"""
食物分类器配置文件
包含训练参数、路径配置等
"""

import os

# 基础路径配置
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))

# 数据集路径
DATASET_DIR = os.path.join(BASE_DIR, 'dataset')
TRAIN_DATA_DIR = os.path.join(DATASET_DIR, 'train')
VAL_DATA_DIR = os.path.join(DATASET_DIR, 'val')
TEST_DATA_DIR = os.path.join(DATASET_DIR, 'test')

# 模型保存路径
MODEL_DIR = os.path.join(BASE_DIR, 'model', '15')
BEST_MODEL_PATH = os.path.join(MODEL_DIR, 'best_food_model.pth')
TRAINING_CURVES_PATH = os.path.join(MODEL_DIR, 'training_curves.png')
TRAINING_RESULTS_PATH = os.path.join(MODEL_DIR, 'training_results.txt')

# INFERENCE_BEST_MODEL_PATH = os.path.join(BASE_DIR, 'model', '05','best_food_model.pth')
INFERENCE_BEST_MODEL_PATH = BEST_MODEL_PATH

# 训练参数
NUM_EPOCHS = 100
BATCH_SIZE = 32
# BATCH_SIZE = 128
LEARNING_RATE = 0.001
WEIGHT_DECAY = 1e-4

# 学习率调度器参数
SCHEDULER_STEP_SIZE = 30
SCHEDULER_GAMMA = 0.1

# 数据预处理参数
IMAGE_SIZE = (32, 32)
NORMALIZE_MEAN = (0.485, 0.456, 0.406)
NORMALIZE_STD = (0.229, 0.224, 0.225)

# 数据增强参数
RANDOM_HORIZONTAL_FLIP_P = 0.5
RANDOM_ROTATION_DEGREES = 10
COLOR_JITTER_BRIGHTNESS = 0.2
COLOR_JITTER_CONTRAST = 0.2
COLOR_JITTER_SATURATION = 0.2
COLOR_JITTER_HUE = 0.1

# 模型参数
NUM_CLASSES = 4

# 其他配置
NUM_WORKERS = 0  # Windows下建议设为0
DEVICE = 'cuda'  # 'cuda' 或 'cpu'，程序会自动检测可用性

# 中心损失权重
CENTER_LOSS_WEIGHT = 0.1