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?