python_code stringlengths 0 992k | repo_name stringlengths 8 46 | file_path stringlengths 5 162 |
|---|---|---|
import glob
import os
import os.path as osp
import mmcv
import torch.nn as nn
from mmaction.models import build_localizer, build_recognizer
def _get_config_path():
"""Find the predefined recognizer config path."""
repo_dir = osp.dirname(osp.dirname(osp.dirname(__file__)))
config_dpath = osp.join(repo_di... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_runtime/test_config.py |
# Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... | InternVideo-main | Downstream/Open-Set-Action-Recognition/docs/conf.py |
#!/usr/bin/env python
import functools as func
import glob
import re
files = sorted(glob.glob('*_models.md'))
stats = []
for f in files:
with open(f, 'r') as content_file:
content = content_file.read()
# title
title = content.split('\n')[0].replace('#', '')
# count papers
papers = set(x... | InternVideo-main | Downstream/Open-Set-Action-Recognition/docs/stat.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTIN',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
shift_div=4),
cls_head=dict(
type='TSMHead',
num_classes=174,
in_channels=2048,
spatial... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tin/tin_r50_1x1x8_40e_sthv1_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTIN',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
shift_div=4),
cls_head=dict(
type='TSMHead',
num_classes=400,
in_channels=2048,
spatial... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tin/tin_tsm_finetune_r50_1x1x8_50e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTIN',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
shift_div=4),
cls_head=dict(
type='TSMHead',
num_classes=174,
in_channels=2048,
spatial... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tin/tin_r50_1x1x8_40e_sthv2_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNet',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False),
cls_head=dict(
type='TSNHead',
num_classes=200,
in_channels=2048,
spatial_type='avg',
con... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/omnisource/tsn_r50_1x1x8_100e_minikinetics/tsn_r50_1x1x8_100e_minikinetics_webimage_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNet',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False),
cls_head=dict(
type='TSNHead',
num_classes=200,
in_channels=2048,
spatial_type='avg',
con... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/omnisource/tsn_r50_1x1x8_100e_minikinetics/tsn_r50_1x1x8_100e_minikinetics_kineticsraw_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNet',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False),
cls_head=dict(
type='TSNHead',
num_classes=200,
in_channels=2048,
spatial_type='avg',
con... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/omnisource/tsn_r50_1x1x8_100e_minikinetics/tsn_r50_1x1x8_100e_minikinetics_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNet',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False),
cls_head=dict(
type='TSNHead',
num_classes=200,
in_channels=2048,
spatial_type='avg',
con... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/omnisource/tsn_r50_1x1x8_100e_minikinetics/tsn_r50_1x1x8_100e_minikinetics_googleimage_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNet',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False),
cls_head=dict(
type='TSNHead',
num_classes=200,
in_channels=2048,
spatial_type='avg',
con... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/omnisource/tsn_r50_1x1x8_100e_minikinetics/tsn_r50_1x1x8_100e_minikinetics_omnisource_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNet',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False),
cls_head=dict(
type='TSNHead',
num_classes=200,
in_channels=2048,
spatial_type='avg',
con... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/omnisource/tsn_r50_1x1x8_100e_minikinetics/tsn_r50_1x1x8_100e_minikinetics_insvideo_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowOnly',
depth=50,
pretrained=None,
lateral=False,
conv1_kernel=(1, 7, 7),
conv1_stride_t=1,
pool1_stride_t=1,
inflate=(0, 0, 1, 1),
norm_eval=False),
cl... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/omnisource/slowonly_r50_8x8x1_256e_minikinetics/slowonly_r50_8x8x1_256e_minikinetics_insvideo_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowOnly',
depth=50,
pretrained=None,
lateral=False,
conv1_kernel=(1, 7, 7),
conv1_stride_t=1,
pool1_stride_t=1,
inflate=(0, 0, 1, 1),
norm_eval=False),
cl... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/omnisource/slowonly_r50_8x8x1_256e_minikinetics/slowonly_r50_8x8x1_256e_minikinetics_kineticsraw_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowOnly',
depth=50,
pretrained=None,
lateral=False,
conv1_kernel=(1, 7, 7),
conv1_stride_t=1,
pool1_stride_t=1,
