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YOLO-World3
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third_party
/mmyolo
/configs
/yolov5
/ins_seg
/yolov5_ins_l-v61_syncbn_fast_8xb16-300e_coco_instance.py
_base_ = './yolov5_ins_m-v61_syncbn_fast_8xb16-300e_coco_instance.py' # noqa | |
# 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), | |
border=(-img_scale[0] // 2, -img_scale[1] // 2), | |
border_val=(114, 114, 114), | |
min_area_ratio=_base_.min_area_ratio, | |
max_aspect_ratio=_base_.max_aspect_ratio, | |
use_mask_refine=_base_.use_mask2refine), | |
] | |
# enable mixup | |
train_pipeline = [ | |
*pre_transform, | |
*mosaic_affine_pipeline, | |
dict( | |
type='YOLOv5MixUp', | |
prob=mixup_prob, | |
pre_transform=[*pre_transform, *mosaic_affine_pipeline]), | |
# TODO: support mask transform in albu | |
# Geometric transformations are not supported in albu now. | |
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='Polygon2Mask', | |
downsample_ratio=_base_.downsample_ratio, | |
mask_overlap=_base_.mask_overlap), | |
dict( | |
type='PackDetInputs', | |
meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', 'flip', | |
'flip_direction')) | |
] | |
train_dataloader = dict(dataset=dict(pipeline=train_pipeline)) | |