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_base_ = './rtmdet_l_8xb32-300e_coco.py' | |
checkpoint = 'https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-s_imagenet_600e.pth' # noqa | |
model = dict( | |
backbone=dict( | |
deepen_factor=0.33, | |
widen_factor=0.5, | |
init_cfg=dict( | |
type='Pretrained', prefix='backbone.', checkpoint=checkpoint)), | |
neck=dict(in_channels=[128, 256, 512], out_channels=128, num_csp_blocks=1), | |
bbox_head=dict(in_channels=128, feat_channels=128, exp_on_reg=False)) | |
train_pipeline = [ | |
dict( | |
type='LoadImageFromFile', | |
file_client_args={{_base_.file_client_args}}), | |
dict(type='LoadAnnotations', with_bbox=True), | |
dict(type='CachedMosaic', img_scale=(640, 640), pad_val=114.0), | |
dict( | |
type='RandomResize', | |
scale=(1280, 1280), | |
ratio_range=(0.5, 2.0), | |
keep_ratio=True), | |
dict(type='RandomCrop', crop_size=(640, 640)), | |
dict(type='YOLOXHSVRandomAug'), | |
dict(type='RandomFlip', prob=0.5), | |
dict(type='Pad', size=(640, 640), pad_val=dict(img=(114, 114, 114))), | |
dict( | |
type='CachedMixUp', | |
img_scale=(640, 640), | |
ratio_range=(1.0, 1.0), | |
max_cached_images=20, | |
pad_val=(114, 114, 114)), | |
dict(type='PackDetInputs') | |
] | |
train_pipeline_stage2 = [ | |
dict( | |
type='LoadImageFromFile', | |
file_client_args={{_base_.file_client_args}}), | |
dict(type='LoadAnnotations', with_bbox=True), | |
dict( | |
type='RandomResize', | |
scale=(640, 640), | |
ratio_range=(0.5, 2.0), | |
keep_ratio=True), | |
dict(type='RandomCrop', crop_size=(640, 640)), | |
dict(type='YOLOXHSVRandomAug'), | |
dict(type='RandomFlip', prob=0.5), | |
dict(type='Pad', size=(640, 640), pad_val=dict(img=(114, 114, 114))), | |
dict(type='PackDetInputs') | |
] | |
train_dataloader = dict(dataset=dict(pipeline=train_pipeline)) | |
custom_hooks = [ | |
dict( | |
type='EMAHook', | |
ema_type='ExpMomentumEMA', | |
momentum=0.0002, | |
update_buffers=True, | |
priority=49), | |
dict( | |
type='PipelineSwitchHook', | |
switch_epoch=280, | |
switch_pipeline=train_pipeline_stage2) | |
] | |