inflate=(0, 0, 1, 1),
norm_eval=False),
cl... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/omnisource/slowonly_r50_8x8x1_256e_minikinetics/slowonly_r50_8x8x1_256e_minikinetics_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowOnly',
depth=50,
pretrained=None,
lateral=False,
conv1_kernel=(1, 7, 7),
conv1_stride_t=1,
pool1_stride_t=1,
inflate=(0, 0, 1, 1),
norm_eval=False),
cl... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/omnisource/slowonly_r50_8x8x1_256e_minikinetics/slowonly_r50_8x8x1_256e_minikinetics_googleimage_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowOnly',
depth=50,
pretrained=None,
lateral=False,
conv1_kernel=(1, 7, 7),
conv1_stride_t=1,
pool1_stride_t=1,
inflate=(0, 0, 1, 1),
norm_eval=False),
cl... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/omnisource/slowonly_r50_8x8x1_256e_minikinetics/slowonly_r50_8x8x1_256e_minikinetics_webimage_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowOnly',
depth=50,
pretrained=None,
lateral=False,
conv1_kernel=(1, 7, 7),
conv1_stride_t=1,
pool1_stride_t=1,
inflate=(0, 0, 1, 1),
norm_eval=False),
cl... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/omnisource/slowonly_r50_8x8x1_256e_minikinetics/slowonly_r50_8x8x1_256e_minikinetics_omnisource_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet2Plus1d',
depth=34,
pretrained=None,
pretrained2d=False,
norm_eval=False,
conv_cfg=dict(type='Conv2plus1d'),
norm_cfg=dict(type='SyncBN', requires_grad=True, eps=1e-3),
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/r2plus1d/r2plus1d_r34_32x2x1_180e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet2Plus1d',
depth=34,
pretrained=None,
pretrained2d=False,
norm_eval=False,
conv_cfg=dict(type='Conv2plus1d'),
norm_cfg=dict(type='SyncBN', requires_grad=True, eps=1e-3),
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/r2plus1d/r2plus1d_r34_8x8x1_180e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet2Plus1d',
depth=34,
pretrained=None,
pretrained2d=False,
norm_eval=False,
conv_cfg=dict(type='Conv2plus1d'),
norm_cfg=dict(type='SyncBN', requires_grad=True, eps=1e-3),
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/r2plus1d/r2plus1d_r34_video_8x8x1_180e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet2Plus1d',
depth=34,
pretrained=None,
pretrained2d=False,
norm_eval=False,
conv_cfg=dict(type='Conv2plus1d'),
norm_cfg=dict(type='SyncBN', requires_grad=True, eps=1e-3),
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/r2plus1d/r2plus1d_r34_video_inference_8x8x1_180e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dCSN',
pretrained2d=False,
pretrained= # noqa: E251
'https://download.openmmlab.com/mmaction/recognition/csn/ircsn_from_scratch_r152_ig65m_20200807-771c4135.pth', # noqa: E501
depth=152,
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/csn/ircsn_ig65m_pretrained_r152_32x2x1_58e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dCSN',
pretrained2d=False,
pretrained= # noqa: E251
'https://download.openmmlab.com/mmaction/recognition/csn/ircsn_from_scratch_r152_ig65m_20200807-771c4135.pth', # noqa: E501
depth=152,
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/csn/finetune_ucf101_csn_dnn.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dCSN',
pretrained2d=False,
pretrained= # noqa: E251
'https://download.openmmlab.com/mmaction/recognition/csn/ircsn_from_scratch_r152_ig65m_20200807-771c4135.pth', # noqa: E501
depth=152,
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/csn/inference_csn_dnn.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dCSN',
pretrained2d=False,
pretrained= # noqa: E251
'https://download.openmmlab.com/mmaction/recognition/csn/ircsn_from_scratch_r152_ig65m_20200807-771c4135.pth', # noqa: E501
depth=152,
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/csn/ircsn_ig65m_pretrained_bnfrozen_r152_32x2x1_58e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dCSN',
pretrained2d=False,
pretrained= # noqa: E251
'https://download.openmmlab.com/mmaction/recognition/csn/ircsn_from_scratch_r152_ig65m_20200807-771c4135.pth', # noqa: E501
depth=152,
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/csn/inference_csn_enn.py |
# model settings
evidence_loss = dict(type='EvidenceLoss',
num_classes=101,
evidence='exp',
loss_type='log',
with_kldiv=False,
with_avuloss=True,
annealing_method='exp')
model = dict(
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/csn/finetune_ucf101_csn_edlnokl_avuc_debias.py |
model = dict(
type='Recognizer3DBNN',
backbone=dict(
type='ResNet3dSlowFast',
pretrained=None,
resample_rate=4, # tau
speed_ratio=4, # alpha
channel_ratio=8, # beta_inv
slow_pathway=dict(
type='resnet3d',
depth=50,
pretrained... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/slowfast/inference_slowfast_bnn.py |
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowFast',
