_fpn_8xb4-crop896-1x_coco.py | configs/efficientnet/retinanet_effb3_fpn_8xb4-crop896-1x_coco.py | _base_ = [
'../_base_/models/retinanet_r50_fpn.py',
'../_base_/schedules/schedule_1x.py',
'../_base_/datasets/coco_detection.py', '../_base_/default_runtime.py'
]
image_size = (896, 896)
batch_augments = [dict(type='BatchFixedSizePad', size=image_size)]
norm_cfg = dict(type='BN', requires_grad=True)
checkp... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/ssd/ssdlite_mobilenetv2-scratch_8xb24-600e_coco.py | configs/ssd/ssdlite_mobilenetv2-scratch_8xb24-600e_coco.py | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# model settings
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=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/ssd/ssd512_coco.py | configs/ssd/ssd512_coco.py | _base_ = 'ssd300_coco.py'
# model settings
input_size = 512
model = dict(
neck=dict(
out_channels=(512, 1024, 512, 256, 256, 256, 256),
level_strides=(2, 2, 2, 2, 1),
level_paddings=(1, 1, 1, 1, 1),
last_kernel_size=4),
bbox_head=dict(
in_channels=(512, 1024, 512, 256, 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/ssd/ssd300_coco.py | configs/ssd/ssd300_coco.py | _base_ = [
'../_base_/models/ssd300.py', '../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_2x.py', '../_base_/default_runtime.py'
]
# dataset settings
input_size = 300
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/carafe/faster-rcnn_r50_fpn-carafe_1x_coco.py | configs/carafe/faster-rcnn_r50_fpn-carafe_1x_coco.py | _base_ = '../faster_rcnn/faster-rcnn_r50_fpn_1x_coco.py'
model = dict(
data_preprocessor=dict(pad_size_divisor=64),
neck=dict(
type='FPN_CARAFE',
in_channels=[256, 512, 1024, 2048],
out_channels=256,
num_outs=5,
start_level=0,
end_level=-1,
norm_cfg=None,
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/carafe/mask-rcnn_r50_fpn-carafe_1x_coco.py | configs/carafe/mask-rcnn_r50_fpn-carafe_1x_coco.py | _base_ = '../mask_rcnn/mask-rcnn_r50_fpn_1x_coco.py'
model = dict(
data_preprocessor=dict(pad_size_divisor=64),
neck=dict(
type='FPN_CARAFE',
in_channels=[256, 512, 1024, 2048],
out_channels=256,
num_outs=5,
start_level=0,
end_level=-1,
norm_cfg=None,
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/bytetrack/bytetrack_yolox_x_8xb4-amp-80e_crowdhuman-mot17halftrain_test-mot17test.py | configs/bytetrack/bytetrack_yolox_x_8xb4-amp-80e_crowdhuman-mot17halftrain_test-mot17test.py | _base_ = [
'./bytetrack/bytetrack_yolox_x_8xb4-amp-80e_crowdhuman-'
'mot17halftrain_test-mot17halfval.py'
]
test_dataloader = dict(
dataset=dict(
data_root='data/MOT17/',
ann_file='annotations/test_cocoformat.json',
data_prefix=dict(img_path='test')))
test_evaluator = 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/bytetrack/yolox_x_8xb4-amp-80e_crowdhuman-mot17halftrain_test-mot17halfval.py | configs/bytetrack/yolox_x_8xb4-amp-80e_crowdhuman-mot17halftrain_test-mot17halfval.py | _base_ = [
'../strongsort/yolox_x_8xb4-80e_crowdhuman-mot17halftrain_test-mot17halfval.py' # noqa: E501
]
# fp16 settings
optim_wrapper = dict(type='AmpOptimWrapper', loss_scale='dynamic')
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/bytetrack/bytetrack_yolox_x_8xb4-80e_crowdhuman-mot17halftrain_test-mot17halfval.py | configs/bytetrack/bytetrack_yolox_x_8xb4-80e_crowdhuman-mot17halftrain_test-mot17halfval.py | _base_ = ['../yolox/yolox_x_8xb8-300e_coco.py']
dataset_type = 'MOTChallengeDataset'
data_root = 'data/MOT17/'
img_scale = (1440, 800) # weight, height
batch_size = 4
detector = _base_.model
detector.pop('data_preprocessor')
detector.bbox_head.update(dict(num_classes=1))
