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dataset:
root: "/path/to/GridNet-HD"
split_file: "/path/to/GridNet-HD/split.json"
n_classes: 11
voxel_size: 0.05 # for KDTree
pre-processing_num_workers: 8
max_point_per_class: 1000000
class_map:
- keys: [0, 1, 2, 3, 4] # original values
value: 0 # new value (remap value)
- keys: [5]
value: 1
- keys: [6, 7]
value: 2
- keys: [8, 9, 10, 11]
value: 3
- keys: [14]
value: 4
- keys: [15]
value: 5
- keys: [16]
value: 6
- keys: [17, 18]
value: 7
- keys: [19]
value: 8
- keys: [20]
value: 9
- keys: [21]
value: 10
- keys: [12, 13, 255]
value: 255
training:
batch_size: 8192
epochs: 10
learning_rate: 0.001
weight_decay: 0.0001
device: "cuda"
lr_step_size: 4 # scheduler every 4 epochs
lr_gamma: 0.1 # decay factor
model:
hidden_dims: [128, 256, 128, 64]
ignore_index: 255
logging:
save_dir: "outputs/run"
save_freq: 5
wandb:
project: "GridNet-HD_MLP_late_fusion"
entity: "your-team"