_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="PT-v2m2", in_channels=9, num_classes=25, patch_embed_depth=1, patch_embed_channels=48, patch_embed_groups=6, patch_embed_neighbours=8, enc_depths=(2, 2, 6, 2), enc_channels=(96, 192, 384, 512), enc_groups=(12, 24, 48, 64), enc_neighbours=(16, 16, 16, 16), dec_depths=(1, 1, 1, 1), dec_channels=(48, 96, 192, 384), dec_groups=(6, 12, 24, 48), dec_neighbours=(16, 16, 16, 16), grid_sizes=(0.06, 0.15, 0.375, 0.9375), # x3, x2.5, x2.5, x2.5 attn_qkv_bias=True, pe_multiplier=False, pe_bias=True, attn_drop_rate=0.0, drop_path_rate=0.3, enable_checkpoint=False, unpool_backend="map", # map / interp ), criteria=[dict(type="CrossEntropyLoss", loss_weight=1.0, ignore_index=-1)], ) # scheduler settings epoch = 100 optimizer = dict(type="SGD", lr=0.05, momentum=0.9, weight_decay=0.0001, nesterov=True) scheduler = dict( type="OneCycleLR", max_lr=optimizer["lr"], pct_start=0.05, anneal_strategy="cos", div_factor=10.0, final_div_factor=10000.0, ) # 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, ), 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=("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_grid_coord=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=("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", return_grid_coord=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=("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)], ], ), ), )