detector.test_cfg.nms.update(dict(iou_thresh... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/bytetrack/bytetrack_yolox_x_8xb4-amp-80e_crowdhuman-mot20train_test-mot20test.py | configs/bytetrack/bytetrack_yolox_x_8xb4-amp-80e_crowdhuman-mot20train_test-mot20test.py | _base_ = [
'./bytetrack_yolox_x_8xb4-80e_crowdhuman-mot20train_test-mot20test.py'
]
# fp16 settings
optim_wrapper = dict(type='AmpOptimWrapper', loss_scale='dynamic')
val_cfg = dict(type='ValLoop', fp16=True)
test_cfg = dict(type='TestLoop', fp16=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/bytetrack/bytetrack_yolox_x_8xb4-80e_crowdhuman-mot20train_test-mot20test.py | configs/bytetrack/bytetrack_yolox_x_8xb4-80e_crowdhuman-mot20train_test-mot20test.py | _base_ = [
'./bytetrack_yolox_x_8xb4-80e_crowdhuman-mot17halftrain_'
'test-mot17halfval.py'
]
dataset_type = 'MOTChallengeDataset'
img_scale = (1600, 896) # weight, height
model = dict(
data_preprocessor=dict(
type='TrackDataPreprocessor',
use_det_processor=True,
pad_size_divisor... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/bytetrack/bytetrack_yolox_x_8xb4-amp-80e_crowdhuman-mot17halftrain_test-mot17halfval.py | configs/bytetrack/bytetrack_yolox_x_8xb4-amp-80e_crowdhuman-mot17halftrain_test-mot17halfval.py | _base_ = [
'./bytetrack_yolox_x_8xb4-80e_crowdhuman-mot17halftrain_'
'test-mot17halfval.py'
]
# fp16 settings
optim_wrapper = dict(type='AmpOptimWrapper', loss_scale='dynamic')
val_cfg = dict(type='ValLoop', fp16=True)
test_cfg = dict(type='TestLoop', fp16=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/tridentnet/tridentnet_r50-caffe_1x_coco.py | configs/tridentnet/tridentnet_r50-caffe_1x_coco.py | _base_ = [
'../_base_/models/faster-rcnn_r50-caffe-c4.py',
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
type='TridentFasterRCNN',
backbone=dict(
type='TridentResNet',
trident_dilations=(1, 2, 3),
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/tridentnet/tridentnet_r50-caffe_ms-1x_coco.py | configs/tridentnet/tridentnet_r50-caffe_ms-1x_coco.py | _base_ = 'tridentnet_r50-caffe_1x_coco.py'
train_pipeline = [
dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='RandomChoiceResize',
scales=[(1333, 640), (1333, 672), (1333, 704), (1333, 736),
(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/tridentnet/tridentnet_r50-caffe_ms-3x_coco.py | configs/tridentnet/tridentnet_r50-caffe_ms-3x_coco.py | _base_ = 'tridentnet_r50-caffe_ms-1x_coco.py'
# learning rate
max_epochs = 36
train_cfg = dict(
type='EpochBasedTrainLoop', max_epochs=max_epochs, val_interval=1)
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/cascade_rpn/cascade-rpn_faster-rcnn_r50-caffe_fpn_1x_coco.py | configs/cascade_rpn/cascade-rpn_faster-rcnn_r50-caffe_fpn_1x_coco.py | _base_ = '../faster_rcnn/faster-rcnn_r50-caffe_fpn_1x_coco.py'
rpn_weight = 0.7
model = dict(
rpn_head=dict(
_delete_=True,
type='CascadeRPNHead',
num_stages=2,
stages=[
dict(
type='StageCascadeRPNHead',
in_channels=256,
fea... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/cascade_rpn/cascade-rpn_r50-caffe_fpn_1x_coco.py | configs/cascade_rpn/cascade-rpn_r50-caffe_fpn_1x_coco.py | _base_ = '../rpn/rpn_r50-caffe_fpn_1x_coco.py'
model = dict(
rpn_head=dict(
_delete_=True,
type='CascadeRPNHead',
num_stages=2,
stages=[
dict(
type='StageCascadeRPNHead',
in_channels=256,
feat_channels=256,
a... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/cascade_rpn/cascade-rpn_fast-rcnn_r50-caffe_fpn_1x_coco.py | configs/cascade_rpn/cascade-rpn_fast-rcnn_r50-caffe_fpn_1x_coco.py | _base_ = '../fast_rcnn/fast-rcnn_r50-caffe_fpn_1x_coco.py'
model = dict(
roi_head=dict(
bbox_head=dict(
