pi_rcnn_seg_pretrain.yaml

CLASS_NAMES: ['Car', 'Pedestrian', 'Cyclist']

DATA_CONFIG:
    _BASE_CONFIG_: cfgs/dataset_configs/kitti_seg_dataset.yaml

    CONVERT_LABEL: True

    MULTI_CLASSES: True

    DATA_PATH: '../data/kitti/semantic'

MODEL:
    NAME: PIRCNN

    BACKBONE_IMAGE:
        ENABLED: True
        FIXED: False
        NAME: UNet
        INPUT_CHANNELS: 3
        BN: True
        CHANNELS: [64, 128, 256, 512, 1024]
        OUTPUT_CHANNELS: 10
        OUTPUT_PROB: True

        LOSS_CONFIG:
            NAME: FocalLoss


OPTIMIZATION:
    BATCH_SIZE_PER_GPU: 4
    NUM_EPOCHS: 200

    OPTIMIZER: adam_onecycle
    LR: 0.01
    WEIGHT_DECAY: 0.01
    MOMENTUM: 0.9

    MOMS: [0.95, 0.85]
    PCT_START: 0.4
    DIV_FACTOR: 10
    DECAY_STEP_LIST: [35, 45]
    LR_DECAY: 0.1
    LR_CLIP: 0.0000001

    LR_WARMUP: False
    WARMUP_EPOCH: 1

    GRAD_NORM_CLIP: 10