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# YOLOv6s model | |
model = dict( | |
type='YOLOv6s', | |
pretrained=None, | |
depth_multiple=0.33, | |
width_multiple=0.50, | |
backbone=dict( | |
type='EfficientRep', | |
num_repeats=[1, 6, 12, 18, 6], | |
out_channels=[64, 128, 256, 512, 1024], | |
), | |
neck=dict( | |
type='RepPAN', | |
num_repeats=[12, 12, 12, 12], | |
out_channels=[256, 128, 128, 256, 256, 512], | |
), | |
head=dict( | |
type='EffiDeHead', | |
in_channels=[128, 256, 512], | |
num_layers=3, | |
begin_indices=24, | |
anchors=1, | |
out_indices=[17, 20, 23], | |
strides=[8, 16, 32], | |
iou_type='siou' | |
) | |
) | |
solver = dict( | |
optim='SGD', | |
lr_scheduler='Cosine', | |
lr0=0.01, | |
lrf=0.01, | |
momentum=0.937, | |
weight_decay=0.0005, | |
warmup_epochs=3.0, | |
warmup_momentum=0.8, | |
warmup_bias_lr=0.1 | |
) | |
data_aug = dict( | |
hsv_h=0.015, | |
hsv_s=0.7, | |
hsv_v=0.4, | |
degrees=0.0, | |
translate=0.1, | |
scale=0.5, | |
shear=0.0, | |
flipud=0.0, | |
fliplr=0.5, | |
mosaic=1.0, | |
mixup=0.0, | |
) | |