136 lines
5.1 KiB
Python
136 lines
5.1 KiB
Python
import os
|
||
import cv2
|
||
from rapidocr import RapidOCR
|
||
from logger_config import logger
|
||
|
||
|
||
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): # 降低阈值提高检出率
|
||
"""
|
||
初始化OCR引擎和违禁词列表。
|
||
|
||
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。
|
||
"""
|
||
self.forbidden_words = self._load_forbidden_words(forbidden_words_path)
|
||
self.ocr_engine = self._initialize_ocr()
|
||
self.OCR_CONFIDENCE_THRESHOLD = ocr_confidence_threshold
|
||
|
||
def _load_forbidden_words(self, path):
|
||
"""从txt文件加载违禁词列表（与rapidocr_test.py保持一致）"""
|
||
words = set()
|
||
if not os.path.exists(path):
|
||
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（不排除注释行，与测试代码统一）
|
||
words = {line.strip() for line in f if line.strip()}
|
||
logger.info(f"成功加载 {len(words)} 个违禁词。")
|
||
except Exception as e:
|
||
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"""
|
||
logger.info("正在初始化RapidOCR引擎...")
|
||
|
||
config_path = r".\config\1.yaml"
|
||
try:
|
||
engine = RapidOCR(
|
||
config_path=config_path
|
||
)
|
||
logger.info("RapidOCR引擎初始化成功。")
|
||
return engine
|
||
except Exception as e:
|
||
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)
|
||
"""
|
||
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（修正调用方式，与测试代码一致）
|
||
result = self.ocr_engine(frame)
|
||
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:
|
||
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:
|
||
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:
|
||
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_single_image():
|
||
# """测试单张图片的OCR违规检测（显示所有违禁词）"""
|
||
# TEST_IMAGE_PATH = r"ocr/images/img_7.png" # 修正路径格式
|
||
# FORBIDDEN_WORDS_PATH = r"ocr/forbidden_words.txt"
|
||
# CONFIDENCE_THRESHOLD = 0.5
|
||
#
|
||
# detector = OCRViolationDetector(
|
||
# forbidden_words_path=FORBIDDEN_WORDS_PATH,
|
||
# ocr_confidence_threshold=CONFIDENCE_THRESHOLD
|
||
# )
|
||
#
|
||
# if not os.path.exists(TEST_IMAGE_PATH):
|
||
# print(f"错误：图片文件不存在 - {TEST_IMAGE_PATH}")
|
||
# return
|
||
#
|
||
# frame = cv2.imread(TEST_IMAGE_PATH)
|
||
# if frame is None:
|
||
# print(f"错误：无法读取图片 - {TEST_IMAGE_PATH}")
|
||
# return
|
||
#
|
||
# # 执行检测
|
||
# has_violation, words, confidences = detector.detect(frame)
|
||
#
|
||
# # 输出所有检测到的违禁词
|
||
# if has_violation:
|
||
# print(f"测试结果：图片中共检测到 {len(words)} 个违禁词：")
|
||
# for word, conf in zip(words, confidences):
|
||
# print(f"- {word}（置信度：{conf:.4f}）")
|
||
# else:
|
||
# print("测试结果：图片中未检测到违禁词")
|
||
#
|
||
#
|
||
# if __name__ == "__main__":
|
||
# print("开始单张图片OCR违规检测测试...")
|
||
# test_single_image()
|
||
# print("测试完成") |