data set

[Hiwyl]

Do I have to use segmentation data sets?but i just have box

[dengtianbi]

I meet the same problem !
Did you solve it ？

[Hiwyl]

@Scalsol TKS

[Scalsol]

Box annotation is enough :)

[Hiwyl]

@Scalsol TKS help me
base = './reppoints_v2_r50_fpn_giou_1x_coco.py'

learning policy

lr_config = dict(step=[16, 22])
total_epochs = 24

multi-scale training

img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='Resize',
# img_scale=[(1333, 480), (1333, 960)],
img_scale=[(1296,972)],
multiscale_mode='range',
keep_ratio=True),
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='Normalize', **img_norm_cfg),
dict(type='Pad', size_divisor=32),
dict(type='LoadRPDV2Annotations'),
dict(type='RPDV2FormatBundle'),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_sem_map', 'gt_sem_weights']),
]
data = dict(train=dict(pipeline=train_pipeline))

this dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_sem_map', 'gt_sem_weights']) just use box?