from pointcept.datasets.preprocessing.scannet.meta_data.scannet200_constants import ( CLASS_LABELS_200, ) _base_ = ["../_base_/default_runtime.py"] # misc custom setting batch_size = 8 # bs: total bs in all gpus mix_prob = 0 empty_cache = False enable_amp = True find_unused_parameters = True # model settings model = dict( type="DefaultSegmentor", backbone=dict( type="ST-v1m2", in_channels=9, num_classes=200, channels=(48, 96, 192, 384, 384), num_heads=(6, 12, 24, 24), depths=(3, 9, 3, 3), window_size=(0.2, 0.4, 0.8, 1.6), quant_size=(0.01, 0.02, 0.04, 0.08), mlp_expend_ratio=4.0, down_ratio=0.25, down_num_sample=16, kp_ball_radius=2.5 * 0.02, kp_max_neighbor=34, kp_grid_size=0.02, kp_sigma=1.0, drop_path_rate=0.2, rel_query=True, rel_key=True, rel_value=True, qkv_bias=True, stem=True, ), criteria=[dict(type="CrossEntropyLoss", loss_weight=1.0, ignore_index=-1)], ) # scheduler settings epoch = 600 optimizer = dict(type="AdamW", lr=0.006, weight_decay=0.05) scheduler = dict(type="MultiStepLR", milestones=[0.6, 0.8], gamma=0.1) # dataset settings dataset_type = "ScanNet200Dataset" data_root = "data/scannet" data = dict( num_classes=200, ignore_index=-1, names=CLASS_LABELS_200, 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_min_coord=True, ), dict(type="SphereCrop", point_max=100000, mode="random"), dict(type="CenterShift", apply_z=False), dict(type="NormalizeColor"), dict(type="ShufflePoint"), dict(type="ToTensor"), dict( type="Collect", keys=("coord", "segment"), feat_keys=("coord", "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_min_coord=True, ), dict(type="CenterShift", apply_z=False), dict(type="NormalizeColor"), dict(type="ToTensor"), dict( type="Collect", keys=("coord", "segment"), feat_keys=("coord", "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", keys=("coord", "color", "normal"), ), crop=None, post_transform=[ dict(type="CenterShift", apply_z=False), dict(type="ToTensor"), dict( type="Collect", keys=("coord", "index"), feat_keys=("coord", "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)], ], ), ), )