|
|
|
|
_base_ = ['./yolov3_mobilenetv2_mstrain-416_300e_coco.py']
|
|
|
|
|
|
|
|
|
|
# yapf:disable
|
|
|
|
|
model = dict(
|
|
|
|
|
bbox_head=dict(
|
|
|
|
|
anchor_generator=dict(
|
|
|
|
|
base_sizes=[[(220, 125), (128, 222), (264, 266)],
|
|
|
|
|
[(35, 87), (102, 96), (60, 170)],
|
|
|
|
|
[(10, 15), (24, 36), (72, 42)]])))
|
|
|
|
|
# yapf:enable
|
|
|
|
|
|
|
|
|
|
# dataset settings
|
|
|
|
|
img_norm_cfg = dict(
|
|
|
|
|
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
|
|
|
|
|
train_pipeline = [
|
|
|
|
|
dict(type='LoadImageFromFile'),
|
|
|
|
|
dict(type='LoadAnnotations', with_bbox=True),
|
|
|
|
|
dict(
|
|
|
|
|
type='Expand',
|
|
|
|
|
mean=img_norm_cfg['mean'],
|
|
|
|
|
to_rgb=img_norm_cfg['to_rgb'],
|
|
|
|
|
ratio_range=(1, 2)),
|
|
|
|
|
dict(
|
|
|
|
|
type='MinIoURandomCrop',
|
|
|
|
|
min_ious=(0.4, 0.5, 0.6, 0.7, 0.8, 0.9),
|
|
|
|
|
min_crop_size=0.3),
|
|
|
|
|
dict(type='Resize', img_scale=(320, 320), keep_ratio=True),
|
|
|
|
|
dict(type='RandomFlip', flip_ratio=0.5),
|
|
|
|
|
dict(type='PhotoMetricDistortion'),
|
|
|
|
|
dict(type='Normalize', **img_norm_cfg),
|
|
|
|
|
dict(type='Pad', size_divisor=32),
|
|
|
|
|
dict(type='DefaultFormatBundle'),
|
|
|
|
|
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
|
|
|
|
|
]
|
|
|
|
|
test_pipeline = [
|
|
|
|
|
dict(type='LoadImageFromFile'),
|
|
|
|
|
dict(
|
|
|
|
|
type='MultiScaleFlipAug',
|
|
|
|
|
img_scale=(320, 320),
|
|
|
|
|
flip=False,
|
|
|
|
|
transforms=[
|
|
|
|
|
dict(type='Resize', keep_ratio=True),
|
|
|
|
|
dict(type='RandomFlip'),
|
|
|
|
|
dict(type='Normalize', **img_norm_cfg),
|
|
|
|
|
dict(type='Pad', size_divisor=32),
|
|
|
|
|
dict(type='DefaultFormatBundle'),
|
|
|
|
|
dict(type='Collect', keys=['img'])
|
|
|
|
|
])
|
|
|
|
|
]
|
|
|
|
|
data = dict(
|
|
|
|
|
train=dict(dataset=dict(pipeline=train_pipeline)),
|
|
|
|
|
val=dict(pipeline=test_pipeline),
|
|
|
|
|
test=dict(pipeline=test_pipeline))
|
