831 lines
34 KiB
Python
831 lines
34 KiB
Python
"""
|
||
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 fastapi import APIRouter, HTTPException, BackgroundTasks
|
||
|
||
from config import settings
|
||
from database.connection import db_manager
|
||
from models.face_feature import FeatureStatus
|
||
from models.video_check_task import SurVideoCheckTask
|
||
from models.sur_config import SurConfigBase
|
||
from models.sur_person import SurPersonBlacklist, SurFaceFeature
|
||
from repositories.face_feature_repository import FaceFeatureRepository
|
||
from algorithm.face_recognition_algorithm import FaceRecognitionAlgorithm
|
||
from biz.base_face_biz import BaseFaceBiz
|
||
from biz.video_check_biz import VideoCheckBiz
|
||
from biz.video_face_biz import VideoFaceBiz
|
||
from repositories.video_check_repository import VideoCheckTaskRepository
|
||
|
||
# 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)
|
||
|
||
# 初始化RTSP专用人脸识别算法
|
||
face_algorithm_for_rtsp = FaceRecognitionAlgorithm(use_gpu=settings.FACE_USE_GPU, use_npu=settings.FACE_USE_NPU)
|
||
|
||
# 初始化RTSP专用VideoFaceBiz实例
|
||
video_face_biz = VideoFaceBiz(face_algorithm_for_rtsp.get_app())
|
||
|
||
|
||
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:
|
||
# 直接创建BaseFaceBiz实例
|
||
face_biz = BaseFaceBiz(face_algorithm.get_app())
|
||
feature_vector = face_biz.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
|
||
|
||
|
||
async def process_pending_features():
|
||
"""
|
||
异步处理所有待处理的人脸特征计算
|
||
"""
|
||
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
|
||
for feature in timeout_features:
|
||
feature.status = FeatureStatus.FAILED
|
||
feature.finish_time = datetime.now()
|
||
|
||
if timeout_features:
|
||
session.commit()
|
||
|
||
# 处理待处理记录
|
||
processed_count = 0
|
||
|
||
for feature in pending_features:
|
||
processed_count += 1
|
||
process_feature_calculation(feature.id)
|
||
|
||
# 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}")
|
||
|
||
logger.info(f"特征计算处理完成: 共处理 {processed_count} 个特征")
|
||
|
||
except Exception as e:
|
||
logger.error(f"批量处理特征计算时发生异常: {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:
|
||
# 在后台任务中异步处理，避免阻塞请求
|
||
background_tasks.add_task(process_pending_features)
|
||
|
||
return {
|
||
"success": True,
|
||
"message": "收到特征值计算请求"
|
||
}
|
||
|
||
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)}")
|
||
|
||
|
||
def process_video_check_task(task_id: int) -> bool:
|
||
"""
|
||
处理单个视频检查任务
|
||
|
||
参数:
|
||
task_id: 任务ID
|
||
|
||
返回:
|
||
是否成功处理
|
||
"""
|
||
try:
|
||
with db_manager.get_session() as session:
|
||
repository = VideoCheckTaskRepository(session)
|
||
|
||
# 获取任务记录
|
||
task = repository.get_by_id(task_id)
|
||
if not task:
|
||
logger.error(f"视频检查任务不存在: {task_id}")
|
||
return False
|
||
|
||
# 检查是否已经处理完成
|
||
if task.status in [2, 3, 5]: # 完成、取消、失败
|
||
logger.info(f"视频检查任务已处理完成: {task_id}, 状态: {task.status}")
|
||
return True
|
||
|
||
# 检查是否超时
|
||
if task.status == 1: # 处理中
|
||
if task.start_time:
|
||
timeout_duration = timedelta(hours=settings.FACE_CAL_FEATURE_TIMEOUT_HOURS)
|
||
if datetime.now() - task.start_time > timeout_duration:
|
||
# 超时处理
|
||
