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dd3d_dla_34_kitti.yml
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_base_: '../_base_/kitti_mono.yml'
batch_size: 8 #total bs 32
iters: 50000
train_dataset:
transforms:
- type: LoadImage
reader: pillow
to_chw: False
to_rgb: False
- type: ResizeShortestEdge
short_edge_length: [288, 304, 320, 336, 352, 368, 384, 400, 416, 448, 480, 512, 544, 576]
max_size: 10000
sample_style: choice
- type: ToVisionBasedBox
- type: RandomHorizontalFlip
input_type: floating_point_coordinates
- type: RandomBrightness
intensity_min: 0.8
intensity_max: 1.2
- type: RandomSaturation
intensity_min: 0.8
intensity_max: 1.2
- type: RandomContrast
intensity_min: 0.8
intensity_max: 1.2
class_names: ["Car", "Pedestrian", "Cyclist", "Van", "Person_sitting"]
CLASS_MAP: {'Car': 0, 'Pedestrian': 1, 'Cyclist': 2, 'Van': 3, 'Person_sitting': 4}
class_balanced_sampling: True
val_dataset:
transforms:
- type: LoadImage
reader: pillow
to_chw: False
to_rgb: False
- type: ResizeShortestEdge
short_edge_length: [384]
max_size: 10000
sample_style: choice
- type: ToVisionBasedBox
class_names: ["Car", "Pedestrian", "Cyclist", "Van", "Person_sitting"]
CLASS_MAP: {'Car': 0, 'Pedestrian': 1, 'Cyclist': 2, 'Van': 3, 'Person_sitting': 4}
optimizer:
type: Momentum
momentum: 0.9
use_nesterov: False
weight_decay: 0.0001
lr_scheduler:
type: MultiStepDecay
milestones: [43000, 48000]
learning_rate: 0.001
gamma: 0.1
model:
type: DD3D
backbone:
type: DLABase34
norm_type: 'frozen_bn'
out_features: [3, 4, 5]
feature_locations_offset: "none"
fpn:
type: FPN
in_strides: [8, 16, 32]
in_channels: [128, 256, 512]
out_channel: 256
norm: 'FrozenBN'
top_block:
type: LastLevelP6P7
in_channels: 256
out_channels: 256
in_feature: 'p5'
fuse_type: "sum"
fcos2d_head:
type: FCOS2DHead
in_strides: [8, 16, 32, 64, 128]
in_channels: [256, 256, 256, 256, 256]
num_classes: 5
use_scale: True
box2d_scale_init_factor: 1.0
version: "v2"
num_cls_convs: 4
num_box_convs: 4
use_deformable: False
norm: "BN"
fcos2d_loss:
type: FCOS2DLoss
alpha: 0.25
gamma: 2.0
loc_loss_type: 'giou'
num_classes: 5
fcos2d_inference:
type: FCOS2DInference
thresh_with_ctr: True
pre_nms_thresh: 0.05
pre_nms_topk: 1000
post_nms_topk: 100
nms_thresh: 0.75
num_classes: 5
fcos3d_head:
type: FCOS3DHead
in_strides: [8, 16, 32, 64, 128]
in_channels: [256, 256, 256, 256, 256]
num_classes: 5
use_scale: True
depth_scale_init_factor: 0.3
proj_ctr_scale_init_factor: 1.0
use_per_level_predictors: False
mean_depth_per_level: [32.594, 15.178, 8.424, 5.004, 4.662]
std_depth_per_level: [14.682, 7.139, 4.345, 2.399, 2.587]
num_convs: 4
use_deformable: False
norm: 'FrozenBN'
class_agnostic_box3d: False
per_level_predictors: False
fcos3d_loss:
type: FCOS3DLoss
canon_box_sizes: [[1.61876949, 3.89154523, 1.52969237], # Car
[0.62806586, 0.82038497, 1.76784787], # Pedestrian
[0.56898187, 1.77149234, 1.7237099], # Cyclist
[1.9134491 , 5.15499603, 2.18998422], # Van
[2.61168401, 9.22692319, 3.36492722], # Truck
[0.5390196 , 1.08098042, 1.28392158], # Person_sitting
[2.36044838, 15.56991038, 3.5289238], # Tram
[1.24489164, 2.51495357, 1.61402478], # Misc
] # (width, length, height)
min_depth: 0.1
max_depth: 80.0
predict_allocentric_rot: True
scale_depth_by_focal_lengths: True
scale_depth_by_focal_lengths_factor: 500.0
predict_distance: False
smooth_l1_loss_beta: 0.05
max_loss_per_group: 20.0
box3d_loss_weight: 2.0
conf3d_loss_weight: 1.0
conf_3d_temperature: 1.0
num_classes: 5
class_agnostic: False
fcos3d_inference:
type: FCOS3DInference
canon_box_sizes: [[1.61876949, 3.89154523, 1.52969237], # Car
[0.62806586, 0.82038497, 1.76784787], # Pedestrian
[0.56898187, 1.77149234, 1.7237099], # Cyclist
[1.9134491 , 5.15499603, 2.18998422], # Van
[2.61168401, 9.22692319, 3.36492722], # Truck
[0.5390196 , 1.08098042, 1.28392158], # Person_sitting
[2.36044838, 15.56991038, 3.5289238], # Tram
[1.24489164, 2.51495357, 1.61402478], # Misc
] # (width, length, height)
min_depth: 0.1
max_depth: 80.0
predict_allocentric_rot: True
scale_depth_by_focal_lengths: True
scale_depth_by_focal_lengths_factor: 500.0
predict_distance: False
num_classes: 5
class_agnostic: False
prepare_targets:
type: DD3DTargetPreparer
input_strides: [8, 16, 32, 64, 128]
num_classes: 5
center_sample: True
radius: 1.5
dd3d_on: True
sizes_of_interest: [64, 128, 256, 512]
do_nms: True
nusc_sample_aggregate: False
num_classes: 5
pixel_mean: [103.53, 116.28, 123.675]
pixel_std: [57.375, 57.12, 58.395]
input_strides: [8, 16, 32, 64, 128]
size_divisibility: 128