#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
字幕检测器测试脚本

验证：
1. 预设区域定义
2. 自动字幕区域检测
3. 缓存机制
"""

import sys
import os
import cv2
import numpy as np

# 添加项目路径
project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.insert(0, project_root)

from src.extractors.subtitle_detector import SubtitleDetector


def create_test_frame_with_text(width=1280, height=720):
    """
    创建包含模拟字幕的测试帧
    
    Args:
        width: 帧宽度
        height: 帧高度
        
    Returns:
        numpy.ndarray: 测试帧
    """
    # 创建黑色背景
    frame = np.zeros((height, width, 3), dtype=np.uint8)
    
    # 添加一些噪声背景
    noise = np.random.randint(0, 50, (height, width, 3), dtype=np.uint8)
    frame = cv2.add(frame, noise)
    
    # 在底部添加白色文字（模拟B站字幕）
    font = cv2.FONT_HERSHEY_SIMPLEX
    font_scale = 1.0
    thickness = 2
    
    # 添加多行字幕
    texts = [
        "这是测试字幕内容",
        "B站硬字幕提取测试",
        "00:01:23 第一行字幕",
        "00:01:25 第二行字幕"
    ]
    
    y_start = int(height * 0.85)
    line_height = 35
    
    for i, text in enumerate(texts):
        y = y_start + i * line_height
        x = int(width * 0.15)
        
        # 绘制文字阴影（黑色）
        cv2.putText(frame, text, (x + 2, y + 2), font, font_scale, (0, 0, 0), thickness + 2)
        # 绘制白色文字
        cv2.putText(frame, text, (x, y), font, font_scale, (255, 255, 255), thickness)
    
    return frame


def test_preset_regions():
    """测试1: 预设区域定义"""
    print("\n" + "="*60)
    print("测试1: 预设区域定义")
    print("="*60)
    
    detector = SubtitleDetector()
    frame_width, frame_height = 1280, 720
    
    # 测试所有预设区域
    for region_name in [detector.REGION_BOTTOM, detector.REGION_CENTER, detector.REGION_TOP]:
        try:
            x, y, width, height = detector.get_preset_region(region_name, frame_height, frame_width)
            print(f"\n✓ 区域 '{region_name}':")
            print(f"  坐标: x={x}, y={y}")
            print(f"  尺寸: width={width}, height={height}")
            print(f"  相对位置: top={y/frame_height:.2f}, bottom={(y+height)/frame_height:.2f}")
        except Exception as e:
            print(f"✗ 区域 '{region_name}' 失败: {e}")
    
    # 测试无效区域名称
    try:
        detector.get_preset_region("invalid", frame_height, frame_width)
        print("\n✗ 错误: 应该抛出异常但没有")
    except ValueError as e:
        print(f"\n✓ 无效区域名称正确抛出异常: {e}")
    
    print("\n测试1完成!")


def test_auto_detection():
    """测试2: 自动字幕区域检测"""
    print("\n" + "="*60)
    print("测试2: 自动字幕区域检测")
    print("="*60)
    
    detector = SubtitleDetector()
    
    # 创建测试帧（带字幕）
    print("\n创建测试帧...")
    test_frame = create_test_frame_with_text()
    height, width = test_frame.shape[:2]
    print(f"帧尺寸: {width}x{height}")
    
    # 保存测试帧用于可视化
    test_frame_path = "/tmp/test_subtitle_frame.png"
    cv2.imwrite(test_frame_path, test_frame)
    print(f"✓ 测试帧已保存到: {test_frame_path}")
    
    # 执行自动检测
    print("\n执行自动检测...")
    try:
        x, y, w, h = detector.auto_detect_subtitle_region(test_frame, video_id=None, use_cache=False)
        print(f"✓ 检测到字幕区域:")
        print(f"  坐标: x={x}, y={y}")
        print(f"  尺寸: width={w}, height={h}")
        print(f"  相对位置: top={y/height:.2f}, bottom={(y+h)/height:.2f}")
        
        # 在测试帧上绘制检测框
        frame_with_box = test_frame.copy()
        cv2.rectangle(frame_with_box, (x, y), (x+w, y+h), (0, 255, 0), 2)
        
        # 保存结果
        result_path = "/tmp/test_subtitle_detected.png"
        cv2.imwrite(result_path, frame_with_box)
        print(f"✓ 检测结果已保存到: {result_path}")
        
        # 验证检测区域是否合理（应该在底部）
        region_bottom = (y + h) / height
        if region_bottom > 0.7:  # 底部30%
            print(f"✓ 检测区域位置合理（底部）")
        else:
            print(f"! 警告: 检测区域可能不在底部 (bottom={region_bottom:.2f})")
            
    except Exception as e:
        print(f"✗ 自动检测失败: {e}")
        import traceback
        traceback.print_exc()
    
    print("\n测试2完成!")


def test_cache_mechanism():
    """测试3: 缓存机制"""
    print("\n" + "="*60)
    print("测试3: 缓存机制")
    print("="*60)
    
    detector = SubtitleDetector(cache_size=3)  # 小缓存便于测试
    
    # 创建测试帧
    test_frame = create_test_frame_with_text()
    
    # 测试1: 首次检测并缓存
    print("\n1. 首次检测并缓存...")
    video_id1 = "BV1xx411c7mD"
    region1 = detector.auto_detect_subtitle_region(test_frame, video_id=video_id1, use_cache=True)
    print(f"✓ 检测完成，区域: {region1}")
    print(f"✓ 缓存大小: {detector.get_cache_size()}")
    
