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_base_ = './yolov8_m_syncbn_fast_8xb16-500e_coco.py' |
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deepen_factor = 1.00 |
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widen_factor = 1.00 |
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last_stage_out_channels = 512 |
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mixup_prob = 0.15 |
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pre_transform = _base_.pre_transform |
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mosaic_affine_transform = _base_.mosaic_affine_transform |
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last_transform = _base_.last_transform |
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model = dict( |
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backbone=dict( |
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last_stage_out_channels=last_stage_out_channels, |
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deepen_factor=deepen_factor, |
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widen_factor=widen_factor), |
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neck=dict( |
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deepen_factor=deepen_factor, |
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widen_factor=widen_factor, |
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in_channels=[256, 512, last_stage_out_channels], |
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out_channels=[256, 512, last_stage_out_channels]), |
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bbox_head=dict( |
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head_module=dict( |
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widen_factor=widen_factor, |
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in_channels=[256, 512, last_stage_out_channels]))) |
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train_pipeline = [ |
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*pre_transform, *mosaic_affine_transform, |
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dict( |
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type='YOLOv5MixUp', |
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prob=mixup_prob, |
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pre_transform=[*pre_transform, *mosaic_affine_transform]), |
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*last_transform |
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] |
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train_dataloader = dict(dataset=dict(pipeline=train_pipeline)) |
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