233 lines
8.8 KiB
Python
233 lines
8.8 KiB
Python
import os
|
||
import cv2
|
||
import logging
|
||
from rapidocr import RapidOCR
|
||
|
||
|
||
class OCRViolationDetector:
|
||
"""
|
||
封装RapidOCR引擎，用于检测图像帧中的违禁词。
|
||
"""
|
||
|
||
def __init__(self, forbidden_words_path: str, ocr_confidence_threshold: float = 0.5,
|
||
log_level: int = logging.INFO, log_file: str = None):
|
||
"""
|
||
初始化OCR引擎、违禁词列表和日志配置。
|
||
|
||
Args:
|
||
forbidden_words_path (str): 违禁词列表 .txt 文件的路径。
|
||
ocr_confidence_threshold (float): OCR识别结果的置信度阈值。
|
||
log_level (int): 日志级别，默认为logging.INFO
|
||
log_file (str, optional): 日志文件路径，如不提供则只输出到控制台
|
||
"""
|
||
# 初始化日志
|
||
self.logger = self._setup_logger(log_level, log_file)
|
||
|
||
# 加载违禁词
|
||
self.forbidden_words = self._load_forbidden_words(forbidden_words_path)
|
||
|
||
# 初始化OCR引擎
|
||
self.ocr_engine = self._initialize_ocr()
|
||
|
||
# 设置置信度阈值
|
||
self.OCR_CONFIDENCE_THRESHOLD = ocr_confidence_threshold
|
||
self.logger.info(f"OCR置信度阈值设置为: {ocr_confidence_threshold}")
|
||
|
||
def _setup_logger(self, log_level: int, log_file: str = None) -> logging.Logger:
|
||
"""
|
||
配置日志系统
|
||
|
||
Args:
|
||
log_level: 日志级别
|
||
log_file: 日志文件路径，如为None则只输出到控制台
|
||
|
||
Returns:
|
||
配置好的logger实例
|
||
"""
|
||
# 创建logger
|
||
logger = logging.getLogger('OCRViolationDetector')
|
||
logger.setLevel(log_level)
|
||
|
||
# 避免重复添加处理器
|
||
if logger.handlers:
|
||
return logger
|
||
|
||
# 定义日志格式
|
||
formatter = logging.Formatter(
|
||
'%(asctime)s - %(name)s - %(levelname)s - %(message)s'
|
||
)
|
||
|
||
# 添加控制台处理器
|
||
console_handler = logging.StreamHandler()
|
||
console_handler.setFormatter(formatter)
|
||
logger.addHandler(console_handler)
|
||
|
||
# 如果提供了日志文件路径，则添加文件处理器
|
||
if log_file:
|
||
try:
|
||
# 确保日志目录存在
|
||
log_dir = os.path.dirname(log_file)
|
||
if log_dir and not os.path.exists(log_dir):
|
||
os.makedirs(log_dir)
|
||
|
||
file_handler = logging.FileHandler(log_file, encoding='utf-8')
|
||
file_handler.setFormatter(formatter)
|
||
logger.addHandler(file_handler)
|
||
logger.info(f"日志文件将保存至: {log_file}")
|
||
except Exception as e:
|
||
logger.warning(f"无法创建日志文件处理器: {str(e)}，仅输出至控制台")
|
||
|
||
return logger
|
||
|
||
def _load_forbidden_words(self, path):
|
||
"""从txt文件加载违禁词列表"""
|
||
words = set()
|
||
if not os.path.exists(path):
|
||
self.logger.warning(f"警告：未找到违禁词文件 {path}，将跳过违禁词检测")
|
||
return words
|
||
|
||
try:
|
||
with open(path, 'r', encoding='utf-8') as f:
|
||
# 去除每行首尾空格和换行符，过滤空行
|
||
words = {line.strip() for line in f if line.strip()}
|
||
self.logger.info(f"成功加载 {len(words)} 个违禁词。")
|
||
except Exception as e:
|
||
self.logger.error(f"加载违禁词文件失败：{str(e)}，将跳过违禁词检测")
|
||
return words
|
||
|
||
def _initialize_ocr(self):
|
||
"""初始化RapidOCR引擎"""
|
||
self.logger.info("正在初始化RapidOCR引擎...")
