#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
视频检测系统启动脚本
简化的用户界面，方便快速开始检测
"""

import os
import sys
from pathlib import Path
from batch_detector import BatchVideoDetector
from config import config

def check_requirements():
    """检查运行环境"""
    try:
        import cv2
        import numpy as np
        from ultralytics import YOLO
        print("✓ 所有依赖库已安装")
        return True
    except ImportError as e:
        print(f"✗ 缺少依赖库: {e}")
        print("请运行: pip install ultralytics opencv-python")
        return False

def check_model():
    """检查模型文件"""
    model_path = config.get_model_path()
    if Path(model_path).exists():
        print(f"✓ 模型文件存在: {model_path}")
        return True
    else:
        print(f"✗ 模型文件不存在: {model_path}")
        print("请检查模型路径配置")
        return False

def setup_folders():
    """设置文件夹结构"""
    config.create_folders()
    
    input_folder = Path(config.INPUT_FOLDER)
    output_folder = Path(config.OUTPUT_FOLDER)
    
    print(f"✓ 输入文件夹: {input_folder.absolute()}")
    print(f"✓ 输出文件夹: {output_folder.absolute()}")
    
    if not any(input_folder.iterdir()) if input_folder.exists() else True:
        print(f"⚠ 输入文件夹为空，请将视频文件放入: {input_folder.absolute()}")
        return False
    
    return True

def get_user_settings():
    """获取用户设置"""
    print("\n=== 检测参数设置 ===")
    
    # 置信度设置
    while True:
        try:
            confidence_input = input(f"请输入置信度阈值 (0.1-0.9, 默认 {config.CONFIDENCE_THRESHOLD}): ").strip()
            if not confidence_input:
                confidence = config.CONFIDENCE_THRESHOLD
                break
            confidence = float(confidence_input)
            if 0.1 <= confidence <= 0.9:
                break
            else:
                print("置信度必须在 0.1 到 0.9 之间")
        except ValueError:
            print("请输入有效的数字")
    
    # 输入文件夹
    input_folder = input(f"输入视频文件夹 (默认 '{config.INPUT_FOLDER}'): ").strip()
    if not input_folder:
        input_folder = config.INPUT_FOLDER
    
    # 输出文件夹
    output_folder = input(f"输出图片文件夹 (默认 '{config.OUTPUT_FOLDER}'): ").strip()
    if not output_folder:
        output_folder = config.OUTPUT_FOLDER
    
    return confidence, input_folder, output_folder

def main():
    """主函数"""
    print("=" * 60)
    print("        道路损伤检测系统 - 视频批量处理")
    print("=" * 60)
    
    # 检查运行环境
    print("\n1. 检查运行环境...")
    if not check_requirements():
        return
    
    if not check_model():
        return
    
    # 设置文件夹
    print("\n2. 设置文件夹...")
    if not setup_folders():
        input("\n请添加视频文件后重新运行程序。按回车键退出...")
        return
    
    # 获取用户设置
    confidence, input_folder, output_folder = get_user_settings()
    
    # 确认设置
    print("\n=== 检测设置确认 ===")
    print(f"模型文件: {config.get_model_path()}")
    print(f"置信度阈值: {confidence}")
    print(f"输入文件夹: {Path(input_folder).absolute()}")
    print(f"输出文件夹: {Path(output_folder).absolute()}")
    print(f"检测类别: {list(config.CLASS_NAMES_CN.values())}")
    
    confirm = input("\n确认开始检测? (y/n): ").strip().lower()
    if confirm not in ['y', 'yes', '是', '确认']:
        print("检测已取消")
        return
    
    # 开始检测
    print("\n=== 开始批量检测 ===")
    try:
        detector = BatchVideoDetector(
            model_path=config.get_model_path(),
            confidence=confidence
        )
        
        detector.process_all_videos(input_folder, output_folder)
        
        print("\n检测完成! 请查看输出文件夹中的结果。")
        
    except KeyboardInterrupt:
        print("\n检测被用户中断")
    except Exception as e:
        print(f"\n检测过程中出现错误: {e}")
        import traceback
        traceback.print_exc()
    
    input("\n按回车键退出...")

if __name__ == '__main__':
    main()