496 lines
19 KiB
Python
496 lines
19 KiB
Python
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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专业视频字幕OCR提取器
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支持PaddleOCR和EasyOCR两种引擎
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"""
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import cv2
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import os
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import time
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import json
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import argparse
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from pathlib import Path
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from datetime import datetime
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import logging
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import numpy as np
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from typing import List, Dict, Tuple
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# 设置日志
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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logger = logging.getLogger(__name__)
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def convert_numpy_types(obj):
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"""转换NumPy类型为Python原生类型，用于JSON序列化"""
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if isinstance(obj, np.integer):
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return int(obj)
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elif isinstance(obj, np.floating):
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return float(obj)
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elif isinstance(obj, np.ndarray):
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return obj.tolist()
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elif isinstance(obj, (list, tuple)):
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return [convert_numpy_types(item) for item in obj]
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elif isinstance(obj, dict):
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return {key: convert_numpy_types(value) for key, value in obj.items()}
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else:
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return obj
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class VideoSubtitleExtractor:
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"""专业视频字幕OCR提取器"""
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def __init__(self, ocr_engine="paddleocr", language="ch"):
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"""
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初始化OCR提取器
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Args:
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ocr_engine: OCR引擎 ("paddleocr", "easyocr", "both")
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language: 语言设置 ("ch", "en", "ch_en")
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"""
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self.ocr_engine = ocr_engine
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self.language = language
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self.paddle_ocr = None
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self.easy_ocr = None
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self.load_ocr_engines()
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def load_ocr_engines(self):
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"""加载OCR引擎"""
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logger.info(f"正在加载OCR引擎: {self.ocr_engine}")
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if self.ocr_engine in ["paddleocr", "both"]:
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try:
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from paddleocr import PaddleOCR
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# PaddleOCR语言映射
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paddle_lang_map = {
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"ch": "ch",
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"en": "en",
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"ch_en": "ch" # PaddleOCR支持ch包含中英文
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}
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paddle_lang = paddle_lang_map.get(self.language, "ch")
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self.paddle_ocr = PaddleOCR(
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use_textline_orientation=True,
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lang=paddle_lang
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)
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logger.info("PaddleOCR加载完成")
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except ImportError:
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logger.error("请安装PaddleOCR: pip install paddleocr")
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raise
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if self.ocr_engine in ["easyocr", "both"]:
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try:
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import easyocr
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# EasyOCR语言映射
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if self.language == "ch":
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lang_list = ['ch_sim'] # 简体中文
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elif self.language == "en":
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lang_list = ['en']
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elif self.language == "ch_en":
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lang_list = ['ch_sim', 'en'] # 中英文混合
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else:
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lang_list = ['ch_sim'] # 默认简体中文
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self.easy_ocr = easyocr.Reader(lang_list)
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logger.info("EasyOCR加载完成")
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except ImportError:
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logger.error("请安装EasyOCR: pip install easyocr")
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raise
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def extract_subtitles_from_video(self, video_path: str,
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sample_interval: int = 30,
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confidence_threshold: float = 0.5,
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subtitle_region: Tuple = None) -> Dict:
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"""
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从视频中提取字幕
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Args:
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video_path: 视频文件路径
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sample_interval: 采样间隔（帧数）
