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Merge pull request open-mmlab#1183 from open-mmlab/dev-0.23
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Merge Dev 0.23
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@ly015
ly015 authored Feb 11, 2022
2 parents e040bc6 + 7387ae7 commit bf73977
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Showing 428 changed files with 6,892 additions and 3,985 deletions.
19 changes: 19 additions & 0 deletions configs/_base_/default_runtime.py
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checkpoint_config = dict(interval=10)

log_config = dict(
interval=50,
hooks=[
dict(type='TextLoggerHook'),
# dict(type='TensorboardLoggerHook')
])

log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]

# disable opencv multithreading to avoid system being overloaded
opencv_num_threads = 0
# set multi-process start method as `fork` to speed up the training
mp_start_method = 'fork'
11 changes: 4 additions & 7 deletions ...gs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/animalpose/hrnet_w32_animalpose_256x256.py
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_base_ = ['../../../../_base_/datasets/animalpose.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/animalpose.py'
]
evaluation = dict(interval=10, metric='mAP', save_best='AP')

optimizer = dict(
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11 changes: 4 additions & 7 deletions ...gs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/animalpose/hrnet_w48_animalpose_256x256.py
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_base_ = ['../../../../_base_/datasets/animalpose.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/animalpose.py'
]
evaluation = dict(interval=10, metric='mAP', save_best='AP')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/animalpose/res101_animalpose_256x256.py
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_base_ = ['../../../../_base_/datasets/animalpose.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/animalpose.py'
]
evaluation = dict(interval=10, metric='mAP', save_best='AP')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/animalpose/res152_animalpose_256x256.py
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_base_ = ['../../../../_base_/datasets/animalpose.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/animalpose.py'
]
evaluation = dict(interval=10, metric='mAP', save_best='AP')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/animalpose/res50_animalpose_256x256.py
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_base_ = ['../../../../_base_/datasets/animalpose.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/animalpose.py'
]
evaluation = dict(interval=10, metric='mAP', save_best='AP')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/ap10k/hrnet_w32_ap10k_256x256.py
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_base_ = ['../../../../_base_/datasets/ap10k.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/ap10k.py'
]
evaluation = dict(interval=10, metric='mAP', save_best='AP')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/ap10k/hrnet_w48_ap10k_256x256.py
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_base_ = ['../../../../_base_/datasets/ap10k.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/ap10k.py'
]
evaluation = dict(interval=10, metric='mAP', save_best='AP')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/ap10k/res101_ap10k_256x256.py
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_base_ = ['../../../../_base_/datasets/ap10k.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/ap10k.py'
]
evaluation = dict(interval=10, metric='mAP', save_best='AP')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/ap10k/res50_ap10k_256x256.py
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_base_ = ['../../../../_base_/datasets/ap10k.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/ap10k.py'
]
evaluation = dict(interval=10, metric='mAP', save_best='AP')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/atrw/hrnet_w32_atrw_256x256.py
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_base_ = ['../../../../_base_/datasets/atrw.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/atrw.py'
]
evaluation = dict(interval=10, metric='mAP', save_best='AP')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/atrw/hrnet_w48_atrw_256x256.py
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_base_ = ['../../../../_base_/datasets/atrw.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/atrw.py'
]
evaluation = dict(interval=10, metric='mAP', save_best='AP')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/atrw/res101_atrw_256x256.py
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@@ -1,10 +1,7 @@
_base_ = ['../../../../_base_/datasets/atrw.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/atrw.py'
]
evaluation = dict(interval=10, metric='mAP', save_best='AP')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/atrw/res152_atrw_256x256.py
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@@ -1,10 +1,7 @@
_base_ = ['../../../../_base_/datasets/atrw.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/atrw.py'
]
evaluation = dict(interval=10, metric='mAP', save_best='AP')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/atrw/res50_atrw_256x256.py
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@@ -1,10 +1,7 @@
_base_ = ['../../../../_base_/datasets/atrw.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/atrw.py'
]
evaluation = dict(interval=10, metric='mAP', save_best='AP')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/fly/res101_fly_192x192.py
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_base_ = ['../../../../_base_/datasets/fly.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/fly.py'
]
evaluation = dict(interval=10, metric=['PCK', 'AUC', 'EPE'], save_best='AUC')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/fly/res152_fly_192x192.py
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_base_ = ['../../../../_base_/datasets/fly.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/fly.py'
]
evaluation = dict(interval=10, metric=['PCK', 'AUC', 'EPE'], save_best='AUC')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/fly/res50_fly_192x192.py
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@@ -1,10 +1,7 @@
_base_ = ['../../../../_base_/datasets/fly.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/fly.py'
]
evaluation = dict(interval=10, metric=['PCK', 'AUC', 'EPE'], save_best='AUC')

