mirror of
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>
77 lines
2.2 KiB
Python
77 lines
2.2 KiB
Python
_base_ = './yolov8_s_syncbn_fast_8xb16-500e_coco.py'
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# ========================modified parameters======================
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deepen_factor = 0.67
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widen_factor = 0.75
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last_stage_out_channels = 768
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affine_scale = 0.9
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mixup_prob = 0.1
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# =======================Unmodified in most cases==================
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img_scale = _base_.img_scale
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pre_transform = _base_.pre_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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mosaic_affine_transform = [
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dict(
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type='Mosaic',
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img_scale=img_scale,
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pad_val=114.0,
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pre_transform=pre_transform),
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dict(
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type='YOLOv5RandomAffine',
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max_rotate_degree=0.0,
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max_shear_degree=0.0,
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max_aspect_ratio=100,
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scaling_ratio_range=(1 - affine_scale, 1 + affine_scale),
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# img_scale is (width, height)
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border=(-img_scale[0] // 2, -img_scale[1] // 2),
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border_val=(114, 114, 114))
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]
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# enable mixup
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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_pipeline_stage2 = [
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*pre_transform,
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dict(type='YOLOv5KeepRatioResize', scale=img_scale),
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dict(
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type='LetterResize',
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scale=img_scale,
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allow_scale_up=True,
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pad_val=dict(img=114.0)),
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dict(
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type='YOLOv5RandomAffine',
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max_rotate_degree=0.0,
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max_shear_degree=0.0,
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scaling_ratio_range=(1 - affine_scale, 1 + affine_scale),
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max_aspect_ratio=100,
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border_val=(114, 114, 114)), *last_transform
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]
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train_dataloader = dict(dataset=dict(pipeline=train_pipeline))
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_base_.custom_hooks[1].switch_pipeline = train_pipeline_stage2
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