bbox_coder=dict(target_stds=[0.04, 0.04, 0.08, 0.08]),
loss_cls=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.5),
loss_bbox=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/reid/reid_r50_8xb32-6e_mot16train80_test-mot16val20.py | configs/reid/reid_r50_8xb32-6e_mot16train80_test-mot16val20.py | _base_ = ['./reid_r50_8xb32-6e_mot17train80_test-mot17val20.py']
model = dict(head=dict(num_classes=371))
# data
data_root = 'data/MOT16/'
train_dataloader = dict(dataset=dict(data_root=data_root))
val_dataloader = dict(dataset=dict(data_root=data_root))
test_dataloader = val_dataloader
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/reid/reid_r50_8xb32-6e_mot20train80_test-mot20val20.py | configs/reid/reid_r50_8xb32-6e_mot20train80_test-mot20val20.py | _base_ = ['./reid_r50_8xb32-6e_mot17train80_test-mot17val20.py']
model = dict(head=dict(num_classes=1701))
# data
data_root = 'data/MOT20/'
train_dataloader = dict(dataset=dict(data_root=data_root))
val_dataloader = dict(dataset=dict(data_root=data_root))
test_dataloader = val_dataloader
# train, val, test setting
tra... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/reid/reid_r50_8xb32-6e_mot15train80_test-mot15val20.py | configs/reid/reid_r50_8xb32-6e_mot15train80_test-mot15val20.py | _base_ = ['./reid_r50_8xb32-6e_mot17train80_test-mot17val20.py']
model = dict(head=dict(num_classes=368))
# data
data_root = 'data/MOT15/'
train_dataloader = dict(dataset=dict(data_root=data_root))
val_dataloader = dict(dataset=dict(data_root=data_root))
test_dataloader = val_dataloader
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/reid/reid_r50_8xb32-6e_mot17train80_test-mot17val20.py | configs/reid/reid_r50_8xb32-6e_mot17train80_test-mot17val20.py | _base_ = [
'../_base_/datasets/mot_challenge_reid.py', '../_base_/default_runtime.py'
]
model = dict(
type='BaseReID',
data_preprocessor=dict(
type='ReIDDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
backbone=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/fsaf/fsaf_r101_fpn_1x_coco.py | configs/fsaf/fsaf_r101_fpn_1x_coco.py | _base_ = './fsaf_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/fsaf/fsaf_r50_fpn_1x_coco.py | configs/fsaf/fsaf_r50_fpn_1x_coco.py | _base_ = '../retinanet/retinanet_r50_fpn_1x_coco.py'
# model settings
model = dict(
type='FSAF',
bbox_head=dict(
type='FSAFHead',
num_classes=80,
in_channels=256,
stacked_convs=4,
feat_channels=256,
reg_decoded_bbox=True,
# Only anchor-free branch is imple... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/fsaf/fsaf_x101-64x4d_fpn_1x_coco.py | configs/fsaf/fsaf_x101-64x4d_fpn_1x_coco.py | _base_ = './fsaf_r50_fpn_1x_coco.py'
model = dict(
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
style='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/seesaw_loss/mask-rcnn_r50_fpn_seesaw-loss_sample1e-3-ms-2x_lvis-v1.py | configs/seesaw_loss/mask-rcnn_r50_fpn_seesaw-loss_sample1e-3-ms-2x_lvis-v1.py | _base_ = [
'../_base_/models/mask-rcnn_r50_fpn.py',
'../_base_/datasets/lvis_v1_instance.py',
'../_base_/schedules/schedule_2x.py', '../_base_/default_runtime.py'
]
model = dict(
roi_head=dict(
bbox_head=dict(
num_classes=1203,
cls_predictor_cfg=dict(type='NormedLinear', ... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/seesaw_loss/mask-rcnn_r50_fpn_seesaw-loss_random-ms-2x_lvis-v1.py | configs/seesaw_loss/mask-rcnn_r50_fpn_seesaw-loss_random-ms-2x_lvis-v1.py | _base_ = [
'../_base_/models/mask-rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_2x.py', '../_base_/default_runtime.py'
]
model = dict(
roi_head=dict(
bbox_head=dict(
num_classes=1203,
