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WaffleIron-48-256__kitti.yaml
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WaffleIron-48-256__kitti.yaml
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waffleiron: # Architecture of the backbone
nb_channels: 256 # Define F = the feature size = width of the WaffleIron
depth: 48 # Define L = the depth on the network
fov_xyz: # Define the FOV in meters
- - -50 # min value on x-axis: -50 m
- -50 # min value on y-axis: -50 m
- -3 # min value on z-axis: -5 m
- - 50 # max value on x-axis: 50 m
- 50 # max value on y-axis: 50 m
- 2 # max value on z-axis: 5 m
dim_proj: # Define the sequence of projection (which is then repeated sequentially until \ell = L)
- 2 # Project along the z axis at \ell = 1 (and then the same at all layer)
- 1 # At \ell = 2, project along y
- 0 # At \ell = 1, project along x
grids_size: # Define here the size of the 2D grids
- [250, 250]
- [250, 12]
- [250, 12]
drop: 0.2
classif: # Architecture of the classifcation layer, after WaffleIron
nb_class: 19 # Number of classes on nuscenes (after removing the ignore class)
embedding: # Architecture of the embedding layer, before WaffleIron
input_feat: # List of features on each point
- "intensity"
- "xyz"
- "radius"
size_input: 5 # Input feature size on each point
neighbors: 16 # Neighborhood for embedding layer
voxel_size: 0.1 # Voxel size for downsampling point cloud in pre-processing
dataloader:
batch_size: 4
num_workers: 12
max_points: 20000
augmentations:
rotation:
- [2, 6]
flip_xy: null
scale:
- [4, 5, 6, 7]
- 0.1
instance_cutmix: True # Will apply Cutmix *and* Polarmix
loss:
lovasz: 1.0
optim:
lr: .001
weight_decay: 0.003
scheduler:
min_lr: 0.00001
max_epoch: 45
epoch_warmup: 4