pretrained=None,
resample_rate=4, # tau
speed_ratio=4, # alpha
channel_ratio=8, # beta_inv
slow_pathway=dict(
type='resnet3d',
depth=50,
pretrained=No... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/slowfast/slowfast_r50_8x8x1_256e_kinetics400_rgb.py |
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowFast',
pretrained=None,
resample_rate=8, # tau
speed_ratio=8, # alpha
channel_ratio=8, # beta_inv
slow_pathway=dict(
type='resnet3d',
depth=50,
pretrained=No... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/slowfast/slowfast_r50_video_inference_4x16x1_256e_kinetics400_rgb.py |
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowFast',
pretrained=None,
resample_rate=8, # tau
speed_ratio=8, # alpha
channel_ratio=8, # beta_inv
slow_pathway=dict(
type='resnet3d',
depth=50,
pretrained=No... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/slowfast/slowfast_r50_video_4x16x1_256e_kinetics400_rgb.py |
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowFast',
pretrained=None,
resample_rate=4, # tau
speed_ratio=4, # alpha
channel_ratio=8, # beta_inv
slow_pathway=dict(
type='resnet3d',
depth=50,
pretrained=No... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/slowfast/inference_slowfast_dnn.py |
# model settings
evidence_loss = dict(type='EvidenceLoss',
num_classes=101,
evidence='exp',
loss_type='log',
with_kldiv=False,
with_avuloss=True,
annealing_method='exp')
model = dict(
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/slowfast/finetune_ucf101_slowfast_edlnokl_avuc_debias.py |
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowFast',
pretrained=None,
resample_rate=8, # tau
speed_ratio=8, # alpha
channel_ratio=8, # beta_inv
slow_pathway=dict(
type='resnet3d',
depth=50,
pretrained=No... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/slowfast/slowfast_r50_4x16x1_256e_kinetics400_rgb.py |
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowFast',
pretrained=None,
resample_rate=4, # tau
speed_ratio=4, # alpha
channel_ratio=8, # beta_inv
slow_pathway=dict(
type='resnet3d',
depth=50,
pretrained=No... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/slowfast/inference_slowfast_enn.py |
model = dict(
type='Recognizer3DRPL',
backbone=dict(
type='ResNet3dSlowFast',
pretrained=None,
resample_rate=4, # tau
speed_ratio=4, # alpha
channel_ratio=8, # beta_inv
slow_pathway=dict(
type='resnet3d',
depth=50,
pretrained... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/slowfast/finetune_ucf101_slowfast_rpl.py |
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowFast',
pretrained=None,
resample_rate=4, # tau
speed_ratio=4, # alpha
channel_ratio=8, # beta_inv
slow_pathway=dict(
type='resnet3d',
depth=50,
pretrained=No... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/slowfast/finetune_ucf101_slowfast_dnn.py |
model = dict(
type='Recognizer3DRPL',
backbone=dict(
type='ResNet3dSlowFast',
pretrained=None,
resample_rate=4, # tau
speed_ratio=4, # alpha
channel_ratio=8, # beta_inv
slow_pathway=dict(
type='resnet3d',
depth=50,
pretrained... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/slowfast/inference_slowfast_rpl.py |
model = dict(
type='Recognizer3DBNN',
backbone=dict(
type='ResNet3dSlowFast',
pretrained=None,
resample_rate=4, # tau
speed_ratio=4, # alpha
channel_ratio=8, # beta_inv
slow_pathway=dict(
type='resnet3d',
depth=50,
pretrained... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/slowfast/finetune_ucf101_slowfast_bnn.py |
# model settings
model = dict(
type='Recognizer2DBNN',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMBNNHead',
num_classes=101,
in_channels=2048,
s... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/finetune_ucf101_tsm_bnn.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet101',
depth=101,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMHead',
num_classes=174,
in_channels=2048,
spati... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/tsm_r101_1x1x8_50e_sthv1_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
num_segments=16,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMHead',
num_classes=174,
num_segm... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/tsm_r50_1x1x16_50e_sthv2_rgb.py |
# model settings
evidence_loss = dict(type='EvidenceLoss',
num_classes=101,
evidence='exp',
loss_type='log',
with_kldiv=False,
with_avuloss=True,
annealing_method='exp')
model = dict(
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/train_kinetics10_tsm_DEAR.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMHead',
num_classes=400,
in_channels=2048,
spatial... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/tsm_r50_video_inference_1x1x8_100e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMHead',
num_classes=101,
in_channels=2048,
spatial... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/finetune_ucf101_tsm_dnn.py |