repository.update_task_status(
|
||
task_id, 5, finish_time=datetime.now(),
|
||
result=0, result_data={"error": "任务超时"}
|
||
)
|
||
logger.warning(f"视频检查任务超时: {task_id}")
|
||
return False
|
||
else:
|
||
# 没有开始时间，重置状态
|
||
repository.update_task_status(task_id, 0)
|
||
|
||
# 处理未开始的任务
|
||
if task.status == 0: # 等待
|
||
# 设置状态为处理中
|
||
repository.update_task_status(task_id, 1, start_time=datetime.now())
|
||
logger.info(f"开始处理视频检查任务: {task_id}")
|
||
|
||
# 创建VideoCheckBiz实例
|
||
video_biz = VideoCheckBiz(face_algorithm.get_app())
|
||
|
||
# 获取配置参数
|
||
config_dict = repository.get_config_by_group_id(task.config_id)
|
||
|
||
# 设置VideoCheckBiz参数
|
||
if config_dict:
|
||
param_mapping = {
|
||
"face.list_mode": "list_mode",
|
||
"face.clarity_threshold": "clarity_threshold",
|
||
"face.min_face_size": "min_face_size",
|
||
"face.pitch_threshold": "pitch_threshold",
|
||
"face.yaw_threshold": "yaw_threshold",
|
||
"face.similarity_threshold": "similarity_threshold",
|
||
"face.skip_frame": "frame_skip"
|
||
}
|
||
|
||
for config_key, biz_param in param_mapping.items():
|
||
if config_key in config_dict:
|
||
try:
|
||
value = config_dict[config_key]
|
||
if biz_param == "list_mode":
|
||
video_biz.set_list_mode(value)
|
||
elif biz_param == "clarity_threshold":
|
||
video_biz.set_clarity_threshold(float(value))
|
||
elif biz_param == "min_face_size":
|
||
video_biz.set_min_face_size(int(value))
|
||
elif biz_param == "pitch_threshold":
|
||
video_biz.set_pitch_threshold(float(value))
|
||
elif biz_param == "yaw_threshold":
|
||
video_biz.set_yaw_threshold(float(value))
|
||
elif biz_param == "similarity_threshold":
|
||
video_biz.set_similarity_threshold(float(value))
|
||
elif biz_param == "frame_skip":
|
||
# frame_skip作为参数传递给方法，不设置到实例
|
||
pass
|
||
except (ValueError, TypeError) as e:
|
||
logger.warning(f"参数设置失败 {config_key}: {value}, 错误: {str(e)}")
|
||
|
||
# 获取目标视频路径
|
||
target_video = repository.get_video_by_id(int(task.target_video_id))
|
||
if not target_video:
|
||
logger.error(f"目标视频不存在: {task.target_video_id}")
|
||
repository.update_task_status(
|
||
task_id, 5, finish_time=datetime.now(),
|
||
result=0, result_data={"error": "目标视频不存在"}
|
||
)
|
||
return False
|
||
|
||
target_video_path = os.path.join(settings.VIDEO_RESOURCE_DIR, target_video.video_name_on_server)
|
||
|
||
if not os.path.exists(target_video_path):
|
||
logger.error(f"目标视频文件不存在: {target_video_path}")
|
||
repository.update_task_status(
|
||
task_id, 5, finish_time=datetime.now(),
|
||
result=0, result_data={"error": "目标视频文件不存在"}
|
||
)
|
||
return False
|
||
|
||
# 提取最佳人脸特征
|
||
frame_skip = int(config_dict.get("face.skip_frame", 10))
|
||
best_feature = video_biz.extract_best_face_from_video(target_video_path, frame_skip)
|
||
|
||
if best_feature is None:
|
||
logger.error(f"无法从目标视频中提取人脸特征: {task_id}")
|
||
repository.update_task_status(
|
||
task_id, 5, finish_time=datetime.now(),
|
||
result=0, result_data={"error": "无法从目标视频中提取人脸特征"}
|
||
)
|
||
return False
|
||
|
||
# 将特征值保存到数据库
|
||
feature_bytes = best_feature.tobytes()
|
||
|
||
# 设置黑名单（使用提取的特征）
|
||
video_biz.set_registered_faces({"target_person": best_feature})
|
||
|
||
# 获取待检查的视频列表
|