cls_predictor_cfg=dict(type='NormedLinear', tem... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/seesaw_loss/cascade-mask-rcnn_r101_fpn_seesaw-loss-normed-mask_random-ms-2x_lvis-v1.py | configs/seesaw_loss/cascade-mask-rcnn_r101_fpn_seesaw-loss-normed-mask_random-ms-2x_lvis-v1.py | _base_ = './cascade-mask-rcnn_r101_fpn_seesaw-loss_random-ms-2x_lvis-v1.py' # noqa: E501
model = dict(
roi_head=dict(
mask_head=dict(
predictor_cfg=dict(type='NormedConv2d', tempearture=20))))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/seesaw_loss/mask-rcnn_r101_fpn_seesaw-loss-normed-mask_random-ms-2x_lvis-v1.py | configs/seesaw_loss/mask-rcnn_r101_fpn_seesaw-loss-normed-mask_random-ms-2x_lvis-v1.py | _base_ = './mask-rcnn_r50_fpn_seesaw-loss-normed-mask_random-ms-2x_lvis-v1.py' # noqa: E501
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/seesaw_loss/mask-rcnn_r50_fpn_seesaw-loss-normed-mask_random-ms-2x_lvis-v1.py | configs/seesaw_loss/mask-rcnn_r50_fpn_seesaw-loss-normed-mask_random-ms-2x_lvis-v1.py | _base_ = './mask-rcnn_r50_fpn_seesaw-loss_random-ms-2x_lvis-v1.py'
model = dict(
roi_head=dict(
mask_head=dict(
predictor_cfg=dict(type='NormedConv2d', tempearture=20))))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/seesaw_loss/cascade-mask-rcnn_r101_fpn_seesaw-loss-normed-mask_sample1e-3-ms-2x_lvis-v1.py | configs/seesaw_loss/cascade-mask-rcnn_r101_fpn_seesaw-loss-normed-mask_sample1e-3-ms-2x_lvis-v1.py | _base_ = './cascade-mask-rcnn_r101_fpn_seesaw-loss_sample1e-3-ms-2x_lvis-v1.py' # noqa: E501
model = dict(
roi_head=dict(
mask_head=dict(
predictor_cfg=dict(type='NormedConv2d', tempearture=20))))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/seesaw_loss/mask-rcnn_r50_fpn_seesaw-loss-normed-mask_sample1e-3-ms-2x_lvis-v1.py | configs/seesaw_loss/mask-rcnn_r50_fpn_seesaw-loss-normed-mask_sample1e-3-ms-2x_lvis-v1.py | _base_ = './mask-rcnn_r50_fpn_seesaw-loss_sample1e-3-ms-2x_lvis-v1.py'
model = dict(
roi_head=dict(
mask_head=dict(
predictor_cfg=dict(type='NormedConv2d', tempearture=20))))
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/seesaw_loss/mask-rcnn_r101_fpn_seesaw-loss_sample1e-3-ms-2x_lvis-v1.py | configs/seesaw_loss/mask-rcnn_r101_fpn_seesaw-loss_sample1e-3-ms-2x_lvis-v1.py | _base_ = './mask-rcnn_r50_fpn_seesaw-loss_sample1e-3-ms-2x_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/seesaw_loss/cascade-mask-rcnn_r101_fpn_seesaw-loss_random-ms-2x_lvis-v1.py | configs/seesaw_loss/cascade-mask-rcnn_r101_fpn_seesaw-loss_random-ms-2x_lvis-v1.py | _base_ = [
'../_base_/models/cascade-mask-rcnn_r50_fpn.py',
'../_base_/datasets/coco_instance.py',
'../_base_/schedules/schedule_2x.py', '../_base_/default_runtime.py'
]
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvisio... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/seesaw_loss/mask-rcnn_r101_fpn_seesaw-loss-normed-mask_sample1e-3-ms-2x_lvis-v1.py | configs/seesaw_loss/mask-rcnn_r101_fpn_seesaw-loss-normed-mask_sample1e-3-ms-2x_lvis-v1.py | _base_ = './mask-rcnn_r50_fpn_seesaw-loss-normed-mask_sample1e-3-ms-2x_lvis-v1.py' # noqa: E501
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/seesaw_loss/cascade-mask-rcnn_r101_fpn_seesaw-loss_sample1e-3-ms-2x_lvis-v1.py | configs/seesaw_loss/cascade-mask-rcnn_r101_fpn_seesaw-loss_sample1e-3-ms-2x_lvis-v1.py | _base_ = [
'../_base_/models/cascade-mask-rcnn_r50_fpn.py',
'../_base_/datasets/lvis_v1_instance.py',
'../_base_/schedules/schedule_2x.py', '../_base_/default_runtime.py'
]
model = dict(
backbone=dict(
depth=101,
init_cfg=dict(type='Pretrained',