# model settings
evidence_loss = dict(type='EvidenceLoss',
num_classes=101,
evidence='exp',
loss_type='log',
with_kldiv=False,
with_avuloss=True,
annealing_method='exp')
model = dict(
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/finetune_ucf101_tsm_edlnokl_avuc_debias.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMHead',
num_classes=400,
in_channels=2048,
spatial... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/tsm_r50_dense_1x1x8_100e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
num_segments=16,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMHead',
num_classes=400,
num_segm... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/tsm_r50_1x1x16_50e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer2DRPL',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMRPLHead',
loss_cls=dict(type='RPLoss',
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/inference_tsm_rpl.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMHead',
num_classes=174,
in_channels=2048,
spatial... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/tsm_r50_1x1x8_50e_sthv1_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
non_local=((0, 0, 0), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0, 0, 0)),
non_local_cfg=dict(
sub_sample=True... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/tsm_nl_embedded_gaussian_r50_1x1x8_50e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMHead',
num_classes=400,
in_channels=2048,
spatial... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/tsm_r50_1x1x8_50e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
non_local=((0, 0, 0), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0, 0, 0)),
non_local_cfg=dict(
sub_sample=True... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/tsm_nl_gaussian_r50_1x1x8_50e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMHead',
loss_cls=dict(type='EvidenceLoss',
n... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/inference_tsm_enn.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
num_segments=16,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMHead',
num_classes=174,
num_segm... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/tsm_r50_1x1x16_50e_sthv1_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet101',
depth=101,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMHead',
num_classes=174,
in_channels=2048,
spati... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/tsm_r101_1x1x8_50e_sthv2_rgb.py |
# model settings
model = dict(
type='Recognizer2DRPL',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMRPLHead',
loss_cls=dict(type='RPLoss',
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/finetune_ucf101_tsm_rpl.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
temporal_pool=True,
shift_div=8),
cls_head=dict(
type='TSMHead',
num_classes=400,
in_ch... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/tsm_temporal_pool_r50_1x1x8_50e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMHead',
num_classes=101,
in_channels=2048,
spatial... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/inference_tsm_dnn.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMHead',
num_classes=174,
in_channels=2048,
spatial... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/tsm_r50_1x1x8_50e_sthv2_rgb.py |
# model settings
evidence_loss = dict(type='EvidenceLoss',
num_classes=101,
evidence='exp',
loss_type='log',
with_kldiv=False,
with_avuloss=True,
annealing_method='exp')
model = dict(
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/train_kinetics10_tsm_DEAR_noDebias.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMHead',
num_classes=400,
in_channels=2048,
spatial... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/tsm_r50_video_1x1x8_50e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer2DBNN',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
shift_div=8),
cls_head=dict(
type='TSMBNNHead',
num_classes=101,
in_channels=2048,
s... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/inference_tsm_bnn.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
non_local=((0, 0, 0), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0, 0, 0)),
non_local_cfg=dict(
sub_sample=True... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tsm/tsm_nl_dot_product_r50_1x1x8_50e_kinetics400_rgb.py |
# model settings
evidence_loss = dict(type='EvidenceLoss',
num_classes=101,
evidence='exp',
loss_type='log',
with_kldiv=False,
with_avuloss=False,
annealing_method='exp')
# mae huge
model... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/mae/inference_mae_enn.py |
# model settings
evidence_loss = dict(type='EvidenceLoss',
num_classes=101,
evidence='exp',
loss_type='log',
with_kldiv=False,
with_avuloss=False,
annealing_method='exp')
