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_base_ = [ |
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'../_base_/models/fcaf3d.py', '../_base_/default_runtime.py', |
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'../_base_/datasets/scannet-3d.py' |
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] |
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n_points = 100000 |
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backend_args = None |
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|
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train_pipeline = [ |
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dict( |
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type='LoadPointsFromFile', |
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coord_type='DEPTH', |
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shift_height=False, |
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use_color=True, |
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load_dim=6, |
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use_dim=[0, 1, 2, 3, 4, 5], |
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backend_args=backend_args), |
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dict(type='LoadAnnotations3D'), |
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dict(type='GlobalAlignment', rotation_axis=2), |
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dict(type='PointSample', num_points=n_points), |
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dict( |
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type='RandomFlip3D', |
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sync_2d=False, |
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flip_ratio_bev_horizontal=0.5, |
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flip_ratio_bev_vertical=0.5), |
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dict( |
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type='GlobalRotScaleTrans', |
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rot_range=[-0.087266, 0.087266], |
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scale_ratio_range=[.9, 1.1], |
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translation_std=[.1, .1, .1], |
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shift_height=False), |
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dict(type='NormalizePointsColor', color_mean=None), |
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dict( |
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type='Pack3DDetInputs', |
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keys=['points', 'gt_bboxes_3d', 'gt_labels_3d']) |
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] |
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test_pipeline = [ |
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dict( |
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type='LoadPointsFromFile', |
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coord_type='DEPTH', |
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shift_height=False, |
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use_color=True, |
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load_dim=6, |
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use_dim=[0, 1, 2, 3, 4, 5], |
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backend_args=backend_args), |
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dict(type='GlobalAlignment', rotation_axis=2), |
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dict( |
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type='MultiScaleFlipAug3D', |
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img_scale=(1333, 800), |
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pts_scale_ratio=1, |
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flip=False, |
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transforms=[ |
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dict( |
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type='GlobalRotScaleTrans', |
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rot_range=[0, 0], |
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scale_ratio_range=[1., 1.], |
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translation_std=[0, 0, 0]), |
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dict( |
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type='RandomFlip3D', |
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sync_2d=False, |
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flip_ratio_bev_horizontal=0.5, |
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flip_ratio_bev_vertical=0.5), |
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dict(type='PointSample', num_points=n_points), |
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dict(type='NormalizePointsColor', color_mean=None), |
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]), |
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dict(type='Pack3DDetInputs', keys=['points']) |
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] |
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train_dataloader = dict( |
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dataset=dict( |
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type='RepeatDataset', |
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times=10, |
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dataset=dict(pipeline=train_pipeline, filter_empty_gt=True))) |
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val_dataloader = dict(dataset=dict(pipeline=test_pipeline)) |
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test_dataloader = val_dataloader |
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|
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optim_wrapper = dict( |
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type='OptimWrapper', |
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optimizer=dict(type='AdamW', lr=0.001, weight_decay=0.0001), |
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clip_grad=dict(max_norm=10, norm_type=2)) |
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|
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param_scheduler = dict( |
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type='MultiStepLR', |
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begin=0, |
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end=12, |
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by_epoch=True, |
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milestones=[8, 11], |
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gamma=0.1) |
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|
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custom_hooks = [dict(type='EmptyCacheHook', after_iter=True)] |
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|
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train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=12, val_interval=12) |
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val_cfg = dict(type='ValLoop') |
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test_cfg = dict(type='TestLoop') |
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