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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, | |
| ) | |