# mae huge -----... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/mae/finetune_ucf101_mae_edlnokl.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='C3D',
pretrained= # noqa: E251
'https://download.openmmlab.com/mmaction/recognition/c3d/c3d_sports1m_pretrain_20201016-dcc47ddc.pth', # noqa: E501
style='pytorch',
conv_cfg=dict(type='Conv3d'),
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/c3d/c3d_sports1m_16x1x1_45e_ucf101_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
# pretrained='work_dirs/i3d/finetune_ucf101_i3d_edlnokl/latest.pth',
# pretrained=False,
depth=50,
conv_cfg=dict(typ... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/inference_i3d_enn.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
depth=50,
conv_cfg=dict(type='Conv3d'),
norm_eval=False,
inflate=((1, 1, 1), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0, 1... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/i3d_r50_32x2x1_100e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer3DRPL',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
depth=50,
conv_cfg=dict(type='Conv3d'),
norm_eval=False,
inflate=((1, 1, 1), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/finetune_ucf101_i3d_rpl.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
depth=50,
conv_cfg=dict(type='Conv3d'),
norm_eval=False,
inflate=((1, 1, 1), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0, 1... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/inference_i3d_dnn.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
depth=50,
conv_cfg=dict(type='Conv3d'),
norm_eval=False,
inflate=((1, 1, 1), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0, 1... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/i3d_nl_dot_product_r50_32x2x1_100e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
depth=50,
norm_eval=False,
inflate=((1, 1, 1), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0, 1, 0)),
zero_init_residual=Fals... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/i3d_r50_lazy_32x2x1_100e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
depth=50,
conv_cfg=dict(type='Conv3d'),
norm_eval=False,
inflate=((1, 1, 1), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0, 1... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/i3d_r50_video_inference_32x2x1_100e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
depth=50,
conv_cfg=dict(type='Conv3d'),
norm_eval=False,
inflate=(1, 1, 1, 1),
conv1_stride_t=1,
poo... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/i3d_r50_video_heavy_8x8x1_100e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
depth=50,
conv_cfg=dict(type='Conv3d'),
norm_eval=False,
inflate=((1, 1, 1), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0, 1... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/i3d_nl_embedded_gaussian_r50_32x2x1_100e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer3DBNN',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
depth=50,
conv_cfg=dict(type='Conv3d'),
norm_eval=False,
inflate=((1, 1, 1), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/inference_i3d_bnn.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
depth=50,
conv_cfg=dict(type='Conv3d'),
norm_eval=False,
inflate=(1, 1, 1, 1),
conv1_stride_t=1,
poo... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/i3d_r50_heavy_8x8x1_100e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer3DBNN',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
depth=50,
conv_cfg=dict(type='Conv3d'),
norm_eval=False,
inflate=((1, 1, 1), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/finetune_ucf101_i3d_bnn.py |
# model settings
evidence_loss = dict(type='EvidenceLoss',
num_classes=101,
evidence='exp',
loss_type='log',
with_kldiv=False,
with_avuloss=False,
annealing_method='exp')
model = dict(
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/finetune_ucf101_i3d_edlnokl.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
depth=50,
conv_cfg=dict(type='Conv3d'),
norm_eval=False,
inflate=((1, 1, 1), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0, 1... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/i3d_nl_gaussian_r50_32x2x1_100e_kinetics400_rgb.py |
# model settings
evidence_loss = dict(type='EvidenceLoss',
num_classes=10,
evidence='exp',
loss_type='log',
with_kldiv=False,
with_avuloss=True,
annealing_method='exp')
model = dict(
t... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/train_kinetics10_i3d_DEAR_noDebias.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
depth=50,
conv_cfg=dict(type='Conv3d'),
norm_eval=False,
inflate=((1, 1, 1), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0, 1... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/i3d_r50_video_32x2x1_100e_kinetics400_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
depth=50,
conv_cfg=dict(type='Conv3d'),
norm_eval=False,
