_base_ = ["../_base_/default_runtime.py"] # misc custom setting batch_size = 12 # bs: total bs in all gpus mix_prob = 0.8 empty_cache = False enable_amp = True # model settings model = dict( type="DefaultSegmentor", backbone=dict( type="Swin3D-v1m1", in_channels=9, num_classes=25, base_grid_size=0.02, depths=[2, 4, 9, 4, 4], channels=[80, 160, 320, 640, 640], num_heads=[10, 10, 20, 40, 40], window_sizes=[5, 7, 7, 7, 7], quant_size=4, drop_path_rate=0.3, up_k=3, num_layers=5, stem_transformer=True, down_stride=3, upsample="linear_attn", knn_down=True, cRSE="XYZ_RGB_NORM", fp16_mode=1, ), criteria=[dict(type="CrossEntropyLoss", loss_weight=1.0, ignore_index=-1)], ) # scheduler settings epoch = 100 optimizer = dict(type="AdamW", lr=0.008, weight_decay=0.05) scheduler = dict( type="OneCycleLR", max_lr=[0.008, 0.0008], pct_start=0.05, anneal_strategy="cos", div_factor=10.0, final_div_factor=1000.0, ) param_dicts = [dict(keyword="blocks", lr=0.0008)] # dataset settings dataset_type = "Structured3DDataset" data_root = "data/structured3d" data = dict( num_classes=25, ignore_index=-1, names=( "wall", "floor", "cabinet", "bed", "chair", "sofa", "table", "door", "window", "picture", "desk", "shelves", "curtain", "dresser", "pillow", "mirror", "ceiling", "refrigerator", "television", "nightstand", "sink", "lamp", "otherstructure", "otherfurniture", "otherprop", ), train=dict( type=dataset_type, split="train", data_root=data_root, transform=[ dict(type="CenterShift", apply_z=True), dict( type="RandomDropout", dropout_ratio=0.2, dropout_application_ratio=0.2 ), # dict(type="RandomRotateTargetAngle", angle=(1/2, 1, 3/2), center=[0, 0, 0], axis="z", p=0.75), dict(type="RandomRotate", angle=[-1, 1], axis="z", center=[0, 0, 0], p=0.5), dict(type="RandomRotate", angle=[-1 / 64, 1 / 64], axis="x", p=0.5), dict(type="RandomRotate", angle=[-1 / 64, 1 / 64], axis="y", p=0.5), dict(type="RandomScale", scale=[0.9, 1.1]), # dict(type="RandomShift", shift=[0.2, 0.2, 0.2]), dict(type="RandomFlip", p=0.5), dict(type="RandomJitter", sigma=0.005, clip=0.02), dict(type="ElasticDistortion", distortion_params=[[0.2, 0.4], [0.8, 1.6]]), dict(type="ChromaticAutoContrast", p=0.2, blend_factor=None), dict(type="ChromaticTranslation", p=0.95, ratio=0.05), dict(type="ChromaticJitter", p=0.95, std=0.05), # dict(type="HueSaturationTranslation", hue_max=0.2, saturation_max=0.2), # dict(type="RandomColorDrop", p=0.2, color_augment=0.0), dict( type="GridSample", grid_size=0.02, hash_type="fnv", mode="train", return_grid_coord=True, return_displacement=True, ), dict(type="SphereCrop", sample_rate=0.8, mode="random"), dict(type="SphereCrop", point_max=120000, mode="random"), dict(type="CenterShift", apply_z=False), dict(type="NormalizeColor"), dict(type="ShufflePoint"), dict(type="ToTensor"), dict( type="Collect", keys=("coord", "grid_coord", "segment"), feat_keys=("color", "normal", "displacement"), coord_feat_keys=("color", "normal"), ), ], test_mode=False, ), val=dict( type=dataset_type, split="val", data_root=data_root, transform=[ dict(type="CenterShift", apply_z=True), dict( type="GridSample", grid_size=0.02, hash_type="fnv", mode="train", return_grid_coord=True, return_displacement=True, ), # dict(type="SphereCrop", point_max=1000000, mode="center"), dict(type="CenterShift", apply_z=False), dict(type="NormalizeColor"), dict(type="ToTensor"), dict( type="Collect", keys=("coord", "grid_coord", "segment"), feat_keys=("color", "normal", "displacement"), coord_feat_keys=("color", "normal"), ), ], test_mode=False, ), test=dict( type=dataset_type, split="val", data_root=data_root, transform=[ dict(type="CenterShift", apply_z=True), dict(type="NormalizeColor"), ], test_mode=True, test_cfg=dict( voxelize=dict( type="GridSample", grid_size=0.02, hash_type="fnv", mode="test", return_grid_coord=True, return_displacement=True, keys=("coord", "color", "normal"), ), crop=None, post_transform=[ dict(type="CenterShift", apply_z=False), dict(type="ToTensor"), dict( type="Collect", keys=("coord", "grid_coord", "index"), feat_keys=("color", "normal", "displacement"), coord_feat_keys=("color", "normal"), ), ], aug_transform=[ [ dict( type="RandomRotateTargetAngle", angle=[0], axis="z", center=[0, 0, 0], p=1, ) ], [ dict( type="RandomRotateTargetAngle", angle=[1 / 2], axis="z", center=[0, 0, 0], p=1, ) ], [ dict( type="RandomRotateTargetAngle", angle=[1], axis="z", center=[0, 0, 0], p=1, ) ], [ dict( type="RandomRotateTargetAngle", angle=[3 / 2], axis="z", center=[0, 0, 0], p=1, ) ], [ dict( type="RandomRotateTargetAngle", angle=[0], axis="z", center=[0, 0, 0], p=1, ), dict(type="RandomScale", scale=[0.95, 0.95]), ], [ dict( type="RandomRotateTargetAngle", angle=[1 / 2], axis="z", center=[0, 0, 0], p=1, ), dict(type="RandomScale", scale=[0.95, 0.95]), ], [ dict( type="RandomRotateTargetAngle", angle=[1], axis="z", center=[0, 0, 0], p=1, ), dict(type="RandomScale", scale=[0.95, 0.95]), ], [ dict( type="RandomRotateTargetAngle", angle=[3 / 2], axis="z", center=[0, 0, 0], p=1, ), dict(type="RandomScale", scale=[0.95, 0.95]), ], [ dict( type="RandomRotateTargetAngle", angle=[0], axis="z", center=[0, 0, 0], p=1, ), dict(type="RandomScale", scale=[1.05, 1.05]), ], [ dict( type="RandomRotateTargetAngle", angle=[1 / 2], axis="z", center=[0, 0, 0], p=1, ), dict(type="RandomScale", scale=[1.05, 1.05]), ], [ dict( type="RandomRotateTargetAngle", angle=[1], axis="z", center=[0, 0, 0], p=1, ), dict(type="RandomScale", scale=[1.05, 1.05]), ], [ dict( type="RandomRotateTargetAngle", angle=[3 / 2], axis="z", center=[0, 0, 0], p=1, ), dict(type="RandomScale", scale=[1.05, 1.05]), ], [dict(type="RandomFlip", p=1)], ], ), ), )