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default_scope = 'mmpose'
# hooks
default_hooks = dict(
timer=dict(type='IterTimerHook'),
logger=dict(type='LoggerHook', interval=50),
param_scheduler=dict(type='ParamSchedulerHook'),
checkpoint=dict(type='CheckpointHook', interval=10),
sampler_seed=dict(type='DistSamplerSeedHook'),
visualization=dict(type='PoseVisualizationHook', enable=False),
badcase=dict(
type='BadCaseAnalysisHook',
enable=False,
out_dir='badcase',
metric_type='loss',
badcase_thr=5))
# custom hooks
custom_hooks = [
# Synchronize model buffers such as running_mean and running_var in BN
# at the end of each epoch
dict(type='SyncBuffersHook')
]
# multi-processing backend
env_cfg = dict(
cudnn_benchmark=False,
mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0),
dist_cfg=dict(backend='nccl'),
)
# visualizer
vis_backends = [
dict(type='LocalVisBackend'),
# dict(type='TensorboardVisBackend'),
# dict(type='WandbVisBackend'),
]
visualizer = dict(
type='PoseLocalVisualizer', vis_backends=vis_backends, name='visualizer')
# logger
log_processor = dict(
type='LogProcessor', window_size=50, by_epoch=True, num_digits=6)
log_level = 'INFO'
load_from = None
resume = False
# file I/O backend
backend_args = dict(backend='local')
# training/validation/testing progress
train_cfg = dict(by_epoch=True)
val_cfg = dict()
test_cfg = dict()
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