65 lines
1.7 KiB
YAML
65 lines
1.7 KiB
YAML
gt_paste_stop_epoch: 15
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model:
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heads:
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object:
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type: CenterHead
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in_channels: null
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train_cfg:
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point_cloud_range: ${point_cloud_range}
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grid_size: [1024, 1024, 1]
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voxel_size: ${voxel_size}
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out_size_factor: 8
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dense_reg: 1
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gaussian_overlap: 0.1
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max_objs: 500
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min_radius: 2
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code_weights: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.2, 0.2]
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test_cfg:
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post_center_limit_range: [-61.2, -61.2, -10.0, 61.2, 61.2, 10.0]
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max_per_img: 500
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max_pool_nms: false
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min_radius: [4, 12, 10, 1, 0.85, 0.175]
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score_threshold: 0.1
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out_size_factor: 8
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voxel_size: ${voxel_size[:2]}
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nms_type: rotate
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pre_max_size: 1000
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post_max_size: 83
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nms_thr: 0.2
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tasks:
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- ["car"]
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- ["truck", "construction_vehicle"]
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- ["bus", "trailer"]
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- ["barrier"]
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- ["motorcycle", "bicycle"]
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- ["pedestrian", "traffic_cone"]
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common_heads:
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reg: [2, 2]
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height: [1, 2]
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dim: [3, 2]
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rot: [2, 2]
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vel: [2, 2]
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share_conv_channel: 64
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bbox_coder:
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type: CenterPointBBoxCoder
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pc_range: ${point_cloud_range}
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post_center_range: [-61.2, -61.2, -10.0, 61.2, 61.2, 10.0]
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max_num: 500
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score_threshold: 0.1
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out_size_factor: 8
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voxel_size: ${voxel_size[:2]}
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code_size: 9
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separate_head:
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type: SeparateHead
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init_bias: -2.19
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final_kernel: 3
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loss_cls:
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type: GaussianFocalLoss
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reduction: mean
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loss_bbox:
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type: L1Loss
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reduction: mean
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loss_weight: 0.25
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norm_bbox: true
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