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confidence_threshold: 置信度阈值
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subtitle_region: 字幕区域 (x1, y1, x2, y2)，None表示全画面
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Returns:
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Dict: 提取结果
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"""
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video_path = Path(video_path)
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if not video_path.exists():
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raise FileNotFoundError(f"视频文件不存在: {video_path}")
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logger.info(f"开始提取视频字幕: {video_path}")
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logger.info(f"采样间隔: {sample_interval}帧, 置信度阈值: {confidence_threshold}")
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start_time = time.time()
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# 打开视频
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cap = cv2.VideoCapture(str(video_path))
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fps = cap.get(cv2.CAP_PROP_FPS)
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total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
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duration = total_frames / fps
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logger.info(f"视频信息: {total_frames}帧, {fps:.2f}FPS, {duration:.2f}秒")
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results = {
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"video_path": str(video_path),
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"duration": duration,
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"fps": fps,
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"total_frames": total_frames,
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"sample_interval": sample_interval,
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"confidence_threshold": confidence_threshold,
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"subtitle_region": subtitle_region,
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"subtitles": [],
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"unique_texts": set(),
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"ocr_engine": self.ocr_engine,
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"timestamp": datetime.now().isoformat()
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}
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frame_count = 0
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processed_frames = 0
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try:
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while True:
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ret, frame = cap.read()
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if not ret:
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break
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# 按间隔采样
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if frame_count % sample_interval == 0:
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timestamp = frame_count / fps
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# 裁剪字幕区域
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if subtitle_region:
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x1, y1, x2, y2 = subtitle_region
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frame_crop = frame[y1:y2, x1:x2]
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else:
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frame_crop = frame
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# OCR识别
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ocr_results = self._ocr_frame(frame_crop, timestamp, confidence_threshold)
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if ocr_results:
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results["subtitles"].extend(ocr_results)
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for result in ocr_results:
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results["unique_texts"].add(result["text"])
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processed_frames += 1
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# 显示进度
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if processed_frames % 10 == 0:
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progress = (frame_count / total_frames) * 100
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logger.info(f"处理进度: {progress:.1f}% ({processed_frames}帧)")
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frame_count += 1
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finally:
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cap.release()
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# 转换set为list
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results["unique_texts"] = list(results["unique_texts"])
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# 后处理：去重和合并
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results = self._postprocess_subtitles(results)
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extract_time = time.time() - start_time
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results["extract_time"] = extract_time
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logger.info(f"字幕提取完成，耗时: {extract_time:.2f}秒")
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logger.info(f"提取到 {len(results['subtitles'])} 个字幕片段")
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logger.info(f"唯一文本 {len(results['unique_texts'])} 条")
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return results
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def _ocr_frame(self, frame: np.ndarray, timestamp: float, confidence_threshold: float) -> List[Dict]:
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"""对单帧进行OCR识别"""
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ocr_results = []
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# PaddleOCR识别
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if self.paddle_ocr:
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try:
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paddle_result = self.paddle_ocr.ocr(frame)
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if paddle_result and paddle_result[0]:
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for detection in paddle_result[0]:
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if detection:
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# 处理不同版本的返回格式
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try:
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if len(detection) == 2:
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# 旧版本格式: [bbox, (text, confidence)]
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bbox, (text, confidence) = detection
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elif len(detection) == 3:
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# 新版本格式: [bbox, text, confidence]
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bbox, text, confidence = detection