||
video_ids = [int(vid.strip()) for vid in task.video_id_list.split(",") if vid.strip()]
|
||
video_list = repository.get_videos_by_ids(video_ids)
|
||
|
||
if not video_list:
|
||
logger.error(f"待检查视频列表为空: {task_id}")
|
||
repository.update_task_status(
|
||
task_id, 5, finish_time=datetime.now(),
|
||
result=0, result_data={"error": "待检查视频列表为空"}
|
||
)
|
||
return False
|
||
|
||
# 构建视频信息列表
|
||
video_infos = []
|
||
for video in video_list:
|
||
video_path = os.path.join(settings.VIDEO_RESOURCE_DIR, video.video_name_on_server)
|
||
if os.path.exists(video_path):
|
||
video_infos.append({
|
||
'video_id': video.id,
|
||
'video_name': video.video_name,
|
||
'video_path': video_path
|
||
})
|
||
else:
|
||
logger.warning(f"视频文件不存在，跳过: {video_path}")
|
||
|
||
if not video_infos:
|
||
logger.error(f"所有待检查视频文件都不存在: {task_id}")
|
||
repository.update_task_status(
|
||
task_id, 5, finish_time=datetime.now(),
|
||
result=0, result_data={"error": "所有待检查视频文件都不存在"}
|
||
)
|
||
return False
|
||
|
||
# 批量处理视频进行黑名单检测
|
||
results = video_biz.batch_process_videos_with_blacklist_detection(
|
||
video_infos, frame_skip, "_checked"
|
||
)
|
||
|
||
# 分析结果
|
||
has_blacklist_match = any(result.get('has_blacklist_match', False) for result in results)
|
||
total_detections = sum(result.get('detection_count', 0) for result in results)
|
||
|
||
# 更新任务状态
|
||
result_status = 1 if has_blacklist_match else 2 # 1=找到，2=未找到
|
||
|
||
repository.update_task_status(
|
||
task_id, 2, finish_time=datetime.now(),
|
||
result=result_status, result_data={
|
||
"has_blacklist_match": has_blacklist_match,
|
||
"total_detections": total_detections,
|
||
"video_results": results,
|
||
"target_video": target_video_path,
|
||
"target_video_name": target_video.video_name,
|
||
"checked_videos": len(video_infos)
|
||
},
|
||
feature_data=feature_bytes
|
||
)
|
||
|
||
logger.info(f"视频检查任务完成: {task_id}, 结果: {'找到' if has_blacklist_match else '未找到'}")
|
||
return True
|
||
|
||
return True
|
||
|
||
except Exception as e:
|
||
logger.error(f"处理视频检查任务时发生异常: {task_id}, 错误: {str(e)}")
|
||
try:
|
||
with db_manager.get_session() as session:
|
||
repository = VideoCheckTaskRepository(session)
|
||
repository.update_task_status(
|
||
task_id, 5, finish_time=datetime.now(),
|
||
result=0, result_data={"error": str(e)}
|
||
)
|
||
except Exception:
|
||
pass
|
||
return False
|
||
|
||
|
||
async def process_pending_video_checks():
|
||
"""
|
||
异步处理所有待处理的视频检查任务
|
||
"""
|
||
try:
|
||
with db_manager.get_session() as session:
|
||
repository = VideoCheckTaskRepository(session)
|
||
|
||
# 查找需要处理的任务（status=0）
|
||
pending_tasks = repository.get_pending_tasks()
|
||
|
||
# 查找可能超时的任务（status=1且超时）
|
||
timeout_tasks = repository.get_timeout_tasks(settings.FACE_CAL_FEATURE_TIMEOUT_HOURS)
|
||
|
||
total_pending = len(pending_tasks)
|
||
total_timeout = len(timeout_tasks)
|
||
|
||
logger.info(f"发现待处理视频检查任务: {total_pending}个, 超时任务: {total_timeout}个")
|
||
|
||
# 处理超时任务
|
||
for task in timeout_tasks:
|
||
repository.update_task_status(
|
||
task.id, 5, finish_time=datetime.now(),
|
||
result=0, result_data={"error": "任务超时"}
|
||
)
|
||
|
||
if timeout_tasks:
|
||
session.commit()