checkpoint='torchvi... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/configs/seesaw_loss/mask-rcnn_r101_fpn_seesaw-loss_random-ms-2x_lvis-v1.py | configs/seesaw_loss/mask-rcnn_r101_fpn_seesaw-loss_random-ms-2x_lvis-v1.py | _base_ = './mask-rcnn_r50_fpn_seesaw-loss_random-ms-2x_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/projects/example_largemodel/dino-5scale_swin-l_deepspeed_8xb2-12e_coco.py | projects/example_largemodel/dino-5scale_swin-l_deepspeed_8xb2-12e_coco.py | from mmengine.config import read_base
with read_base():
from mmdet.configs.dino.dino_5scale_swin_l_8xb2_12e_coco import * # noqa
model.update(dict(encoder=dict(num_cp=6))) # noqa
runner_type = 'FlexibleRunner'
strategy = dict(
type='DeepSpeedStrategy',
gradient_clipping=0.1,
fp16=dict(
enab... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/example_largemodel/__init__.py | projects/example_largemodel/__init__.py | from .fsdp_utils import checkpoint_check_fn, layer_auto_wrap_policy
__all__ = ['checkpoint_check_fn', 'layer_auto_wrap_policy']
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/example_largemodel/dino-5scale_swin-l_fsdp_8xb2-12e_coco.py | projects/example_largemodel/dino-5scale_swin-l_fsdp_8xb2-12e_coco.py | from mmengine.config import read_base
with read_base():
from mmdet.configs.dino.dino_5scale_swin_l_8xb2_12e_coco import * # noqa
from projects.example_largemodel import (checkpoint_check_fn,
layer_auto_wrap_policy)
# The checkpoint needs to be controlled by the checkpoin... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/example_largemodel/fsdp_utils.py | projects/example_largemodel/fsdp_utils.py | from typing import Sequence, Union
import torch.nn as nn
from mmdet.models.backbones.swin import SwinBlock
from mmdet.models.layers.transformer.deformable_detr_layers import \
DeformableDetrTransformerEncoderLayer
# TODO: The new version of configs does not support passing a module list,
# so for now, it can o... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/ConvNeXt-V2/configs/mask-rcnn_convnext-v2-b_fpn_lsj-3x-fcmae_coco.py | projects/ConvNeXt-V2/configs/mask-rcnn_convnext-v2-b_fpn_lsj-3x-fcmae_coco.py | _base_ = [
'mmdet::_base_/models/mask-rcnn_r50_fpn.py',
'mmdet::_base_/datasets/coco_instance.py',
'mmdet::_base_/schedules/schedule_1x.py',
'mmdet::_base_/default_runtime.py'
]
# please install the mmpretrain
# import mmpretrain.models to trigger register_module in mmpretrain
custom_imports = dict(
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/AlignDETR/align_detr/align_detr_head.py | projects/AlignDETR/align_detr/align_detr_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Any, Dict, List, Tuple, Union
import torch
from mmengine.structures import InstanceData
from torch import Tensor
from mmdet.models.dense_heads import DINOHead
from mmdet.registry import MODELS
from mmdet.structures.bbox import (bbox_cxcywh_to_xyxy, bb... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/AlignDETR/align_detr/mixed_hungarian_assigner.py | projects/AlignDETR/align_detr/mixed_hungarian_assigner.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Optional, Union
import torch
from mmengine import ConfigDict
from mmengine.structures import InstanceData
from scipy.optimize import linear_sum_assignment
from torch import Tensor
from mmdet.models.task_modules import AssignResult, BaseAssigner
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/AlignDETR/align_detr/utils.py | projects/AlignDETR/align_detr/utils.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Any, List, Optional
class KeysRecorder:
"""Wrap object to record its `__getitem__` keys in the history.
Args:
obj (object): Any object that supports `__getitem__`.
keys (List): List of keys already recorded. Default to None.
