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https://github.com/open-mmlab/mmyolo.git
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75fc8fc2a3
* add cfg * add copypaste * add todo * 在mosaic和mixup中处理gt_masks,改config * fix cat bug * add finetune box in affine * add repr * del albu config in l * add doc * add config * format code * fix loadmask * addconfig,fix mask * fix loadann * fix tra * update LoadAnnotations * update * support mask * fix error * fix error * fix config and no maskrefine bug * fix * fix * update config * format code * beauty config * add yolov5 config and readme * beauty yolov5 config * add ut * fix ut. bitmap 2 poly * fix ut and add mix transform ut. * fix bool * fix loadann * rollback yolov5 * rollback yolov5 * format * 提高速度 * update --------- Co-authored-by: huanghaian <huanghaian@sensetime.com>
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
_base_ = './yolov8_m_syncbn_fast_8xb16-500e_coco.py'
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# ========================modified parameters======================
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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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# =======================Unmodified in most cases==================
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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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