|
||
|
||
# 处理待处理任务
|
||
processed_count = 0
|
||
|
||
for task in pending_tasks:
|
||
processed_count += 1
|
||
process_video_check_task(task.id)
|
||
|
||
# 每处理5个任务输出一次进度
|
||
if processed_count % 5 == 0:
|
||
logger.info(f"视频检查处理进度: {processed_count}/{total_pending}")
|
||
|
||
logger.info(f"视频检查任务处理完成: 共处理 {processed_count} 个任务")
|
||
|
||
except Exception as e:
|
||
logger.error(f"批量处理视频检查任务时发生异常: {str(e)}")
|
||
|
||
|
||
@router.post("/start-video-check", summary="开始视频检查")
|
||
async def start_video_check(background_tasks: BackgroundTasks):
|
||
"""
|
||
开始处理视频检查任务
|
||
|
||
此接口会:
|
||
1. 查找所有status为0的视频检查任务
|
||
2. 将状态改为1，设置开始时间
|
||
3. 提取目标视频中最佳人脸特征
|
||
4. 进行黑名单检测
|
||
5. 对于status为1且超时的任务，标记为失败
|
||
|
||
返回处理结果统计
|
||
"""
|
||
try:
|
||
# 在后台任务中异步处理，避免阻塞请求
|
||
background_tasks.add_task(process_pending_video_checks)
|
||
|
||
return {
|
||
"success": True,
|
||
"message": "收到视频检查请求"
|
||
}
|
||
|
||
except Exception as e:
|
||
logger.error(f"启动视频检查失败: {str(e)}")
|
||
raise HTTPException(status_code=500, detail=f"启动视频检查失败: {str(e)}")
|
||
|
||
|
||
@router.get("/video-check-status", summary="获取视频检查状态")
|
||
async def get_video_check_status():
|
||
"""
|
||
获取当前视频检查任务的状态统计
|
||
"""
|
||
try:
|
||
with db_manager.get_session() as session:
|
||
repository = VideoCheckTaskRepository(session)
|
||
|
||
# 获取统计信息
|
||
total_tasks = len(repository.session.query(SurVideoCheckTask).all())
|
||
pending_tasks = len(repository.get_pending_tasks())
|
||
processing_tasks = len(repository.get_processing_tasks())
|
||
|
||
# 获取已完成任务的统计
|
||
completed_tasks = repository.session.query(SurVideoCheckTask).filter(
|
||
SurVideoCheckTask.status == 2
|
||
).all()
|
||
|
||
found_count = sum(1 for task in completed_tasks if task.result == 1)
|
||
not_found_count = sum(1 for task in completed_tasks if task.result == 2)
|
||
failed_count = len(repository.session.query(SurVideoCheckTask).filter(
|
||
SurVideoCheckTask.status == 5
|
||
).all())
|
||
|
||
return {
|
||
"success": True,
|
||
"data": {
|
||
"total_tasks": total_tasks,
|
||
"pending_tasks": pending_tasks,
|
||
"processing_tasks": processing_tasks,
|
||
"completed_tasks": len(completed_tasks),
|
||
"found_count": found_count,
|
||
"not_found_count": not_found_count,
|
||
"failed_count": failed_count,
|
||
"timeout_hours": settings.FACE_CAL_FEATURE_TIMEOUT_HOURS
|
||
}
|
||
}
|
||
|
||
except Exception as e:
|
||
logger.error(f"获取视频检查状态失败: {str(e)}")
|
||
raise HTTPException(status_code=500, detail=f"获取视频检查状态失败: {str(e)}")
|
||
|
||
|
||
def sync_videofacebiz_params():
|
||
"""
|
||
同步VideoFaceBiz的参数
|
||
"""
|
||
try:
|
||
with db_manager.get_session() as session:
|
||
# 查询人脸识别配置（根据实际表结构）
|
||
config_records = session.query(SurConfigBase).filter(
|
||
SurConfigBase.config_type == settings.SUR_CONFIG_TYPE_FACE
|
||
).all()
|
||
|
||
# 构建配置参数字典
|
||
config_params = {}
|
||
for record in config_records:
|
||
if record.config_key and record.config_value:
|
||
config_params[record.config_key] = record.config_value
|
||
|
||
# 配置键映射关系
|
||
config_mapping = {
|
||
"face.list_mode": "list_mode",
|
||
"face.clarity_threshold": "clarity_threshold",
|
||
"face.min_face_size": "min_face_size",
