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_base_ = [ |
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'../_base_/models/occ_mask_rcnn_swin_fpn.py', |
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'../_base_/datasets/walt_vehicle.py', |
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'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py' |
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] |
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model = dict( |
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backbone=dict( |
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embed_dim=96, |
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depths=[2, 2, 6, 2], |
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num_heads=[3, 6, 12, 24], |
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window_size=7, |
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ape=False, |
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drop_path_rate=0.1, |
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patch_norm=True, |
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use_checkpoint=False |
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), |
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neck=dict(in_channels=[96, 192, 384, 768])) |
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img_norm_cfg = dict( |
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mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) |
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train_pipeline = [ |
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dict(type='LoadImageFromFile'), |
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dict(type='LoadAnnotations', with_bbox=True, with_mask=True), |
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dict(type='RandomFlip', flip_ratio=0.5), |
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dict(type='AutoAugment', |
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policies=[ |
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[ |
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dict(type='Resize', |
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img_scale=[(480, 1333), (512, 1333), (544, 1333), (576, 1333), |
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(608, 1333), (640, 1333), (672, 1333), (704, 1333), |
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(736, 1333), (768, 1333), (800, 1333)], |
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multiscale_mode='value', |
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keep_ratio=True) |
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], |
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[ |
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dict(type='Resize', |
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img_scale=[(400, 1333), (500, 1333), (600, 1333)], |
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multiscale_mode='value', |
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keep_ratio=True), |
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dict(type='RandomCrop', |
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crop_type='absolute_range', |
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crop_size=(384, 600), |
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allow_negative_crop=True), |
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dict(type='Resize', |
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img_scale=[(480, 1333), (512, 1333), (544, 1333), |
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(576, 1333), (608, 1333), (640, 1333), |
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(672, 1333), (704, 1333), (736, 1333), |
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(768, 1333), (800, 1333)], |
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multiscale_mode='value', |
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override=True, |
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keep_ratio=True) |
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] |
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]), |
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dict(type='Normalize', **img_norm_cfg), |
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dict(type='Pad', size_divisor=32), |
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dict(type='DefaultFormatBundle'), |
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dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks']), |
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] |
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data = dict(train=dict(pipeline=train_pipeline)) |
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optimizer = dict(_delete_=True, type='AdamW', lr=0.0001, betas=(0.9, 0.999), weight_decay=0.05, |
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paramwise_cfg=dict(custom_keys={'absolute_pos_embed': dict(decay_mult=0.), |
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'relative_position_bias_table': dict(decay_mult=0.), |
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'norm': dict(decay_mult=0.)})) |
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lr_config = dict(step=[8, 11]) |
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runner = dict(type='EpochBasedRunnerAmp', max_epochs=12) |
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fp16 = None |
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optimizer_config = dict( |
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type="DistOptimizerHook", |
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update_interval=1, |
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grad_clip=None, |
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coalesce=True, |
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bucket_size_mb=-1, |
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use_fp16=True, |
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) |
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