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/AlignDETR/align_detr/__init__.py | projects/AlignDETR/align_detr/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .align_detr_head import AlignDETRHead
from .mixed_hungarian_assigner import MixedHungarianAssigner
__all__ = ['AlignDETRHead', 'MixedHungarianAssigner']
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/AlignDETR/configs/align_detr-4scale_r50_8xb2-24e_coco.py | projects/AlignDETR/configs/align_detr-4scale_r50_8xb2-24e_coco.py | _base_ = './align_detr-4scale_r50_8xb2-12e_coco.py'
max_epochs = 24
train_cfg = dict(
type='EpochBasedTrainLoop', max_epochs=max_epochs, val_interval=1)
param_scheduler = [
dict(
type='LinearLR',
start_factor=0.0001,
by_epoch=False,
begin=0,
end=2000),
dict(
t... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/AlignDETR/configs/align_detr-4scale_r50_8xb2-12e_coco.py | projects/AlignDETR/configs/align_detr-4scale_r50_8xb2-12e_coco.py | _base_ = [
'../../../configs/_base_/datasets/coco_detection.py',
'../../../configs/_base_/default_runtime.py'
]
custom_imports = dict(
imports=['projects.AlignDETR.align_detr'], allow_failed_imports=False)
model = dict(
type='DINO',
num_queries=900, # num_matching_queries
with_box_refine=True,... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/detic/centernet_rpn_head.py | projects/Detic_new/detic/centernet_rpn_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
from typing import Dict, List, Optional, Sequence, Tuple
import torch
import torch.nn as nn
from mmcv.cnn import Scale
from mmengine import ConfigDict
from mmengine.structures import InstanceData
from torch import Tensor
from mmdet.models.dense_heads import ... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/detic/detic_roi_head.py | projects/Detic_new/detic/detic_roi_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Sequence, Tuple
import torch
from mmengine.structures import InstanceData
from torch import Tensor
from mmdet.models.roi_heads import CascadeRoIHead
from mmdet.models.task_modules.samplers import SamplingResult
from mmdet.models.test_time_augs i... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/detic/imagenet_lvis.py | projects/Detic_new/detic/imagenet_lvis.py | # Copyright (c) OpenMMLab. All rights reserved.METAINFO
import copy
import os.path as osp
import pickle
import warnings
from typing import List, Union
from mmengine.fileio import get_local_path
from mmdet.datasets import LVISV1Dataset
from mmdet.registry import DATASETS
@DATASETS.register_module()
class ImageNetLVI... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/detic/detic.py | projects/Detic_new/detic/detic.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
from typing import List, Union
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmengine.logging import print_log
from torch import Tensor
from mmdet.datasets import LVISV1Dataset
from mmdet.models.detectors.cascade_... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/detic/zero_shot_classifier.py | projects/Detic_new/detic/zero_shot_classifier.py | # Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
import torch
from torch import nn
from torch.nn import functional as F
from mmdet.registry import MODELS
@MODELS.register_module()
class ZeroShotClassifier(nn.Module):
def __init__(
self,
in_features: int,
out_features... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/detic/__init__.py | projects/Detic_new/detic/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .centernet_rpn_head import CenterNetRPNHead
from .detic import Detic
from .detic_bbox_head import DeticBBoxHead
from .detic_roi_head import DeticRoIHead
from .heatmap_focal_loss import HeatmapFocalLoss
from .imagenet_lvis import ImageNetLVISV1Dataset
from .zero_shot_... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/detic/detic_bbox_head.py | projects/Detic_new/detic/detic_bbox_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import json
from typing import List, Optional
import torch
from mmengine.config import ConfigDict
from mmengine.structures import InstanceData
from torch import Tensor
from torch.nn import functional as F
from mmdet.models.layers import multiclass_nms
from mmdet.models.... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/detic/heatmap_focal_loss.py | projects/Detic_new/detic/heatmap_focal_loss.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Optional, Union
import torch
import torch.nn as nn
from torch import Tensor
from mmdet.registry import MODELS
# support class-agnostic heatmap_focal_loss
def heatmap_focal_loss_with_pos_inds(
pred: Tensor,
targets: Tensor,
po... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/detic/iou_loss.py | projects/Detic_new/detic/iou_loss.py | import torch
from torch import nn
# support calculate IOULoss with box_pred
class IOULoss(nn.Module):
def __init__(self, loc_loss_type='iou'):
super(IOULoss, self).__init__()
self.loc_loss_type = loc_loss_type
def forward(self, pred, target, weight=None, reduction='sum'):
pred_left ... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/configs/detic_centernet2_r50_fpn_4x_lvis-base_boxsup.py | projects/Detic_new/configs/detic_centernet2_r50_fpn_4x_lvis-base_boxsup.py | _base_ = './detic_centernet2_r50_fpn_4x_lvis_boxsup.py'
# 'lvis_v1_train_norare.json' is the annotations of lvis_v1
# removing the labels of 337 rare-class
train_dataloader = dict(
dataset=dict(
type='ClassBalancedDataset',
oversample_thr=1e-3,
dataset=dict(ann_file='annotations/lvis_v1_tra... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/configs/detic_centernet2_r50_fpn_4x_lvis-base_in21k-lvis.py | projects/Detic_new/configs/detic_centernet2_r50_fpn_4x_lvis-base_in21k-lvis.py | _base_ = './detic_centernet2_r50_fpn_4x_lvis_boxsup.py'
dataset_type = ['LVISV1Dataset', 'ImageNetLVISV1Dataset']
image_size_det = (640, 640)
image_size_cls = (320, 320)
# backend = 'pillow'
backend_args = None
train_pipeline_det = [
dict(type='LoadImageFromFile', backend_args=backend_args),
dict(type='LoadAn... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/configs/detic_centernet2_swin-b_fpn_4x_lvis_boxsup.py | projects/Detic_new/configs/detic_centernet2_swin-b_fpn_4x_lvis_boxsup.py | _base_ = './detic_centernet2_r50_fpn_4x_lvis_boxsup.py'
model = dict(
backbone=dict(
_delete_=True,
type='SwinTransformer',
embed_dims=128,
depths=[2, 2, 18, 2],
num_heads=[4, 8, 16, 32],
window_size=7,
mlp_ratio=4,
qkv_bias=True,
qk_scale=Non... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/configs/detic_centernet2_swin-b_fpn_4x_lvis-base_in21k-lvis.py | projects/Detic_new/configs/detic_centernet2_swin-b_fpn_4x_lvis-base_in21k-lvis.py | _base_ = './detic_centernet2_r50_fpn_4x_lvis_in21k-lvis.py'
image_size_det = (896, 896)
image_size_cls = (448, 448)
model = dict(
backbone=dict(
_delete_=True,
type='SwinTransformer',
embed_dims=128,
depths=[2, 2, 18, 2],
num_heads=[4, 8, 16, 32],
window_size=7,
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/configs/detic_centernet2_r50_fpn_4x_lvis_in21k-lvis.py | projects/Detic_new/configs/detic_centernet2_r50_fpn_4x_lvis_in21k-lvis.py | _base_ = './detic_centernet2_r50_fpn_4x_lvis_boxsup.py'
dataset_type = ['LVISV1Dataset', 'ImageNetLVISV1Dataset']
image_size_det = (640, 640)
image_size_cls = (320, 320)
# backend = 'pillow'
backend_args = None
train_pipeline_det = [
dict(type='LoadImageFromFile', backend_args=backend_args),
dict(type='LoadAn... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/configs/detic_centernet2_swin-b_fpn_4x_lvis-base_boxsup.py | projects/Detic_new/configs/detic_centernet2_swin-b_fpn_4x_lvis-base_boxsup.py | _base_ = './detic_centernet2_swin-b_fpn_4x_lvis_boxsup.py'
# 'lvis_v1_train_norare.json' is the annotations of lvis_v1
# removing the labels of 337 rare-class
train_dataloader = dict(
dataset=dict(
type='ClassBalancedDataset',
oversample_thr=1e-3,
dataset=dict(ann_file='annotations/lvis_v1_... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/configs/detic_centernet2_swin-b_fpn_4x_lvis_coco_in21k.py | projects/Detic_new/configs/detic_centernet2_swin-b_fpn_4x_lvis_coco_in21k.py | # not support training, only for testing
_base_ = './detic_centernet2_swin-b_fpn_4x_lvis_in21k-lvis.py'
| python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/configs/detic_centernet2_r50_fpn_4x_lvis_boxsup.py | projects/Detic_new/configs/detic_centernet2_r50_fpn_4x_lvis_boxsup.py | _base_ = 'mmdet::_base_/default_runtime.py'
dataset_type = 'LVISV1Dataset'
custom_imports = dict(
imports=['projects.Detic_new.detic'], allow_failed_imports=False)
num_classes = 1203
lvis_cat_frequency_info = 'data/metadata/lvis_v1_train_cat_info.json'
# 'data/metadata/lvis_v1_clip_a+cname.npy' is pre-computed
# ... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic_new/configs/detic_centernet2_swin-b_fpn_4x_lvis_in21k-lvis.py | projects/Detic_new/configs/detic_centernet2_swin-b_fpn_4x_lvis_in21k-lvis.py | _base_ = './detic_centernet2_r50_fpn_4x_lvis_in21k-lvis.py'
image_size_det = (896, 896)
image_size_cls = (448, 448)
model = dict(
backbone=dict(
_delete_=True,
type='SwinTransformer',
embed_dims=128,
depths=[2, 2, 18, 2],
num_heads=[4, 8, 16, 32],
window_size=7,
... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic/demo.py | projects/Detic/demo.py | # Copyright (c) OpenMMLab. All rights reserved.
