mirror of https://github.com/open-mmlab/mmyolo.git
62 lines
1.9 KiB
Python
62 lines
1.9 KiB
Python
_base_ = './yolox_s_8xb8-300e_coco.py'
|
|
|
|
deepen_factor = 0.33
|
|
widen_factor = 0.375
|
|
|
|
# model settings
|
|
model = dict(
|
|
data_preprocessor=dict(batch_augments=[
|
|
dict(
|
|
type='mmdet.BatchSyncRandomResize',
|
|
random_size_range=(320, 640), # note
|
|
size_divisor=32,
|
|
interval=10)
|
|
]),
|
|
backbone=dict(deepen_factor=deepen_factor, widen_factor=widen_factor),
|
|
neck=dict(deepen_factor=deepen_factor, widen_factor=widen_factor),
|
|
bbox_head=dict(head_module=dict(widen_factor=widen_factor)))
|
|
|
|
img_scale = _base_.img_scale
|
|
pre_transform = _base_.pre_transform
|
|
|
|
train_pipeline_stage1 = [
|
|
*pre_transform,
|
|
dict(
|
|
type='Mosaic',
|
|
img_scale=img_scale,
|
|
pad_val=114.0,
|
|
pre_transform=pre_transform),
|
|
dict(
|
|
type='mmdet.RandomAffine',
|
|
scaling_ratio_range=(0.5, 1.5), # note
|
|
border=(-img_scale[0] // 2, -img_scale[1] // 2)),
|
|
dict(type='mmdet.YOLOXHSVRandomAug'),
|
|
dict(type='mmdet.RandomFlip', prob=0.5),
|
|
dict(
|
|
type='mmdet.FilterAnnotations',
|
|
min_gt_bbox_wh=(1, 1),
|
|
keep_empty=False),
|
|
dict(
|
|
type='mmdet.PackDetInputs',
|
|
meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', 'flip',
|
|
'flip_direction'))
|
|
]
|
|
|
|
test_pipeline = [
|
|
dict(type='LoadImageFromFile', file_client_args=_base_.file_client_args),
|
|
dict(type='mmdet.Resize', scale=(416, 416), keep_ratio=True), # note
|
|
dict(
|
|
type='mmdet.Pad',
|
|
pad_to_square=True,
|
|
pad_val=dict(img=(114.0, 114.0, 114.0))),
|
|
dict(type='LoadAnnotations', with_bbox=True, _scope_='mmdet'),
|
|
dict(
|
|
type='mmdet.PackDetInputs',
|
|
meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape',
|
|
'scale_factor'))
|
|
]
|
|
|
|
train_dataloader = dict(dataset=dict(pipeline=train_pipeline_stage1))
|
|
val_dataloader = dict(dataset=dict(pipeline=test_pipeline))
|
|
test_dataloader = val_dataloader
|