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else:
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# 其他格式，跳过
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continue
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if confidence >= confidence_threshold and text.strip():
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ocr_results.append({
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"timestamp": timestamp,
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"text": text.strip(),
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"confidence": confidence,
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"bbox": bbox,
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"engine": "PaddleOCR"
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})
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except Exception as parse_error:
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logger.debug(f"解析单个检测结果失败: {parse_error}, 数据: {detection}")
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continue
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except Exception as e:
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logger.warning(f"PaddleOCR识别失败 (时间戳:{timestamp:.2f}): {e}")
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# EasyOCR识别
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if self.easy_ocr:
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try:
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easy_result = self.easy_ocr.readtext(frame)
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for detection in easy_result:
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bbox, text, confidence = detection
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if confidence >= confidence_threshold and text.strip():
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ocr_results.append({
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"timestamp": timestamp,
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"text": text.strip(),
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"confidence": confidence,
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"bbox": bbox,
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"engine": "EasyOCR"
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})
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except Exception as e:
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logger.warning(f"EasyOCR识别失败 (时间戳:{timestamp:.2f}): {e}")
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return ocr_results
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def _postprocess_subtitles(self, results: Dict) -> Dict:
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"""后处理字幕结果"""
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subtitles = results["subtitles"]
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# 按时间戳排序
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subtitles.sort(key=lambda x: x["timestamp"])
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# 去重相邻重复文本
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filtered_subtitles = []
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last_text = ""
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last_timestamp = -1
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for subtitle in subtitles:
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text = subtitle["text"]
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timestamp = subtitle["timestamp"]
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# 如果文本不同，或者时间间隔较大，则保留
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if text != last_text or (timestamp - last_timestamp) > 5.0:
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filtered_subtitles.append(subtitle)
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last_text = text
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last_timestamp = timestamp
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results["subtitles"] = filtered_subtitles
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results["filtered_count"] = len(subtitles) - len(filtered_subtitles)
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# 生成连续文本
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results["continuous_text"] = " ".join([s["text"] for s in filtered_subtitles])
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# 统计信息
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results["stats"] = {
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"total_detections": len(subtitles),
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"filtered_detections": len(filtered_subtitles),
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"unique_texts": len(results["unique_texts"]),
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"text_length": len(results["continuous_text"]),
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"average_confidence": np.mean([s["confidence"] for s in filtered_subtitles]) if filtered_subtitles else 0
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}
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return results
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def extract_subtitles_from_frames(self, frame_dir: str, confidence_threshold: float = 0.5) -> Dict:
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"""从帧图片目录中提取字幕"""
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frame_dir = Path(frame_dir)
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if not frame_dir.exists():
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raise FileNotFoundError(f"帧目录不存在: {frame_dir}")
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logger.info(f"开始从帧目录提取字幕: {frame_dir}")
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# 获取所有图片文件
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image_extensions = ['.jpg', '.jpeg', '.png', '.bmp']
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image_files = []
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for ext in image_extensions:
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image_files.extend(frame_dir.glob(f"*{ext}"))
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image_files.extend(frame_dir.glob(f"*{ext.upper()}"))
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image_files.sort()
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if not image_files:
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logger.warning(f"在目录 {frame_dir} 中未找到图片文件")
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return {}
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logger.info(f"找到 {len(image_files)} 个图片文件")
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results = {
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"frame_dir": str(frame_dir),
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"total_images": len(image_files),
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"confidence_threshold": confidence_threshold,
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"subtitles": [],
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"unique_texts": set(),
