160 lines
6.0 KiB
Python
160 lines
6.0 KiB
Python
import os
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import cv2
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import logging
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from rapidocr import RapidOCR
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class OCRViolationDetector:
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"""
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封装RapidOCR引擎，用于检测图像帧中的违禁词。
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"""
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def __init__(self, forbidden_words_path: str, ocr_confidence_threshold: float = 0.5,
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log_level: int = logging.INFO, log_file: str = None):
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"""
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初始化OCR引擎、违禁词列表和日志配置。
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Args:
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forbidden_words_path (str): 违禁词列表 .txt 文件的路径。
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ocr_confidence_threshold (float): OCR识别结果的置信度阈值。
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log_level (int): 日志级别，默认为logging.INFO
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log_file (str, optional): 日志文件路径，如不提供则只输出到控制台
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"""
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# 初始化日志
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self.logger = self._setup_logger(log_level, log_file)
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# 加载违禁词
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self.forbidden_words = self._load_forbidden_words(forbidden_words_path)
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# 初始化OCR引擎
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self.ocr_engine = self._initialize_ocr()
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# 设置置信度阈值
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self.OCR_CONFIDENCE_THRESHOLD = ocr_confidence_threshold
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self.logger.info(f"OCR置信度阈值设置为: {ocr_confidence_threshold}")
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def _setup_logger(self, log_level: int, log_file: str = None) -> logging.Logger:
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"""
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配置日志系统
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Args:
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log_level: 日志级别
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log_file: 日志文件路径，如为None则只输出到控制台
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Returns:
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配置好的logger实例
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"""
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# 创建logger
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logger = logging.getLogger('OCRViolationDetector')
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logger.setLevel(log_level)
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# 避免重复添加处理器
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if logger.handlers:
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return logger
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# 定义日志格式
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formatter = logging.Formatter(
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'%(asctime)s - %(name)s - %(levelname)s - %(message)s'
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)
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# 添加控制台处理器
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console_handler = logging.StreamHandler()
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console_handler.setFormatter(formatter)
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logger.addHandler(console_handler)
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# 如果提供了日志文件路径，则添加文件处理器
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if log_file:
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try:
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# 确保日志目录存在
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log_dir = os.path.dirname(log_file)
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if log_dir and not os.path.exists(log_dir):
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os.makedirs(log_dir)
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file_handler = logging.FileHandler(log_file, encoding='utf-8')
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file_handler.setFormatter(formatter)
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logger.addHandler(file_handler)
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logger.info(f"日志文件将保存至: {log_file}")
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except Exception as e:
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logger.warning(f"无法创建日志文件处理器: {str(e)}，仅输出至控制台")
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return logger
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def _load_forbidden_words(self, path):
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"""从txt文件加载违禁词列表"""
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words = set()
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if not os.path.exists(path):
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self.logger.warning(f"警告：未找到违禁词文件 {path}，将跳过违禁词检测")
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return words
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try:
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with open(path, 'r', encoding='utf-8') as f:
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# 去除每行首尾空格和换行符，过滤空行
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words = {line.strip() for line in f if line.strip()}
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self.logger.info(f"成功加载 {len(words)} 个违禁词。")
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except Exception as e:
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self.logger.error(f"加载违禁词文件失败：{str(e)}，将跳过违禁词检测")
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return words
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def _initialize_ocr(self):
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"""初始化RapidOCR引擎"""
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self.logger.info("正在初始化RapidOCR引擎...")
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config_path = r"D:\Git\bin\video\ocr\config\1.yaml"
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try:
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# 检查配置文件是否存在
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if not os.path.exists(config_path):
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self.logger.error(f"RapidOCR配置文件不存在: {config_path}")
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return None
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engine = RapidOCR(
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config_path=config_path
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)
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self.logger.info("RapidOCR引擎初始化成功。")
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return engine
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except Exception as e:
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self.logger.error(f"RapidOCR引擎初始化失败: {e}")
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return None
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def detect(self, frame):
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"""
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对单帧图像进行OCR，检测所有出现的违禁词并返回列表
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返回格式：(是否有违禁词, 违禁词列表, 对应的置信度列表)
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"""
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print("收到帧")
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if not self.ocr_engine or not self.forbidden_words:
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return False, [], []
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all_prohibited = [] # 存储所有检测到的违禁词
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all_confidences = [] # 存储对应违禁词的置信度
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try:
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# 执行OCR识别
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result = self.ocr_engine(frame)
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self.logger.debug(f"RapidOCR 原始返回结果: {result}")
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if result is None:
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return False, [], []
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# 提取文本和置信度（适配RapidOCR的结果格式）
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texts = result.txts if hasattr(result, 'txts') else []
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confidences = result.scores if hasattr(result, 'scores') else []
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# 遍历所有识别结果，收集所有违禁词
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for text, conf in zip(texts, confidences):
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if conf < self.OCR_CONFIDENCE_THRESHOLD:
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self.logger.debug(f"文本 '{text}' 置信度 {conf:.4f} 低于阈值，跳过")
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continue
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# 检查当前文本中是否包含多个违禁词
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for word in self.forbidden_words:
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if word in text:
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self.logger.warning(f"OCR检测到违禁词: '{word}' (来自文本: '{text}') 置信度: {conf:.4f}")
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all_prohibited.append(word)
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all_confidences.append(conf)
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except Exception as e:
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self.logger.error(f"OCR检测过程中发生错误: {e}", exc_info=True)
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# 返回检测结果（是否有违禁词、所有违禁词列表、对应置信度列表）
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return len(all_prohibited) > 0, all_prohibited, all_confidences
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