|
||
|
||
config_path = r"D:\Git\bin\video\ocr\config\1.yaml"
|
||
try:
|
||
# 检查配置文件是否存在
|
||
if not os.path.exists(config_path):
|
||
self.logger.error(f"RapidOCR配置文件不存在: {config_path}")
|
||
return None
|
||
|
||
engine = RapidOCR(
|
||
config_path=config_path
|
||
)
|
||
self.logger.info("RapidOCR引擎初始化成功。")
|
||
return engine
|
||
except Exception as e:
|
||
self.logger.error(f"RapidOCR引擎初始化失败: {e}")
|
||
return None
|
||
|
||
def detect(self, frame):
|
||
"""
|
||
对单帧图像进行OCR，检测所有出现的违禁词并返回列表
|
||
返回格式：(是否有违禁词, 违禁词列表, 对应的置信度列表)
|
||
"""
|
||
print("收到帧")
|
||
if not self.ocr_engine or not self.forbidden_words:
|
||
return False, [], []
|
||
|
||
all_prohibited = [] # 存储所有检测到的违禁词
|
||
all_confidences = [] # 存储对应违禁词的置信度
|
||
|
||
try:
|
||
# 执行OCR识别
|
||
result = self.ocr_engine(frame)
|
||
self.logger.debug(f"RapidOCR 原始返回结果: {result}")
|
||
|
||
if result is None:
|
||
return False, [], []
|
||
|
||
# 提取文本和置信度（适配RapidOCR的结果格式）
|
||
texts = result.txts if hasattr(result, 'txts') else []
|
||
confidences = result.scores if hasattr(result, 'scores') else []
|
||
|
||
# 遍历所有识别结果，收集所有违禁词
|
||
for text, conf in zip(texts, confidences):
|
||
if conf < self.OCR_CONFIDENCE_THRESHOLD:
|
||
self.logger.debug(f"文本 '{text}' 置信度 {conf:.4f} 低于阈值，跳过")
|
||
continue
|
||
|
||
# 检查当前文本中是否包含多个违禁词
|
||
for word in self.forbidden_words:
|
||
if word in text:
|
||
self.logger.warning(f"OCR检测到违禁词: '{word}' (来自文本: '{text}') 置信度: {conf:.4f}")
|
||
all_prohibited.append(word)
|
||
all_confidences.append(conf)
|
||
|
||
except Exception as e:
|
||
self.logger.error(f"OCR检测过程中发生错误: {e}", exc_info=True)
|
||
|
||
# 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）
|
||
return len(all_prohibited) > 0, all_prohibited, all_confidences
|
||
|
||
# def test_image(self, image_path: str, show_image: bool = True) -> tuple:
|
||
# """
|
||
# 对单张图片进行OCR违禁词检测并展示结果
|
||
#
|
||
# Args:
|
||
# image_path (str): 图片文件路径
|
||
# show_image (bool): 是否显示图片，默认为True
|
||
#
|
||
# Returns:
|
||
# tuple: (是否有违禁词, 违禁词列表, 对应的置信度列表)
|
||
# """
|
||
# # 检查图片文件是否存在
|
||
# if not os.path.exists(image_path):
|
||
# self.logger.error(f"图片文件不存在: {image_path}")
|
||
# return False, [], []
|
||
#
|
||
# try:
|
||
# # 读取图片
|
||
# frame = cv2.imread(image_path)
|
||
# if frame is None:
|
||
# self.logger.error(f"无法读取图片: {image_path}")
|
||
# return False, [], []
|
||
#
|
||
# self.logger.info(f"开始处理图片: {image_path}")
|
||
#
|
||
# # 调用检测方法
|
||
# has_violation, violations, confidences = self.detect(frame)
|
||
#
|
||
# # 输出检测结果
|
||
# if has_violation:
|
||
# self.logger.info(f"在图片中检测到 {len(violations)} 个违禁词:")
|
||
# for word, conf in zip(violations, confidences):
|
||
# self.logger.info(f"- {word} (置信度: {conf:.4f})")
|
||
# else:
|
||
# self.logger.info("图片中未检测到违禁词")
|
||
|
||
# # 显示图片（如果需要）
|
||
# if show_image:
|
||
# # 调整图片大小以便于显示（如果太大）
|
||
# height, width = frame.shape[:2]
|
||
# max_size = 800
|
||
# if max(height, width) > max_size:
|
||
# scale = max_size / max(height, width)
|
||
# frame = cv2.resize(frame, None, fx=scale, fy=scale)
|
||
#
|
||
# cv2.imshow(f"OCR检测结果: {'发现违禁词' if has_violation else '未发现违禁词'}", frame)
|
||
# cv2.waitKey(0) # 等待用户按键
|
||
# cv2.destroyAllWindows()
|
||
#
|
||
# return has_violation, violations, confidences
|
||
#
|
||
# except Exception as e:
|
||
# self.logger.error(f"处理图片时发生错误: {str(e)}", exc_info=True)
|
||
# return False, [], []
|
||
#
|
||
#
|
||
# # 使用示例
|
||
# if __name__ == "__main__":
|
||
# # 配置参数
|
||
# forbidden_words_path = "forbidden_words.txt" # 违禁词文件路径
|
||
# test_image_path = r"D:\Git\bin\video\ocr\images\img_7.png" # 测试图片路径
|
||
# ocr_threshold = 0.6 # OCR置信度阈值
|
||
#
|
||
# # 创建检测器实例
|
||
# detector = OCRViolationDetector(
|
||
# forbidden_words_path=forbidden_words_path,
|
||
# ocr_confidence_threshold=ocr_threshold,
|
||
# log_level=logging.INFO,
|
||
# log_file="ocr_detection.log"
|
||
# )
|
||
#
|
||
# # 测试图片
|
||
# detector.test_image(test_image_path, show_image=True) |