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caddn_ocrnet_hrnet_w18_kitti.yml
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batch_size: 4
iters: 74240 # 928*80
sync_bn: true
train_dataset:
type: KittiDepthDataset
dataset_root: data/kitti
point_cloud_range: [2, -30.08, -3.0, 46.8, 30.08, 1.0]
depth_downsample_factor: 4
voxel_size: [0.16, 0.16, 0.16]
class_names: ['Car', 'Pedestrian', 'Cyclist']
mode: train
val_dataset:
type: KittiDepthDataset
dataset_root: data/kitti
point_cloud_range: [2, -30.08, -3.0, 46.8, 30.08, 1.0]
depth_downsample_factor: 4
voxel_size: [0.16, 0.16, 0.16]
class_names: ['Car', 'Pedestrian', 'Cyclist']
mode: val
optimizer:
type: AdamWOnecycle
clip_grad_by_norm: 10.0
beta1: 0.95
beta2: 0.99
weight_decay: 0.01
lr_scheduler:
type: OneCycle
total_step: 74240 # 928 * 80
lr_max: 0.001
moms: [0.95, 0.85]
div_factor: 10
pct_start: 0.4
model:
type: CADDN
pretrained: "https://bj.bcebos.com/paddle3d/pretrained/hrnet18.pdparams"
backbone_3d:
type: HRNet_W18
class_head:
type: OCRHead
num_classes: 81
backbone_indices: [1]
in_channels: [270]
align_corners: False
bev_cfg:
layer_nums: [10, 10, 10]
layer_strides: [2, 2, 2]
num_filters: [64, 128, 256]
upsample_strides: [1, 2, 4]
num_upsample_filters: [128, 128, 128]
input_channels: 64
dense_head:
type: AnchorHeadSingle
model_cfg:
class_agnostic: False
use_direction_classifier: True
dir_offset: 0.78539
dir_limit_offset: 0.0
input_channels: 384
point_cloud_range: [2, -30.08, -3.0, 46.8, 30.08, 1.0]
class_names: ['Car', 'Pedestrian', 'Cyclist']
predict_boxes_when_training: False
voxel_size: [0.16, 0.16, 0.16]
anchor_generator_cfg: [
{
'class_name': 'Car',
'anchor_sizes': [[3.9, 1.6, 1.56]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-1.78],
'align_center': False,
'feature_map_stride': 2,
'matched_threshold': 0.6,
'unmatched_threshold': 0.45
},
{
'class_name': 'Pedestrian',
'anchor_sizes': [[0.8, 0.6, 1.73]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-0.6],
'align_center': False,
'feature_map_stride': 2,
'matched_threshold': 0.5,
'unmatched_threshold': 0.35
},
{
'class_name': 'Cyclist',
'anchor_sizes': [[1.76, 0.6, 1.73]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-0.6],
'align_center': False,
'feature_map_stride': 2,
'matched_threshold': 0.5,
'unmatched_threshold': 0.35
}
]
anchor_target_cfg:
pos_fraction: -1.0
sample_size: 512
norm_by_num_examples: False
match_height: False
num_dir_bins: 2
loss_weights:
cls_weight: 1.0
loc_weight: 2.0
dir_weight: 0.2
code_weights: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
map_to_bev_cfg:
in_channels: 1600
out_channels: 64
kernel_size: 1
stride: 1
bias_attr: False
padding: 0
ffe_cfg:
channel_reduce_cfg:
in_channels: 256
out_channels: 64
kernel_size: 1
stride: 1
bias_attr: False
padding: 0
downsample_factor: 4
ddn_loss:
weight: 3.0
alpha: 0.25
beta: 2.0
fg_weight: 13
bg_weight: 1
f2v_cfg:
pc_range: [2, -30.08, -3.0, 46.8, 30.08, 1.0]
voxel_size: [0.16, 0.16, 0.16]
sample_cfg:
mode: bilinear
padding_mode: zeros
disc_cfg:
mode: LID
num_bins: 80
depth_min: 2.0
depth_max: 46.8
post_process_cfg:
recall_thresh_list: [0.3, 0.5, 0.7]
score_thresh: 0.1
eval_metric: kitti
nms_config:
nms_thresh: 0.01
nms_pre_maxsize: 4096
nms_post_maxsize: 500
export:
transforms:
- type: LoadImage
to_chw: False
to_rgb: True
- type: Normalize
mean: [0, 0, 0]
std: [1, 1, 1]