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| _base_ = [ | |
| '../_base_/models/occ_mask_rcnn_swin_fpn.py', | |
| '../_base_/datasets/walt_people.py', | |
| '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py' | |
| ] | |
| model = dict( | |
| backbone=dict( | |
| embed_dim=96, | |
| depths=[2, 2, 6, 2], | |
| num_heads=[3, 6, 12, 24], | |
| window_size=7, | |
| ape=False, | |
| drop_path_rate=0.1, | |
| patch_norm=True, | |
| use_checkpoint=False | |
| ), | |
| neck=dict(in_channels=[96, 192, 384, 768])) | |
| img_norm_cfg = dict( | |
| mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) | |
| # augmentation strategy originates from DETR / Sparse RCNN | |
| train_pipeline = [ | |
| dict(type='LoadImageFromFile'), | |
| dict(type='LoadAnnotations', with_bbox=True, with_mask=True), | |
| dict(type='RandomFlip', flip_ratio=0.5), | |
| dict(type='AutoAugment', | |
| policies=[ | |
| [ | |
| dict(type='Resize', | |
| img_scale=[(480, 1333), (512, 1333), (544, 1333), (576, 1333), | |
| (608, 1333), (640, 1333), (672, 1333), (704, 1333), | |
| (736, 1333), (768, 1333), (800, 1333)], | |
| multiscale_mode='value', | |
| keep_ratio=True) | |
| ], | |
| [ | |
| dict(type='Resize', | |
| img_scale=[(400, 1333), (500, 1333), (600, 1333)], | |
| multiscale_mode='value', | |
| keep_ratio=True), | |
| dict(type='RandomCrop', | |
| crop_type='absolute_range', | |
| crop_size=(384, 600), | |
| allow_negative_crop=True), | |
| dict(type='Resize', | |
| img_scale=[(480, 1333), (512, 1333), (544, 1333), | |
| (576, 1333), (608, 1333), (640, 1333), | |
| (672, 1333), (704, 1333), (736, 1333), | |
| (768, 1333), (800, 1333)], | |
| multiscale_mode='value', | |
| override=True, | |
| keep_ratio=True) | |
| ] | |
| ]), | |
| dict(type='Normalize', **img_norm_cfg), | |
| dict(type='Pad', size_divisor=32), | |
| dict(type='DefaultFormatBundle'), | |
| dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks']), | |
| ] | |
| data = dict(train=dict(pipeline=train_pipeline)) | |
| optimizer = dict(_delete_=True, type='AdamW', lr=0.0001, betas=(0.9, 0.999), weight_decay=0.05, | |
| paramwise_cfg=dict(custom_keys={'absolute_pos_embed': dict(decay_mult=0.), | |
| 'relative_position_bias_table': dict(decay_mult=0.), | |
| 'norm': dict(decay_mult=0.)})) | |
| lr_config = dict(step=[8, 11]) | |
| runner = dict(type='EpochBasedRunnerAmp', max_epochs=12) | |
| # do not use mmdet version fp16 | |
| fp16 = None | |
| optimizer_config = dict( | |
| type="DistOptimizerHook", | |
| update_interval=1, | |
| grad_clip=None, | |
| coalesce=True, | |
| bucket_size_mb=-1, | |
| use_fp16=True, | |
| ) | |