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"ocr_engine": self.ocr_engine,
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"timestamp": datetime.now().isoformat()
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}
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for i, image_file in enumerate(image_files):
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try:
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frame = cv2.imread(str(image_file))
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if frame is not None:
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# 使用文件名作为时间戳（如果可能）
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timestamp = float(i) # 简单使用索引
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ocr_results = self._ocr_frame(frame, timestamp, confidence_threshold)
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if ocr_results:
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results["subtitles"].extend(ocr_results)
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for result in ocr_results:
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results["unique_texts"].add(result["text"])
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# 显示进度
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if (i + 1) % 10 == 0:
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progress = ((i + 1) / len(image_files)) * 100
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logger.info(f"处理进度: {progress:.1f}%")
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except Exception as e:
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logger.warning(f"处理图片 {image_file} 时出错: {e}")
|
|||
|
|
|
|||
|
|
# 转换set为list
|
|||
|
|
results["unique_texts"] = list(results["unique_texts"])
|
|||
|
|
|
|||
|
|
# 后处理
|
|||
|
|
results = self._postprocess_subtitles(results)
|
|||
|
|
|
|||
|
|
logger.info(f"字幕提取完成，提取到 {len(results['subtitles'])} 个字幕片段")
|
|||
|
|
|
|||
|
|
return results
|
|||
|
|
|
|||
|
|
def save_results(self, results: Dict, output_path: str, format: str = "json"):
|
|||
|
|
"""保存提取结果"""
|
|||
|
|
output_path = Path(output_path)
|
|||
|
|
|
|||
|
|
if format == "json":
|
|||
|
|
# 序列化结果（处理set类型和NumPy类型）
|
|||
|
|
results_copy = results.copy()
|
|||
|
|
if "unique_texts" in results_copy and isinstance(results_copy["unique_texts"], set):
|
|||
|
|
results_copy["unique_texts"] = list(results_copy["unique_texts"])
|
|||
|
|
|
|||
|
|
# 转换NumPy类型
|
|||
|
|
results_copy = convert_numpy_types(results_copy)
|
|||
|
|
|
|||
|
|
with open(output_path, 'w', encoding='utf-8') as f:
|
|||
|
|
json.dump(results_copy, f, ensure_ascii=False, indent=2)
|
|||
|
|
|
|||
|
|
elif format == "txt":
|
|||
|
|
with open(output_path, 'w', encoding='utf-8') as f:
|
|||
|
|
f.write(results.get("continuous_text", ""))
|
|||
|
|
|
|||
|
|
elif format == "srt":
|
|||
|
|
self._save_srt(results, output_path)
|
|||
|
|
|
|||
|
|
else:
|
|||
|
|
raise ValueError(f"不支持的格式: {format}")
|
|||
|
|
|
|||
|
|
logger.info(f"结果已保存: {output_path}")
|
|||
|
|
|
|||
|
|
def _save_srt(self, results: Dict, output_path: Path):
|
|||
|
|
"""保存为SRT字幕格式"""
|
|||
|
|
with open(output_path, 'w', encoding='utf-8') as f:
|
|||
|
|
for i, subtitle in enumerate(results["subtitles"], 1):
|
|||
|
|
timestamp = subtitle["timestamp"]
|
|||
|
|
text = subtitle["text"]
|
|||
|
|
|
|||
|
|
# 估算字幕持续时间（3秒）
|
|||
|
|
start_time = self._format_time(timestamp)
|
|||
|
|
end_time = self._format_time(timestamp + 3.0)
|
|||
|
|
|
|||
|
|
f.write(f"{i}\n")
|
|||
|
|
f.write(f"{start_time} --> {end_time}\n")
|
|||
|
|
f.write(f"{text}\n\n")
|
|||
|
|
|
|||
|
|
def _format_time(self, seconds):
|
|||
|
|
"""格式化时间为SRT格式"""
|
|||
|
|
hours = int(seconds // 3600)
|
|||
|
|
minutes = int((seconds % 3600) // 60)
|
|||
|
|
seconds = seconds % 60
|
|||
|
|
return f"{hours:02d}:{minutes:02d}:{seconds:06.3f}".replace('.', ',')
|
|||
|
|
|
|||
|
|
def main():
|
|||
|
|
"""主函数"""
|
|||
|
|
parser = argparse.ArgumentParser(description="专业视频字幕OCR提取器")
|
|||
|
|
parser.add_argument("input", help="输入视频文件路径或帧图片目录")
|
|||
|
|
parser.add_argument("-e", "--engine", default="paddleocr",
|
|||
|
|
choices=["paddleocr", "easyocr", "both"],
|
|||
|
|
help="OCR引擎 (默认: paddleocr)")
|
|||
|
|
parser.add_argument("-l", "--language", default="ch",
|
|||
|
|
choices=["ch", "en", "ch_en"],
|
|||
|
|
help="语言设置 (默认: ch)")
|
|||
|
|
parser.add_argument("-i", "--interval", type=int, default=30,
|
|||
|
|
help="帧采样间隔 (默认: 30)")
|
|||
|
|
parser.add_argument("-c", "--confidence", type=float, default=0.5,
|
|||
|
|
help="置信度阈值 (默认: 0.5)")
|
|||
|
|
parser.add_argument("-o", "--output", default="subtitle_results",
|
|||
|
|
help="输出目录 (默认: subtitle_results)")
|
|||
|
|
parser.add_argument("-f", "--format", default="json",
|
|||
|
|
choices=["json", "txt", "srt"],
|
|||
|
|
help="输出格式 (默认: json)")
|
|||
|
|
parser.add_argument("--region", nargs=4, type=int, metavar=('X1', 'Y1', 'X2', 'Y2'),
|
|||
|
|
help="字幕区域坐标 (x1 y1 x2 y2)")
|
|||
|
|
|
|||
|
|
args = parser.parse_args()
|
|||
|
|
|
|||
|
|
# 创建提取器
|
|||
|
|
extractor = VideoSubtitleExtractor(
|
|||
|
|
ocr_engine=args.engine,
|
|||
|
|
language=args.language
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
input_path = Path(args.input)
|
|||
|
|
|
|||
|
|
try:
|
|||
|
|
if input_path.is_file():
|
|||
|
|
# 处理视频文件
|
|||
|
|
logger.info("处理视频文件")
|
|||
|
|
results = extractor.extract_subtitles_from_video(
|
|||
|
|
args.input,
|
|||
|
|
sample_interval=args.interval,
|
|||
|
|
confidence_threshold=args.confidence,
|
|||
|
|
subtitle_region=tuple(args.region) if args.region else None
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
elif input_path.is_dir():
|
|||
|
|
# 处理帧图片目录
|
|||
|
|
logger.info("处理帧图片目录")
|
|||
|
|
results = extractor.extract_subtitles_from_frames(
|
|||
|
|
args.input,
|
|||
|
|
confidence_threshold=args.confidence
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
else:
|
|||
|
|
logger.error(f"输入路径无效: {args.input}")
|
|||
|
|
return
|
|||
|
|
|
|||
|
|
# 保存结果
|
|||
|
|
output_dir = Path(args.output)
|
|||
|
|
output_dir.mkdir(exist_ok=True)
|
|||
|
|
|
|||
|
|
input_name = input_path.stem
|
|||
|
|
output_file = output_dir / f"{input_name}_subtitles.{args.format}"
|
|||
|
|
|
|||
|
|
extractor.save_results(results, output_file, args.format)
|
|||
|
|
|
|||
|
|
# 显示结果
|
|||
|
|
print(f"\n字幕提取完成!")
|
|||
|
|
print(f"输入: {args.input}")
|
|||
|
|
print(f"输出: {output_file}")
|
|||
|
|
print(f"提取时长: {results.get('extract_time', 0):.2f} 秒")
|
|||
|
|
print(f"字幕片段: {results['stats']['filtered_detections']} 个")
|
|||
|
|
print(f"唯一文本: {results['stats']['unique_texts']} 条")
|
|||
|
|
print(f"平均置信度: {results['stats']['average_confidence']:.3f}")
|
|||
|
|
print(f"文本总长度: {results['stats']['text_length']} 字符")
|
|||
|
|
|
|||
|
|
if results.get("continuous_text"):
|
|||
|
|
print(f"\n提取的连续文本:")
|
|||
|
|
print("-" * 50)
|
|||
|
|
print(results["continuous_text"][:500] + "..." if len(results["continuous_text"]) > 500 else results["continuous_text"])
|
|||
|
|
|
|||
|
|
except Exception as e:
|
|||
|
|
logger.error(f"程序执行出错: {str(e)}")
|
|||
|
|
return
|
|||
|
|
|
|||
|
|
if __name__ == "__main__":
|
|||
|
|
main()
|