gwcnet_sceneflow.yaml

DATA_CONFIG:
    DATA_INFOS:
        -   DATASET: SceneFlowDataset
            DATA_SPLIT: {
                TRAINING: ./data/SceneFlow/sceneflow_finalpass_train.txt,
                EVALUATING: ./data/SceneFlow/sceneflow_finalpass_test.txt,
                TESTING: ./data/SceneFlow/sceneflow_finalpass_test.txt
            }
            DATA_PATH: /yourpath/SceneFlow
            RETURN_RIGHT_DISP: false

    DATA_TRANSFORM:
        TRAINING:
            - { NAME: RandomCrop, SIZE: [ 256, 512 ], Y_JITTER: false }
            - { NAME: TransposeImage }
            - { NAME: ToTensor }
            - { NAME: NormalizeImage, MEAN: [ 0.485, 0.456, 0.406 ], STD: [ 0.229, 0.224, 0.225 ] }
        EVALUATING:
            - { NAME: RightBottomCrop, SIZE: [ 512, 960 ] }
            - { NAME: TransposeImage }
            - { NAME: ToTensor }
            - { NAME: NormalizeImage, MEAN: [ 0.485, 0.456, 0.406 ], STD: [ 0.229, 0.224, 0.225 ] }

MODEL:
    NAME: GwcNet
    MAX_DISP: &max_disp 192
    USE_CONCAT_VOLUME: true
    CONCAT_CHANNELS: 12
    DOWNSAMPLE: 4
    NUM_GROUPS: 40
    FIND_UNUSED_PARAMETERS: false
    CKPT: -1
    PRETRAINED_MODEL: ''

OPTIMIZATION:
    BATCH_SIZE_PER_GPU: 4
    FREEZE_BN: false
    SYNC_BN: true
    AMP: false
    NUM_EPOCHS: 20

    OPTIMIZER:
        NAME: RMSprop
        LR: 0.001

    SCHEDULER:
        NAME: MultiStepLR
        GAMMA: 0.5
        MILESTONES: [ 10, 12, 14, 16 ]
        ON_EPOCH: True
        WARMUP:
            WARM_STEPS: 100

    CLIP_GRAD:
        TYPE: norm
        MAX_NORM: 35
        NORM_TYPE: 2

EVALUATOR:
    BATCH_SIZE_PER_GPU: 2
    MAX_DISP: *max_disp
    METRIC:
        - d1_all
        - epe
        - thres_1
        - thres_2
        - thres_3

TRAINER:
    EVAL_INTERVAL: 1
    CKPT_SAVE_INTERVAL: 1
    MAX_CKPT_SAVE_NUM: 30
    LOGGER_ITER_INTERVAL: 10
    TRAIN_VISUALIZATION: True
    EVAL_VISUALIZATION: True