From 3a4bcab9917064a5142294c9cb7cf8ed05067eef Mon Sep 17 00:00:00 2001 From: zqc <835569504@qq.com> Date: Sat, 20 Dec 2025 20:08:52 +0800 Subject: [PATCH] =?UTF-8?q?=E5=AE=8C=E6=88=90=E4=BA=BA=E8=84=B8=E8=AE=A1?= =?UTF-8?q?=E7=AE=97=E4=BB=BB=E5=8A=A1=E8=B0=83=E7=94=A8=E6=96=B9=E6=B3=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- src/api/routes/algorithm_router.py | 315 ++++++++++++++++++++ src/app.py | 6 + src/config.py | 8 + src/face_recognition_algorithm.py | 72 ++++- src/main.py | 2 +- src/repositories/face_feature_repository.py | 81 ++++- 6 files changed, 481 insertions(+), 3 deletions(-) create mode 100644 src/api/routes/algorithm_router.py diff --git a/src/api/routes/algorithm_router.py b/src/api/routes/algorithm_router.py new file mode 100644 index 0000000..4b040d6 --- /dev/null +++ b/src/api/routes/algorithm_router.py @@ -0,0 +1,315 @@ +""" +人脸特征计算算法路由 +提供人脸特征计算的HTTP接口 +""" + +import os +import logging +from datetime import datetime, timedelta +from typing import Dict, Any + +from fastapi import APIRouter, HTTPException, BackgroundTasks +from sqlalchemy.orm import Session + +from src.config import settings +from src.database.connection import db_manager +from src.models.face_feature import SurFaceFeature, FeatureStatus +from src.repositories.face_feature_repository import FaceFeatureRepository +from src.face_recognition_algorithm import FaceRecognitionAlgorithm + +# 创建路由器 +router = APIRouter(prefix="/algorithm", tags=["algorithm"]) + +# 初始化人脸识别算法 +face_algorithm = FaceRecognitionAlgorithm(use_gpu=settings.FACE_USE_GPU, use_npu=settings.FACE_USE_NPU) + +logger = logging.getLogger(__name__) + + +def process_feature_calculation(feature_id: int) -> bool: + """ + 处理单个人脸特征计算 + + 参数: + feature_id: 特征记录ID + + 返回: + 是否成功处理 + """ + try: + with db_manager.get_session() as session: + repository = FaceFeatureRepository(session) + + # 获取特征记录 + feature = repository.get_by_id(feature_id) + if not feature: + logger.error(f"特征记录不存在: {feature_id}") + return False + + # 检查是否已经处理完成 + if feature.status in [FeatureStatus.SUCCESS, FeatureStatus.FAILED]: + logger.info(f"特征记录已处理完成: {feature_id}, 状态: {feature.status_name}") + return True + + # 检查是否超时 + if feature.status == FeatureStatus.PROCESSING: + if feature.start_time: + timeout_duration = timedelta(hours=settings.FACE_CAL_FEATURE_TIMEOUT_HOURS) + if datetime.now() - feature.start_time > timeout_duration: + # 超时处理 + feature.status = FeatureStatus.FAILED + feature.finish_time = datetime.now() + session.commit() + logger.warning(f"特征计算超时: {feature_id}") + return False + else: + # 没有开始时间，重置状态 + feature.status = FeatureStatus.NOT_STARTED + session.commit() + + # 处理未开始的计算 + if feature.status == FeatureStatus.NOT_STARTED: + # 设置状态为计算中 + feature.status = FeatureStatus.PROCESSING + feature.start_time = datetime.now() + session.commit() + logger.info(f"开始计算特征: {feature_id}") + + # 构建图片路径 + if not feature.pic_id: + logger.error(f"特征记录缺少图片ID: {feature_id}") + feature.status = FeatureStatus.FAILED + feature.finish_time = datetime.now() + session.commit() + return False + + image_path = os.path.join(settings.FACE_REGISTER_IMAGE_RESOURCE_DIR, feature.pic_id) + + # 检查图片文件是否存在 + if not os.path.exists(image_path): + logger.error(f"图片文件不存在: {image_path}") + feature.status = FeatureStatus.FAILED + feature.finish_time = datetime.now() + session.commit() + return False + + # 提取人脸特征 + try: + feature_vector = face_algorithm.extract_face_feature(str(image_path)) + + if feature_vector is not None: + # 转换为二进制数据 + feature_bytes = feature_vector.tobytes() + feature.feature_data = feature_bytes + feature.status = FeatureStatus.SUCCESS + feature.finish_time = datetime.now() + session.commit() + logger.info(f"特征计算成功: {feature_id}, 特征向量长度: {len(feature_vector)}") + return True + else: + logger.error(f"特征提取失败: {feature_id}") + feature.status = FeatureStatus.FAILED + feature.finish_time = datetime.now() + session.commit() + return False + + except Exception as e: + logger.error(f"特征计算过程中出错: {feature_id}, 错误: {str(e)}") + feature.status = FeatureStatus.FAILED + feature.finish_time = datetime.now() + session.commit() + return False + + return True + + except Exception as e: + logger.error(f"处理特征计算时发生异常: {feature_id}, 错误: {str(e)}") + return False + + +def process_pending_features() -> Dict[str, Any]: + """ + 处理所有待处理的人脸特征计算 + + 返回: + 处理结果统计 + """ + try: + with db_manager.get_session() as session: + repository = FaceFeatureRepository(session) + + # 查找需要处理的记录 + # 条件: feature_type = FACE_MODEL_VERSION 且 status = 0 (未开始) + pending_features = repository.get_features_by_type_and_status( + feature_type=settings.FACE_MODEL_VERSION, + status=FeatureStatus.NOT_STARTED + ) + + # 查找可能超时的记录 (status = 1 且超时) + timeout_features = [] + processing_features = repository.get_features_by_type_and_status( + feature_type=settings.FACE_MODEL_VERSION, + status=FeatureStatus.PROCESSING + ) + + for feature in processing_features: + if feature.start_time: + timeout_duration = timedelta(hours=settings.FACE_CAL_FEATURE_TIMEOUT_HOURS) + if datetime.now() - feature.start_time > timeout_duration: + timeout_features.append(feature) + + total_pending = len(pending_features) + total_timeout = len(timeout_features) + + logger.info(f"发现待处理特征: {total_pending}个, 超时特征: {total_timeout}个") + + # 处理超时记录 + timeout_success = 0 + for feature in timeout_features: + feature.status = FeatureStatus.FAILED + feature.finish_time = datetime.now() + timeout_success += 1 + + if timeout_features: + session.commit() + + # 处理待处理记录 + processed_count = 0 + success_count = 0 + + for feature in pending_features: + processed_count += 1 + if process_feature_calculation(feature.id): + success_count += 1 + + # 每处理10个记录输出一次进度 + if processed_count % 10 == 0: + logger.info(f"处理进度: {processed_count}/{total_pending}") + + return { + "total_pending": total_pending, + "total_timeout": total_timeout, + "processed_count": processed_count, + "success_count": success_count, + "timeout_handled": timeout_success + } + + except Exception as e: + logger.error(f"批量处理特征计算时发生异常: {str(e)}") + return { + "total_pending": 0, + "total_timeout": 0, + "processed_count": 0, + "success_count": 0, + "timeout_handled": 0, + "error": str(e) + } + + +@router.post("/start-feature-calculation", summary="开始人脸特征计算") +async def start_feature_calculation(background_tasks: BackgroundTasks): + """ + 开始处理人脸特征计算 + + 此接口会: + 1. 查找所有feature_type为当前模型版本且status为0的记录 + 2. 将状态改为1，设置开始时间 + 3. 提取人脸特征值 + 4. 对于status为1且超时的记录，标记为失败 + + 返回处理结果统计 + """ + try: + # 在后台任务中处理，避免阻塞请求 + result = process_pending_features() + + return { + "success": True, + "message": "特征计算处理完成", + "data": result + } + + except Exception as e: + logger.error(f"启动特征计算失败: {str(e)}") + raise HTTPException(status_code=500, detail=f"启动特征计算失败: {str(e)}") + + +@router.get("/feature-calculation-status", summary="获取特征计算状态") +async def get_feature_calculation_status(): + """ + 获取当前特征计算的状态统计 + """ + try: + with db_manager.get_session() as session: + repository = FaceFeatureRepository(session) + + # 获取统计信息 + stats = repository.get_statistics() + + # 获取当前模型版本的特定统计 + current_model_stats = { + "total": repository.count_by_type_and_status( + feature_type=settings.FACE_MODEL_VERSION + ), + "not_started": repository.count_by_type_and_status( + feature_type=settings.FACE_MODEL_VERSION, + status=FeatureStatus.NOT_STARTED + ), + "processing": repository.count_by_type_and_status( + feature_type=settings.FACE_MODEL_VERSION, + status=FeatureStatus.PROCESSING + ), + "success": repository.count_by_type_and_status( + feature_type=settings.FACE_MODEL_VERSION, + status=FeatureStatus.SUCCESS + ), + "failed": repository.count_by_type_and_status( + feature_type=settings.FACE_MODEL_VERSION, + status=FeatureStatus.FAILED + ) + } + + return { + "success": True, + "data": { + "overall_stats": stats, + "current_model_stats": current_model_stats, + "model_version": settings.FACE_MODEL_VERSION, + "timeout_hours": settings.FACE_CAL_FEATURE_TIMEOUT_HOURS + } + } + + except Exception as e: + logger.error(f"获取特征计算状态失败: {str(e)}") + raise HTTPException(status_code=500, detail=f"获取特征计算状态失败: {str(e)}") + + +@router.post("/calculate-single-feature/{feature_id}", summary="计算单个特征") +async def calculate_single_feature(feature_id: int): + """ + 计算单个特征记录的人脸特征 + + 参数: + feature_id: 特征记录ID + """ + try: + success = process_feature_calculation(feature_id) + + if success: + return { + "success": True, + "message": f"特征计算完成: {feature_id}" + } + else: + return { + "success": False, + "message": f"特征计算失败: {feature_id}" + } + + except Exception as e: + logger.error(f"计算单个特征失败: {feature_id}, 错误: {str(e)}") + raise HTTPException(status_code=500, detail=f"计算单个特征失败: {str(e)}") + + +# 导出路由器 +__all__ = ["router"] \ No newline at end of file diff --git a/src/app.py b/src/app.py index 9d79a13..8c8bb8d 100644 --- a/src/app.py +++ b/src/app.py @@ -18,6 +18,7 @@ from fastapi.openapi.docs import ( from fastapi.staticfiles import StaticFiles from src.api.routes import face_features +from src.api.routes.algorithm_router import router as algorithm_router from src.api.errors import ( APIError, validation_exception_handler, @@ -166,6 +167,11 @@ app.include_router( prefix=settings.API_V1_PREFIX ) +app.include_router( + algorithm_router, + prefix=settings.API_V1_PREFIX +) + # 自定义404处理器 @app.exception_handler(404) diff --git a/src/config.py b/src/config.py index 81d1cce..8c8a718 100644 --- a/src/config.py +++ b/src/config.py @@ -47,6 +47,14 @@ class Settings(BaseSettings): # 异步配置 ASYNC_MODE: bool = False + # 资源文件夹配置 + FACE_REGISTER_IMAGE_RESOURCE_DIR: str = "D:/ruoyi/uploadPath/face" + VIDEO_RESOURCE_DIR: str = "D:/ruoyi/uploadPath/video" + FACE_CAL_FEATURE_TIMEOUT_HOURS: int = 10 + FACE_MODEL_VERSION: int = 0 #insight_face_buffalo_l + FACE_USE_GPU: bool = True + FACE_USE_NPU: bool = False + # JWT配置（预留） SECRET_KEY: str = "your-secret-key-here-change-in-production" ALGORITHM: str = "HS256" diff --git a/src/face_recognition_algorithm.py b/src/face_recognition_algorithm.py index c9e63c0..54796f5 100644 --- a/src/face_recognition_algorithm.py +++ b/src/face_recognition_algorithm.py @@ -487,4 +487,74 @@ class FaceRecognitionAlgorithm: def get_list_mode(self) -> str: """获取当前名单模式""" - return self.list_mode \ No newline at end of file + return self.list_mode + + def extract_face_feature(self, image_path: str) -> Optional[np.ndarray]: + """ + 从单张图片中提取人脸特征值 + + 参数: + image_path: 人脸图片路径 + + 返回: + numpy数组格式的人脸特征值，如果检测失败返回None + """ + if not os.path.exists(image_path): + print(f"❌ 图片文件不存在: {image_path}") + return None + + # 读取图片 + img = cv2.imread(image_path) + if img is None: + print(f"❌ 无法读取图片: {image_path}") + return None + + # 人脸检测 + faces = self.app.get(img) + if not faces: + print(f"❌ 图片中未检测到人脸: {image_path}") + return None + + # 使用第一张检测到的人脸 + face = faces[0] + + # 检查人脸质量 + is_acceptable, quality_metrics = self.is_face_quality_acceptable(face, img) + + if not is_acceptable: + print(f"⚠️ 人脸质量不可接受: {image_path}") + print(f" 质量得分: {quality_metrics['quality_score']:.3f}") + print(f" 清晰度: {quality_metrics['clarity_score']:.1f}") + print(f" 姿态角度: pitch={quality_metrics['pitch']:.1f}°, yaw={quality_metrics['yaw']:.1f}°") + return None + + print(f"✅ 成功提取人脸特征: {image_path}") + print(f" 检测得分: {quality_metrics['det_score']:.3f}") + print(f" 质量得分: {quality_metrics['quality_score']:.3f}") + + # 返回特征向量 + return face.embedding + + def extract_face_features_batch(self, image_paths: List[str]) -> Dict[str, Optional[np.ndarray]]: + """ + 批量从多张图片中提取人脸特征值 + + 参数: + image_paths: 人脸图片路径列表 + + 返回: + 字典格式 {图片路径: 特征值}，失败的特征值为None + """ + results = {} + + for image_path in image_paths: + feature = self.extract_face_feature(image_path) + results[image_path] = feature + + # 统计结果 + success_count = sum(1 for feature in results.values() if feature is not None) + total_count = len(image_paths) + + print(f"🎉 批量提取完成: 成功 {success_count}/{total_count} 张图片") + + return results \ No newline at end of file diff --git a/src/main.py b/src/main.py index 96a4536..4d8b459 100644 --- a/src/main.py +++ b/src/main.py @@ -37,7 +37,7 @@ def demo_sync_operations(): print("\n1. 创建特征记录") # 固定的测试ID - test_person_id = 1001 + test_person_id = 10 test_feature_type = 1 # 检查是否已存在 diff --git a/src/repositories/face_feature_repository.py b/src/repositories/face_feature_repository.py index 0d7d1f1..e87a67b 100644 --- a/src/repositories/face_feature_repository.py +++ b/src/repositories/face_feature_repository.py @@ -594,4 +594,83 @@ class FaceFeatureRepository: except SQLAlchemyError as e: logger.error(f"Database error cleaning up old features: {e}") self.session.rollback() - raise \ No newline at end of file + raise + + # ===== 新增方法：支持算法路由 ===== + + def get_features_by_type_and_status( + self, + feature_type: int, + status: Optional[int] = None + ) -> List[SurFaceFeature]: + """ + 根据特征类型和状态获取特征记录 + + Args: + feature_type: 特征类型 + status: 状态（可选） + + Returns: + 特征记录列表 + """ + try: + conditions = [SurFaceFeature.feature_type == feature_type] + + if status is not None: + conditions.append(SurFaceFeature.status == status) + + stmt = ( + select(SurFaceFeature) + .where(and_(*conditions)) + .order_by(asc(SurFaceFeature.created_time)) + ) + + result = self.session.execute(stmt) + features = list(result.scalars().all()) + + logger.debug(f"Retrieved {len(features)} features by type={feature_type}, status={status}") + return features + + except SQLAlchemyError as e: + logger.error(f"Database error getting features by type and status: {e}") + raise + + def count_by_type_and_status( + self, + feature_type: int, + status: Optional[int] = None + ) -> int: + """ + 统计指定特征类型和状态的记录数量 + + Args: + feature_type: 特征类型 + status: 状态（可选） + + Returns: + 记录数量 + """ + try: + conditions = [SurFaceFeature.feature_type == feature_type] + + if status is not None: + conditions.append(SurFaceFeature.status == status) + + stmt = select(func.count()).select_from(SurFaceFeature).where(and_(*conditions)) + result = self.session.execute(stmt) + count = result.scalar_one() + + return count + + except SQLAlchemyError as e: + logger.error(f"Database error counting features by type and status: {e}") + raise + + def get_statistics(self) -> Dict[str, Any]: + """ + 获取统计信息（兼容性方法） + + Returns: + 统计信息字典 + """ + return self.get_stats() \ No newline at end of file