|
_base_ = './yolov8_s_syncbn_fast_8xb16-500e_coco.py' |
|
|
|
|
|
deepen_factor = 0.67 |
|
widen_factor = 0.75 |
|
last_stage_out_channels = 768 |
|
|
|
affine_scale = 0.9 |
|
mixup_prob = 0.1 |
|
|
|
|
|
img_scale = _base_.img_scale |
|
pre_transform = _base_.pre_transform |
|
last_transform = _base_.last_transform |
|
|
|
model = dict( |
|
backbone=dict( |
|
last_stage_out_channels=last_stage_out_channels, |
|
deepen_factor=deepen_factor, |
|
widen_factor=widen_factor), |
|
neck=dict( |
|
deepen_factor=deepen_factor, |
|
widen_factor=widen_factor, |
|
in_channels=[256, 512, last_stage_out_channels], |
|
out_channels=[256, 512, last_stage_out_channels]), |
|
bbox_head=dict( |
|
head_module=dict( |
|
widen_factor=widen_factor, |
|
in_channels=[256, 512, last_stage_out_channels]))) |
|
|
|
mosaic_affine_transform = [ |
|
dict( |
|
type='Mosaic', |
|
img_scale=img_scale, |
|
pad_val=114.0, |
|
pre_transform=pre_transform), |
|
dict( |
|
type='YOLOv5RandomAffine', |
|
max_rotate_degree=0.0, |
|
max_shear_degree=0.0, |
|
max_aspect_ratio=100, |
|
scaling_ratio_range=(1 - affine_scale, 1 + affine_scale), |
|
|
|
border=(-img_scale[0] // 2, -img_scale[1] // 2), |
|
border_val=(114, 114, 114)) |
|
] |
|
|
|
|
|
train_pipeline = [ |
|
*pre_transform, *mosaic_affine_transform, |
|
dict( |
|
type='YOLOv5MixUp', |
|
prob=mixup_prob, |
|
pre_transform=[*pre_transform, *mosaic_affine_transform]), |
|
*last_transform |
|
] |
|
|
|
train_pipeline_stage2 = [ |
|
*pre_transform, |
|
dict(type='YOLOv5KeepRatioResize', scale=img_scale), |
|
dict( |
|
type='LetterResize', |
|
scale=img_scale, |
|
allow_scale_up=True, |
|
pad_val=dict(img=114.0)), |
|
dict( |
|
type='YOLOv5RandomAffine', |
|
max_rotate_degree=0.0, |
|
max_shear_degree=0.0, |
|
scaling_ratio_range=(1 - affine_scale, 1 + affine_scale), |
|
max_aspect_ratio=100, |
|
border_val=(114, 114, 114)), *last_transform |
|
] |
|
|
|
train_dataloader = dict(dataset=dict(pipeline=train_pipeline)) |
|
_base_.custom_hooks[1].switch_pipeline = train_pipeline_stage2 |
|
|
