-
Notifications
You must be signed in to change notification settings - Fork 535
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
[Feature] YOLOv5 supports using mask annotation to optimize bbox (#565)
* add v5 config and readme * fix config * update config * add remove mask * update * update * fix * update --------- Co-authored-by: huanghaian <huanghaian@sensetime.com>
- Loading branch information
1 parent
557f304
commit bda1050
Showing
7 changed files
with
355 additions
and
11 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
77 changes: 77 additions & 0 deletions
77
configs/yolov5/mask_refine/yolov5_l_mask-refine-v61_syncbn_fast_8xb16-300e_coco.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,77 @@ | ||
| _base_ = './yolov5_m_mask-refine-v61_syncbn_fast_8xb16-300e_coco.py' | ||
|
|
||
| # This config use refining bbox and `YOLOv5CopyPaste`. | ||
| # Refining bbox means refining bbox by mask while loading annotations and | ||
| # transforming after `YOLOv5RandomAffine` | ||
|
|
||
| # ========================modified parameters====================== | ||
| deepen_factor = 1.0 | ||
| widen_factor = 1.0 | ||
|
|
||
| mixup_prob = 0.1 | ||
| copypaste_prob = 0.1 | ||
|
|
||
| # =======================Unmodified in most cases================== | ||
| img_scale = _base_.img_scale | ||
|
|
||
| model = dict( | ||
| backbone=dict( | ||
| deepen_factor=deepen_factor, | ||
| widen_factor=widen_factor, | ||
| ), | ||
| neck=dict( | ||
| deepen_factor=deepen_factor, | ||
| widen_factor=widen_factor, | ||
| ), | ||
| bbox_head=dict(head_module=dict(widen_factor=widen_factor))) | ||
|
|
||
| pre_transform = _base_.pre_transform | ||
| albu_train_transforms = _base_.albu_train_transforms | ||
|
|
||
| mosaic_affine_pipeline = [ | ||
| dict( | ||
| type='Mosaic', | ||
| img_scale=img_scale, | ||
| pad_val=114.0, | ||
| pre_transform=pre_transform), | ||
| dict(type='YOLOv5CopyPaste', prob=copypaste_prob), | ||
| dict( | ||
| type='YOLOv5RandomAffine', | ||
| max_rotate_degree=0.0, | ||
| max_shear_degree=0.0, | ||
| scaling_ratio_range=(1 - _base_.affine_scale, 1 + _base_.affine_scale), | ||
| # img_scale is (width, height) | ||
| border=(-img_scale[0] // 2, -img_scale[1] // 2), | ||
| border_val=(114, 114, 114), | ||
| min_area_ratio=_base_.min_area_ratio, | ||
| use_mask_refine=_base_.use_mask2refine), | ||
| dict(type='RemoveDataElement', keys=['gt_masks']) | ||
| ] | ||
|
|
||
| # enable mixup and copypaste | ||
| train_pipeline = [ | ||
| *pre_transform, *mosaic_affine_pipeline, | ||
| dict( | ||
| type='YOLOv5MixUp', | ||
| prob=mixup_prob, | ||
| pre_transform=[*pre_transform, *mosaic_affine_pipeline]), | ||
| dict( | ||
| type='mmdet.Albu', | ||
| transforms=albu_train_transforms, | ||
| bbox_params=dict( | ||
| type='BboxParams', | ||
| format='pascal_voc', | ||
| label_fields=['gt_bboxes_labels', 'gt_ignore_flags']), | ||
| keymap={ | ||
| 'img': 'image', | ||
| 'gt_bboxes': 'bboxes' | ||
| }), | ||
| dict(type='YOLOv5HSVRandomAug'), | ||
| dict(type='mmdet.RandomFlip', prob=0.5), | ||
| dict( | ||
| type='mmdet.PackDetInputs', | ||
| meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', 'flip', | ||
| 'flip_direction')) | ||
| ] | ||
|
|
||
| train_dataloader = dict(dataset=dict(pipeline=train_pipeline)) |
Oops, something went wrong.