import os
import socket

def get_local_ip():
    """获取本机局域网 IP"""
    try:
        # 创建一个UDP套接字
        s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
        # 连接一个不需要实际存在的外部地址
        s.connect(('8.8.8.8', 80))
        ip = s.getsockname()[0]
    except Exception:
        ip = "127.0.0.1"
    finally:
        s.close()
    return ip



class Settings:
    LOCAL_IP: str = get_local_ip()
    LOCAL_PORT: int = 7721
    BASE_URL: str = f"http://{LOCAL_IP}:{LOCAL_PORT}"

    # API 核心配置
    API_URL: str = "http://100.64.0.8/v1/workflows/run"
    API_KEY: str = "Bearer app-qR46FHcfLyKz2kb0tiiRfV50"
    USER_ID: str = "abc-123"

    # 滑动窗口配置 (可用于长视频的分片处理)
    CHUNK_SIZE: int = 10000
    OVERLAP_SIZE: int = 500

    # 静态资源与图片保存目录配置
    STATIC_DIR: str = os.path.join(os.getcwd(), "static")
    FRAMES_DIR: str = os.path.join(STATIC_DIR, "frames")

    # ==========================================
    # 视频帧分析算法配置 (Video Analysis Settings)
    # ==========================================

    # HuggingFace 语义分割模型路径 (用于识别手和卡片)
    VIDEO_SEG_MODEL_DIR: str = r"C:\Code\ML\Model\Card_Seg\segformer_card_hand02_safetensors"

    # 目标时间戳前后的搜索范围 (毫秒) -> 决定了去目标时间戳附近多大范围内寻找最佳帧
    VIDEO_SEARCH_BEFORE_MS: int = int(os.getenv("VIDEO_SEARCH_BEFORE_MS", "1000"))  # 往前找/毫秒
    VIDEO_SEARCH_AFTER_MS: int = int(os.getenv("VIDEO_SEARCH_AFTER_MS", "6000"))  # 往后找

    # 视频分析时的抽帧率 -> 例如 4.0 代表每秒只分析 4 帧，避免逐帧分析导致性能雪崩
    VIDEO_ANALYSIS_FPS: float = float(os.getenv("VIDEO_ANALYSIS_FPS", "4.0"))

    # 只对综合得分排名前 K 的候选帧进行 OCR 识别 (OCR 比较耗时，没必要每帧都跑)
    VIDEO_OCR_TOP_K: int = int(os.getenv("VIDEO_OCR_TOP_K", "5"))

    # 目标停留时间 (秒) -> 用来奖励那些在画面中稳定停留的帧 (排除一闪而过的残影)
    VIDEO_DWELL_TARGET_SECONDS: float = float(os.getenv("VIDEO_DWELL_TARGET_SECONDS", "1.2"))

    # 画面中被判定为"有卡"或"有手"的最小面积比例 (过滤掉误识别的零星像素)
    VIDEO_MIN_CARD_AREA_RATIO: float = float(os.getenv("VIDEO_MIN_CARD_AREA_RATIO", "0.01"))  # 卡片占全图 >= 1%
    VIDEO_MIN_HAND_AREA_RATIO: float = float(os.getenv("VIDEO_MIN_HAND_AREA_RATIO", "0.005"))  # 手占全图 >= 0.5%

    # 分割模型输出的类别 ID
    VIDEO_CARD_LABEL_ID: int = int(os.getenv("VIDEO_CARD_LABEL_ID", "1"))
    VIDEO_HAND_LABEL_ID: int = int(os.getenv("VIDEO_HAND_LABEL_ID", "2"))


settings = Settings()

# 确保图片输出目录存在，避免运行报错
os.makedirs(settings.FRAMES_DIR, exist_ok=True)