    # 测试2: 再次检测同一视频（应使用缓存）
    print("\n2. 再次检测同一视频（应使用缓存）...")
    region2 = detector.auto_detect_subtitle_region(test_frame, video_id=video_id1, use_cache=True)
    print(f"✓ 缓存结果: {region2}")
    if region1 == region2:
        print(f"✓ 缓存命中，结果一致")
    else:
        print(f"✗ 警告: 缓存结果不一致")
    
    # 测试3: 检测不同视频
    print("\n3. 检测不同视频...")
    video_id2 = "BV1yy411c7mE"
    region3 = detector.auto_detect_subtitle_region(test_frame, video_id=video_id2, use_cache=True)
    print(f"✓ 新视频检测完成，区域: {region3}")
    print(f"✓ 缓存大小: {detector.get_cache_size()}")
    
    # 测试4: 查看所有缓存
    print("\n4. 查看所有缓存...")
    cached = detector.get_cached_regions()
    print(f"✓ 缓存内容:")
    for vid, reg in cached.items():
        print(f"  {vid}: {reg}")
    
    # 测试5: 清空指定视频缓存
    print("\n5. 清空指定视频缓存...")
    detector.clear_cache(video_id=video_id1)
    print(f"✓ 已删除 {video_id1}")
    print(f"✓ 缓存大小: {detector.get_cache_size()}")
    
    # 测试6: 清空所有缓存
    print("\n6. 清空所有缓存...")
    detector.clear_cache()
    print(f"✓ 缓存已清空")
    print(f"✓ 缓存大小: {detector.get_cache_size()}")
    
    # 测试7: 缓存容量限制（LRU）
    print("\n7. 测试缓存容量限制（LRU）...")
    for i in range(5):
        vid = f"BV{i:012d}"
        detector.auto_detect_subtitle_region(test_frame, video_id=vid, use_cache=True)
        print(f"  添加视频 {vid}，缓存大小: {detector.get_cache_size()}")
    
    cached = detector.get_cached_regions()
    print(f"✓ 缓存中有 {len(cached)} 个视频（应为最大容量3）")
    print(f"✓ 保留的视频: {list(cached.keys())}")
    
    print("\n测试3完成!")


def test_integration():
    """测试4: 集成测试"""
    print("\n" + "="*60)
    print("测试4: 集成测试")
    print("="*60)
    
    detector = SubtitleDetector()
    test_frame = create_test_frame_with_text()
    height, width = test_frame.shape[:2]
    
    print("\n模拟B站视频字幕检测流程...")
    
    # 步骤1: 尝试自动检测
    print("\n步骤1: 自动检测字幕区域")
    video_id = "BV1xx411c7mD"
    region = detector.auto_detect_subtitle_region(test_frame, video_id=video_id)
    print(f"✓ 自动检测结果: {region}")
    
    # 步骤2: 后续帧使用缓存
    print("\n步骤2: 后续帧使用缓存")
    for i in range(3):
        cached_region = detector.auto_detect_subtitle_region(test_frame, video_id=video_id)
        if cached_region == region:
            print(f"✓ 帧 {i+1}: 使用缓存，结果一致")
        else:
            print(f"✗ 帧 {i+1}: 缓存结果异常")
    
    # 步骤3: 对比预设区域
    print("\n步骤3: 对比预设区域")
    bottom_region = detector.get_preset_region(detector.REGION_BOTTOM, height, width)
    print(f"  检测区域: y={region[1]}, height={region[3]}")
    print(f"  底部预设: y={bottom_region[1]}, height={bottom_region[3]}")
    
    # 步骤4: 提取字幕区域
    print("\n步骤4: 提取字幕区域用于OCR")
    x, y, w, h = region
    subtitle_roi = test_frame[y:y+h, x:x+w]
    subtitle_path = "/tmp/subtitle_roi.png"
    cv2.imwrite(subtitle_path, subtitle_roi)
    print(f"✓ 字幕ROI已保存到: {subtitle_path}")
    print(f"  ROI尺寸: {w}x{h}")
    
    print("\n测试4完成!")


def main():
    """主测试函数"""
    print("\n" + "="*60)
    print("字幕检测器完整测试")
    print("="*60)
    
    try:
        # 运行所有测试
        test_preset_regions()
        test_auto_detection()
        test_cache_mechanism()
        test_integration()
        
        print("\n" + "="*60)
        print("所有测试完成！")
        print("="*60)
        
        print("\n生成的测试文件:")
        print("  - /tmp/test_subtitle_frame.png (原始测试帧)")
        print("  - /tmp/test_subtitle_detected.png (带检测框的结果)")
        print("  - /tmp/subtitle_roi.png (提取的字幕区域)")
        
    except Exception as e:
        print(f"\n✗ 测试失败: {e}")
        import traceback
        traceback.print_exc()
        return 1
    
    return 0


if __name__ == "__main__":
    sys.exit(main())