train_packnet_san_kitti.yaml

arch:
    validate_first: True
model:
    name: 'SemiSupCompletionModel'
    loss:
        supervised_method: 'sparse-silog'
        supervised_num_scales: 1
        supervised_loss_weight: 1.0
    optimizer:
        name: 'Adam'
        depth:
            lr: 0.0001
        pose:
            lr: 0.0001
    scheduler:
        name: 'StepLR'
        step_size: 30
        gamma: 0.5
    depth_net:
        name: 'PackNetSAN01'
        version: '1A'
        dropout: 0.5
    params:
        crop: 'garg'
        min_depth: 0.0
        max_depth: 80.0
        scale_output: 'top-center'
datasets:
    augmentation:
        crop_train_borders: (-352, 0, 0.5, 1216)
        crop_eval_borders: (-352, 0, 0.5, 1216)
    train:
        batch_size: 1
        dataset: ['KITTI']
        path: ['/mnt/fsx/KITTI_raw']
        split: ['data_splits/eigen_zhou_files.txt']
        input_depth_type: ['velodyne']
        depth_type: ['groundtruth']
        repeat: [2]
    validation:
        dataset: ['KITTI']
        path: ['/mnt/fsx/KITTI_raw']
        split: ['data_splits/eigen_test_files.txt',
                'data_splits/eigen_test_files.txt']
        input_depth_type: ['velodyne','']
        depth_type: ['groundtruth','groundtruth']