unet_mechanical_meter.yaml

EVAL_CROP_SIZE: (2049, 1537) # (width, height), for unpadding rangescaling and stepscaling
TRAIN_CROP_SIZE: (769, 769) # (width, height), for unpadding rangescaling and stepscaling
AUG: 
    AUG_METHOD: u"stepscaling" # choice unpadding rangescaling and stepscaling
    FIX_RESIZE_SIZE: (640, 640) # (width, height), for unpadding
    INF_RESIZE_VALUE: 500  # for rangescaling
    MAX_RESIZE_VALUE: 600  # for rangescaling
    MIN_RESIZE_VALUE: 400  # for rangescaling
    MAX_SCALE_FACTOR: 2.0  # for stepscaling
    MIN_SCALE_FACTOR: 0.5  # for stepscaling
    SCALE_STEP_SIZE: 0.25  # for stepscaling
    MIRROR: True
    RICH_CROP: 
        ENABLE: False 

BATCH_SIZE: 2
MEAN: [0.5, 0.5, 0.5]
STD: [0.5, 0.5, 0.5]

DATALOADER: 
    BUF_SIZE: 256
    NUM_WORKERS: 4
DATASET: 
    DATA_DIR: "./dataset/mini_mechanical_industry_meter_data/"
    IMAGE_TYPE: "rgb"  # choice rgb or rgba
    NUM_CLASSES: 5
    TEST_FILE_LIST: "./dataset/mini_mechanical_industry_meter_data/val_mini.txt"
    TEST_TOTAL_IMAGES: 8
    TRAIN_FILE_LIST: "./dataset/mini_mechanical_industry_meter_data/train_mini.txt"
    TRAIN_TOTAL_IMAGES: 64
    VAL_FILE_LIST: "./dataset/mini_mechanical_industry_meter_data/val_mini.txt"
    VAL_TOTAL_IMAGES: 8
    SEPARATOR: "|"
    IGNORE_INDEX: 255

FREEZE:
    MODEL_FILENAME: "__model__"
    PARAMS_FILENAME: "__params__"
MODEL:
    MODEL_NAME: "unet"
    DEFAULT_NORM_TYPE: "bn"
TEST:
    TEST_MODEL: "./saved_model/unet_mechanical_meter/final/"
TRAIN:
    MODEL_SAVE_DIR: "./saved_model/unet_mechanical_meter/"
    PRETRAINED_MODEL_DIR: "./pretrained_model/unet_bn_coco/"
    SNAPSHOT_EPOCH: 10
SOLVER:
    NUM_EPOCHS: 100
    LR: 0.001
    LR_POLICY: "poly"
    OPTIMIZER: "sgd"