inflate=((1, 1, 1), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0, 1... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/finetune_ucf101_i3d_dnn.py |
# model settings
model = dict(
type='Recognizer3DRPL',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
depth=50,
conv_cfg=dict(type='Conv3d'),
norm_eval=False,
inflate=((1, 1, 1), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/inference_i3d_rpl.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3d',
pretrained2d=True,
pretrained='torchvision://resnet50',
depth=50,
conv_cfg=dict(type='Conv3d'),
norm_eval=False,
inflate=((1, 1, 1), (1, 0, 1, 0), (1, 0, 1, 0, 1, 0), (0, 1... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/i3d_r50_dense_32x2x1_100e_kinetics400_rgb.py |
# model settings
evidence_loss = dict(type='EvidenceLoss',
num_classes=101,
evidence='exp',
loss_type='log',
with_kldiv=False,
with_avuloss=True,
annealing_method='exp')
model = dict(
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/finetune_ucf101_i3d_edlnokl_avuc_debias.py |
# model settings
evidence_loss = dict(type='EvidenceLoss',
num_classes=10,
evidence='exp',
loss_type='log',
with_kldiv=False,
with_avuloss=True,
annealing_method='exp')
model = dict(
t... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/i3d/train_kinetics10_i3d_DEAR.py |
# model settings
model = dict(
type='Recognizer3DRPL',
backbone=dict(
type='ResNet3dSlowOnly',
depth=50,
pretrained='torchvision://resnet50',
lateral=False,
out_indices=(2, 3),
conv1_kernel=(1, 7, 7),
conv1_stride_t=1,
pool1_stride_t=1,
inf... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tpn/inference_tpn_slowonly_rpl.py |
# model settings
evidence_loss = dict(type='EvidenceLoss',
num_classes=101,
evidence='exp',
loss_type='log',
with_kldiv=False,
with_avuloss=True,
annealing_method='exp')
model = dict(
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tpn/tpn_slowonly_edlloss_nokl_avuc_debias_r50_8x8x1_150e_kinetics_rgb.py |
# model settings
evidence_loss = dict(type='EvidenceLoss',
num_classes=101,
evidence='exp',
loss_type='log',
annealing_method='exp')
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowOnly',
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tpn/tpn_slowonly_edlloss_r50_8x8x1_150e_kinetics_rgb.py |
# model settings
evidence_loss = dict(type='EvidenceLoss',
num_classes=101,
evidence='exp',
loss_type='log',
with_kldiv=False,
with_avuloss=True,
disentangle=True,
an... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tpn/tpn_slowonly_edlloss_nokl_davuc_debias_r50_8x8x1_150e_kinetics_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowOnly',
depth=50,
pretrained='torchvision://resnet50',
lateral=False,
out_indices=(2, 3),
conv1_kernel=(1, 7, 7),
conv1_stride_t=1,
pool1_stride_t=1,
inflat... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tpn/tpn_imagenet_pretrained_slowonly_r50_8x8x1_150e_kinetics_rgb.py |
# model settings
model = dict(
type='Recognizer3DBNN',
backbone=dict(
type='ResNet3dSlowOnly',
depth=50,
pretrained='torchvision://resnet50',
lateral=False,
out_indices=(2, 3),
conv1_kernel=(1, 7, 7),
conv1_stride_t=1,
pool1_stride_t=1,
inf... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tpn/inference_tpn_slowonly_bnn.py |
# model settings
evidence_loss = dict(type='EvidenceLoss',
num_classes=101,
evidence='exp',
loss_type='log',
with_kldiv=False,
with_avuloss=True,
annealing_method='exp')
model = dict(
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tpn/tpn_slowonly_edlloss_nokl_avuc_rebias_r50_8x8x1_150e_kinetics_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowOnly',
depth=50,
pretrained='torchvision://resnet50',
lateral=False,
out_indices=(2, 3),
conv1_kernel=(1, 7, 7),
conv1_stride_t=1,
pool1_stride_t=1,
inflat... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tpn/tpn_slowonly_celoss_r50_8x8x1_150e_kinetics_rgb.py |
# model settings
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowOnly',
depth=50,
pretrained=None,
lateral=False,
out_indices=(2, 3),
conv1_kernel=(1, 7, 7),
conv1_stride_t=1,
pool1_stride_t=1,
inflate=(0, 0, 1, 1),
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tpn/tpn_slowonly_r50_8x8x1_150e_kinetics_rgb.py |
# model settings
model = dict(
type='Recognizer2D',
backbone=dict(
type='ResNetTSM',
pretrained='torchvision://resnet50',
depth=50,
out_indices=(2, 3),
norm_eval=False,
shift_div=8),
neck=dict(
type='TPN',
in_channels=(1024, 2048),
out_... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tpn/tpn_tsm_r50_1x1x8_150e_sthv1_rgb.py |
# model settings
evidence_loss = dict(type='EvidenceLoss',
num_classes=101,
evidence='exp',
loss_type='log',
with_kldiv=False,
with_avuloss=True,
annealing_method='exp')
model = dict(
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/configs/recognition/tpn/tpn_slowonly_edlloss_nokl_avuc_r50_8x8x1_150e_kinetics_rgb.py |
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