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semseg-spunet-v1m1-0-base.py
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semseg-spunet-v1m1-0-base.py
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_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="SpUNet-v1m1",
in_channels=6,
num_classes=20,
channels=(32, 64, 128, 256, 256, 128, 96, 96),
layers=(2, 3, 4, 6, 2, 2, 2, 2),
),
criteria=[dict(type="CrossEntropyLoss", loss_weight=1.0, ignore_index=-1)],
)
# scheduler settings
epoch = 800
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 = "ScanNetDataset"
data_root = "data/scannet"
data = dict(
num_classes=20,
ignore_index=-1,
names=[
"wall",
"floor",
"cabinet",
"bed",
"chair",
"sofa",
"table",
"door",
"window",
"bookshelf",
"picture",
"counter",
"desk",
"curtain",
"refridgerator",
"shower curtain",
"toilet",
"sink",
"bathtub",
"otherfurniture",
],
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", 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", "grid_coord", "segment"),
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,
),
# 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"),
),
],
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=("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)],
],
),
),
)