config.yaml

---
# ———————————————————————— 通用参数 ———————————————————————— #
# GPU设备
CUDA_DEVICE: "0"

# ———————————————————————— 是否训练 ———————————————————————— #
# 是否需要先训练
start_train: False

batch: 24 
lr: 0.005
# 主干网络学习率倍数
backbone_lr_ratio: 1

epoch: 100
# 保存最后多少个epoch
save_epoch_num: 80
train_num_workers: 0
val_num_workers: 0

momen: 0.9
decay: 0.0005
resize: 416
trainsize:
  - 416
# 断点续训:
continue_train: False
continue_train_pth: "./out/model-70"
continue_train_start_epoch: 70

# 是否开启验证集:
val: True
# 2/3 epoch后开始验证
val_ratio: 0.3
# ecssd 共1000张图片
val_total: 250

# 随机种子
Random_seeds: 520
# 权重路径
out_path: "./out"
# 训练集
train_datapath: "D:/yangxin/data/cod/TrainDataset"
val_datapath: "D:/yangxin/data/cod/CAMO"
# ———————————————————————— 评价 ———————————————————————— #
# 是否评价
start_eval: True
# 是否需要先推断
start_test: True
# 不需要则改成False
method_name: False
# 模型权重: , 不需要则改成False
model_name: #False
  - "model-90"



# 评价保存位置:
save_eval_csv: "../best.csv"


# 权重路径:
model_path: "./out/"
# 图片保存路径:
save_path: "D:/yangxin/result/"
# 数据集路径:
data_path: "D:/yangxin/data/cod/"
# 推断数据集:
data_name:
  - "CAMO"
  - "CHAMELEON"
  - "COD10K"
  - "NC4K"


# 小数位:
Decimal_places: 4
# 评价指标(不能改):
Evaluation_indicators:
  - "S-measure"
  - "MAE"
  - "WFm"
  # - "maxFm"
  # - "meanFm"
  # - "adpFm"
  # - "maxEm"
  - "meanEm"
  # - "adpEm"
...