optimizer = dict(
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11 changes: 4 additions & 7 deletions ...s/animal/2d_kpt_sview_rgb_img/topdown_heatmap/horse10/hrnet_w32_horse10_256x256-split1.py
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_base_ = ['../../../../_base_/datasets/horse10.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/horse10.py'
]
evaluation = dict(interval=10, metric='PCK', save_best='PCK')

optimizer = dict(
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11 changes: 4 additions & 7 deletions ...s/animal/2d_kpt_sview_rgb_img/topdown_heatmap/horse10/hrnet_w32_horse10_256x256-split2.py
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@@ -1,10 +1,7 @@
_base_ = ['../../../../_base_/datasets/horse10.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/horse10.py'
]
evaluation = dict(interval=10, metric='PCK', save_best='PCK')

optimizer = dict(
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11 changes: 4 additions & 7 deletions ...s/animal/2d_kpt_sview_rgb_img/topdown_heatmap/horse10/hrnet_w32_horse10_256x256-split3.py
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@@ -1,10 +1,7 @@
_base_ = ['../../../../_base_/datasets/horse10.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/horse10.py'
]
evaluation = dict(interval=10, metric='PCK', save_best='PCK')

optimizer = dict(
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11 changes: 4 additions & 7 deletions ...s/animal/2d_kpt_sview_rgb_img/topdown_heatmap/horse10/hrnet_w48_horse10_256x256-split1.py
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@@ -1,10 +1,7 @@
_base_ = ['../../../../_base_/datasets/horse10.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/horse10.py'
]
evaluation = dict(interval=10, metric='PCK', save_best='PCK')

optimizer = dict(
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11 changes: 4 additions & 7 deletions ...s/animal/2d_kpt_sview_rgb_img/topdown_heatmap/horse10/hrnet_w48_horse10_256x256-split2.py
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@@ -1,10 +1,7 @@
_base_ = ['../../../../_base_/datasets/horse10.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/horse10.py'
]
evaluation = dict(interval=10, metric='PCK', save_best='PCK')

optimizer = dict(
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11 changes: 4 additions & 7 deletions ...s/animal/2d_kpt_sview_rgb_img/topdown_heatmap/horse10/hrnet_w48_horse10_256x256-split3.py
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@@ -1,10 +1,7 @@
_base_ = ['../../../../_base_/datasets/horse10.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/horse10.py'
]
evaluation = dict(interval=10, metric='PCK', save_best='PCK')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/horse10/res101_horse10_256x256-split1.py
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@@ -1,10 +1,7 @@
_base_ = ['../../../../_base_/datasets/horse10.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/horse10.py'
]
evaluation = dict(interval=10, metric='PCK', save_best='PCK')

optimizer = dict(
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11 changes: 4 additions & 7 deletions configs/animal/2d_kpt_sview_rgb_img/topdown_heatmap/horse10/res101_horse10_256x256-split2.py
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@@ -1,10 +1,7 @@
_base_ = ['../../../../_base_/datasets/horse10.py']
log_level = 'INFO'
load_from = None
resume_from = None
dist_params = dict(backend='nccl')
workflow = [('train', 1)]
checkpoint_config = dict(interval=10)
_base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/horse10.py'
]
evaluation = dict(interval=10, metric='PCK', save_best='PCK')

optimizer = dict(
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