import os
import urllib
from argparse import ArgumentParser
import mmcv
import torch
from mmengine.logging import print_log
from mmengine.utils import ProgressBar, scandir
from mmdet.apis import inference_detector, init_detector
from mmdet.registry import VISUALIZERS
fr... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic/detic/centernet_rpn_head.py | projects/Detic/detic/centernet_rpn_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
from typing import List, Sequence, Tuple
import torch
import torch.nn as nn
from mmcv.cnn import Scale
from mmengine import ConfigDict
from mmengine.structures import InstanceData
from torch import Tensor
from mmdet.models.dense_heads import CenterNetUpdateH... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic/detic/detic_roi_head.py | projects/Detic/detic/detic_roi_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Sequence, Tuple
import torch
from mmengine.structures import InstanceData
from torch import Tensor
from mmdet.models.roi_heads import CascadeRoIHead
from mmdet.models.task_modules.samplers import SamplingResult
from mmdet.models.test_time_augs i... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic/detic/utils.py | projects/Detic/detic/utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
import torch.nn.functional as F
from mmengine.logging import print_log
from .text_encoder import CLIPTextEncoder
# download from
# https://github.com/facebookresearch/Detic/tree/main/datasets/metadata
DATASET_EMBEDDINGS = {
'lvis': 'd... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic/detic/zero_shot_classifier.py | projects/Detic/detic/zero_shot_classifier.py | # Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
import torch
from torch import nn
from torch.nn import functional as F
from mmdet.registry import MODELS
@MODELS.register_module(force=True) # avoid bug
class ZeroShotClassifier(nn.Module):
def __init__(
self,
in_features: in... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic/detic/__init__.py | projects/Detic/detic/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .centernet_rpn_head import CenterNetRPNHead
from .detic_bbox_head import DeticBBoxHead
from .detic_roi_head import DeticRoIHead
from .zero_shot_classifier import ZeroShotClassifier
__all__ = [
'CenterNetRPNHead', 'DeticBBoxHead', 'DeticRoIHead', 'ZeroShotClassif... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic/detic/detic_bbox_head.py | projects/Detic/detic/detic_bbox_head.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Optional, Union
from mmengine.config import ConfigDict
from mmengine.structures import InstanceData
from torch import Tensor
from mmdet.models.layers import multiclass_nms
from mmdet.models.roi_heads.bbox_heads import Shared2FCBBoxHead
from mmdet.mode... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic/detic/text_encoder.py | projects/Detic/detic/text_encoder.py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Union
import torch
import torch.nn as nn
class CLIPTextEncoder(nn.Module):
def __init__(self, model_name='ViT-B/32'):
super().__init__()
import clip
from clip.simple_tokenizer import SimpleTokenizer
self.tok... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/Detic/configs/detic_centernet2_swin-b_fpn_4x_lvis-coco-in21k.py | projects/Detic/configs/detic_centernet2_swin-b_fpn_4x_lvis-coco-in21k.py | _base_ = 'mmdet::common/lsj-200e_coco-detection.py'
custom_imports = dict(
imports=['projects.Detic.detic'], allow_failed_imports=False)
image_size = (1024, 1024)
batch_augments = [dict(type='BatchFixedSizePad', size=image_size)]
cls_layer = dict(
type='ZeroShotClassifier',
zs_weight_path='rand',
zs_... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
open-mmlab/mmdetection | https://github.com/open-mmlab/mmdetection/blob/cfd5d3a985b0249de009b67d04f37263e11cdf3d/projects/gradio_demo/launch.py | projects/gradio_demo/launch.py | # Modified from MMPretrain
import gradio as gr
import torch
from mmengine.logging import MMLogger
from mmdet.apis import DetInferencer
from projects.XDecoder.xdecoder.inference import (
ImageCaptionInferencer, RefImageCaptionInferencer,
TextToImageRegionRetrievalInferencer)
logger = MMLogger('mmdetection', lo... | python | Apache-2.0 | cfd5d3a985b0249de009b67d04f37263e11cdf3d | 2026-01-04T14:42:57.197037Z | false |
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