63 lines
1.4 KiB
YAML
63 lines
1.4 KiB
YAML
model:
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encoders:
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camera:
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neck:
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type: GeneralizedLSSFPN
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in_channels: [512, 1024, 2048]
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out_channels: 256
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start_level: 0
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num_outs: 3
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norm_cfg:
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type: BN2d
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requires_grad: true
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act_cfg:
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type: ReLU
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inplace: true
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upsample_cfg:
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mode: bilinear
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align_corners: false
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vtransform:
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type: DepthLSSTransform
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in_channels: 256
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out_channels: 80
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image_size: ${image_size}
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feature_size: ${[image_size[0] // 8, image_size[1] // 8]}
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xbound: [-51.2, 51.2, 0.4]
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ybound: [-51.2, 51.2, 0.4]
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zbound: [-10.0, 10.0, 20.0]
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dbound: [1.0, 60.0, 0.5]
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downsample: 2
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lidar:
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voxelize:
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max_num_points: 10
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point_cloud_range: ${point_cloud_range}
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voxel_size: ${voxel_size}
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max_voxels: [90000, 120000]
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backbone:
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type: SparseEncoder
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in_channels: 5
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sparse_shape: [1024, 1024, 41]
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output_channels: 128
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order:
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- conv
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- norm
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- act
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encoder_channels:
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- [16, 16, 32]
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- [32, 32, 64]
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- [64, 64, 128]
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- [128, 128]
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encoder_paddings:
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- [0, 0, 1]
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- [0, 0, 1]
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- [0, 0, [1, 1, 0]]
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- [0, 0]
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block_type: basicblock
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lr_config: null
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optimizer:
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lr: 2.0e-4
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max_epochs: 6
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