video/ocr/model_violation_detector.py

import os

import cv2
import yaml
from pathlib import Path
from .ocr_violation_detector import OCRViolationDetector
from .yolo_violation_detector import ViolationDetector as YoloViolationDetector
from .face_recognizer import FaceRecognizer

class MultiModelViolationDetector:
    """
    多模型违规检测封装类，串行调用OCR、人脸识别和YOLO模型，任一模型检测到违规即返回结果
    """

    def __init__(self,
                 forbidden_words_path: str,
                 ocr_config_path: str,
                 yolo_model_path: str,
                 known_faces_dir: str,
                 ocr_confidence_threshold: float = 0.5):
        """
        初始化所有检测模型
        """
        # 初始化OCR检测器
        self.ocr_detector = OCRViolationDetector(
            forbidden_words_path=forbidden_words_path,
            ocr_config_path=ocr_config_path,
            ocr_confidence_threshold=ocr_confidence_threshold
        )

        # 初始化人脸识别器
        self.face_recognizer = FaceRecognizer(
            known_faces_dir=known_faces_dir
        )

        # 初始化YOLO检测器
        self.yolo_detector = YoloViolationDetector(
            model_path=yolo_model_path
        )

        print("多模型违规检测器初始化完成")

    def detect_violations(self, frame):
        """
        串行调用三个检测模型（OCR → 人脸识别 → YOLO），任一检测到违规即返回结果
        """
        # 1. 首先进行OCR违禁词检测
        try:
            ocr_has_violation, ocr_words, ocr_confs = self.ocr_detector.detect(frame)
            if ocr_has_violation:
                details = {
                    "words": ocr_words,
                    "confidences": ocr_confs
                }
                print(f"警告: OCR检测到违禁内容: {details}")
                return (True, "ocr", details)
        except Exception as e:
            print(f"错误: OCR检测出错: {str(e)}")

        # 2. 接着进行人脸识别检测
        try:
            face_has_violation, face_name, face_similarity = self.face_recognizer.recognize(frame)
            if face_has_violation:
                details = {
                    "name": face_name,
                    "similarity": face_similarity
                }
                print(f"警告: 人脸识别到违规人员: {details}")
                return (True, "face", details)
        except Exception as e:
            print(f"错误: 人脸识别出错: {str(e)}")

        # 3. 最后进行YOLO目标检测
        try:
            yolo_results = self.yolo_detector.detect(frame)
            if len(yolo_results.boxes) > 0:
                details = {
                    "classes": yolo_results.names,
                    "boxes": yolo_results.boxes.xyxy.tolist(),
                    "confidences": yolo_results.boxes.conf.tolist(),
                    "class_ids": yolo_results.boxes.cls.tolist()
                }
                print(f"警告: YOLO检测到违规目标: {details}")
                return (True, "yolo", details)
        except Exception as e:
            print(f"错误: YOLO检测出错: {str(e)}")

        # 所有检测均未发现违规
        return (False, None, None)


def load_config(config_path: str) -> dict:
    """加载YAML配置文件"""
    try:
        with open(config_path, 'r', encoding='utf-8') as f:
            return yaml.safe_load(f)
    except FileNotFoundError:
        print(f"错误: 配置文件未找到: {config_path}")
        raise
    except yaml.YAMLError as e:
        print(f"错误: 配置文件格式错误: {config_path}, 错误: {str(e)}")
        raise
    except Exception as e:
        print(f"错误: 加载配置文件出错: {str(e)}")
        raise


# 使用示例
# if __name__ == "__main__":
#     # 加载配置文件
#     config = load_config("config.yaml")  # 配置文件路径，可根据实际情况修改
#
#     # 初始化多模型检测器
#     detector = MultiModelViolationDetector(
#         forbidden_words_path=config["forbidden_words_path"],
#         ocr_config_path=config["ocr_config_path"],
#         yolo_model_path=config["yolo_model_path"],
#         known_faces_dir=config["known_faces_dir"],
#         ocr_confidence_threshold=config.get("ocr_confidence_threshold", 0.5)
#     )
#
#     # 读取测试图像（可替换为视频帧读取逻辑）
#     test_image_path = config.get("test_image_path")  # 从配置文件获取测试图片路径
#     if test_image_path:
#         frame = cv2.imread(test_image_path)
#
#         if frame is not None:
#             has_violation, violation_type, details = detector.detect_violations(frame)
#             if has_violation:
#                 print(f"检测到违规 - 类型: {violation_type}, 详情: {details}")
#             else:
#                 print("未检测到任何违规内容")
#         else:
#             print(f"无法读取测试图像: {test_image_path}")
#     else:
#         print("配置文件中未指定测试图像路径")