pspnet_optic.yaml

# 数据集配置
DATASET:
    DATA_DIR: "./dataset/optic_disc_seg/"
    NUM_CLASSES: 2
    TEST_FILE_LIST: "./dataset/optic_disc_seg/test_list.txt"
    TRAIN_FILE_LIST: "./dataset/optic_disc_seg/train_list.txt"
    VAL_FILE_LIST: "./dataset/optic_disc_seg/val_list.txt"
    VIS_FILE_LIST: "./dataset/optic_disc_seg/test_list.txt"

# 预训练模型配置
MODEL:
    MODEL_NAME: "pspnet"
    DEFAULT_NORM_TYPE: "bn"
    PSPNET:
        DEPTH_MULTIPLIER: 1
        LAYERS: 50

# 其他配置
TRAIN_CROP_SIZE: (512, 512)
EVAL_CROP_SIZE: (512, 512)
AUG:
    AUG_METHOD: "unpadding"
    FIX_RESIZE_SIZE: (512, 512)
BATCH_SIZE: 4
TRAIN:
    PRETRAINED_MODEL_DIR: "./pretrained_model/pspnet50_bn_cityscapes/"
    MODEL_SAVE_DIR: "./saved_model/pspnet_optic/"
    SNAPSHOT_EPOCH: 5
TEST:
    TEST_MODEL: "./saved_model/pspnet_optic/final"
SOLVER:
    NUM_EPOCHS: 10
    LR: 0.001
    LR_POLICY: "poly"
    OPTIMIZER: "adam"