|
||
"face.pitch_threshold": "pitch_threshold",
|
||
"face.yaw_threshold": "yaw_threshold",
|
||
"face.similarity_threshold": "similarity_threshold"
|
||
}
|
||
|
||
updated_count = 0
|
||
|
||
for config_key, param_name in config_mapping.items():
|
||
if config_key in config_params:
|
||
config_value = config_params[config_key]
|
||
|
||
# 根据参数类型进行转换和设置
|
||
if param_name == "list_mode":
|
||
if config_value in ["0", "1"]:
|
||
video_face_biz.set_list_mode(config_value)
|
||
updated_count += 1
|
||
elif param_name == "clarity_threshold":
|
||
try:
|
||
threshold = float(config_value)
|
||
video_face_biz.set_clarity_threshold(threshold)
|
||
updated_count += 1
|
||
except ValueError:
|
||
logger.error(f"无效的清晰度阈值: {config_value}")
|
||
elif param_name == "min_face_size":
|
||
try:
|
||
size = int(config_value)
|
||
video_face_biz.set_min_face_size(size)
|
||
updated_count += 1
|
||
except ValueError:
|
||
logger.error(f"无效的最小人脸尺寸: {config_value}")
|
||
elif param_name == "pitch_threshold":
|
||
try:
|
||
threshold = float(config_value)
|
||
video_face_biz.set_pitch_threshold(threshold)
|
||
updated_count += 1
|
||
except ValueError:
|
||
logger.error(f"无效的俯仰角阈值: {config_value}")
|
||
elif param_name == "yaw_threshold":
|
||
try:
|
||
threshold = float(config_value)
|
||
video_face_biz.set_yaw_threshold(threshold)
|
||
updated_count += 1
|
||
except ValueError:
|
||
logger.error(f"无效的偏航角阈值: {config_value}")
|
||
elif param_name == "similarity_threshold":
|
||
try:
|
||
threshold = float(config_value)
|
||
video_face_biz.set_similarity_threshold(threshold)
|
||
updated_count += 1
|
||
except ValueError:
|
||
logger.error(f"无效的相似度阈值: {config_value}")
|
||
|
||
logger.info(f"✅ 同步VideoFaceBiz参数完成，更新了 {updated_count} 个参数")
|
||
return updated_count
|
||
|
||
except Exception as e:
|
||
logger.error(f"❌ 同步VideoFaceBiz参数失败: {e}")
|
||
return 0
|
||
|
||
def sync_videofacebiz_blacklist():
|
||
"""
|
||
同步VideoFaceBiz的黑名单
|
||
"""
|
||
try:
|
||
with db_manager.get_session() as session:
|
||
# 查询启用的黑名单人员
|
||
blacklist_persons = session.query(SurPersonBlacklist).filter(
|
||
SurPersonBlacklist.status == 1
|
||
).all()
|
||
|
||
if not blacklist_persons:
|
||
logger.info("⚠️ 黑名单为空，清空当前黑名单")
|
||
video_face_biz.set_registered_faces({})
|
||
return 0
|
||
|
||
person_ids = [person.person_id for person in blacklist_persons]
|
||
|
||
# 查询对应的人脸特征
|
||
face_features = session.query(SurFaceFeature).filter(
|
||
SurFaceFeature.person_id.in_(person_ids),
|
||
SurFaceFeature.feature_type == settings.FACE_MODEL_VERSION,
|
||
SurFaceFeature.status == 2 # 计算成功的特征
|
||
).all()
|
||
|
||
# 构建特征字典
|
||
registered_faces = {}
|
||
loaded_count = 0
|
||
|
||
for feature in face_features:
|
||
if feature.feature_data:
|
||
try:
|
||
# 将bytea转换为numpy数组
|
||
import numpy as np
|
||
feature_array = np.frombuffer(feature.feature_data, dtype=np.float32)
|
||
|
||
# 使用person_id作为标识符
|
||
person_name = f"blacklist_{feature.person_id}"
|
||
registered_faces[person_name] = feature_array
|
||
loaded_count += 1
|
||
|
||
except Exception as e:
|
||
logger.error(f"❌ 解析黑名单人员 {feature.person_id} 的特征数据失败: {e}")
|
||
continue
|
||
|
||
# 设置黑名单
|
||
success = video_face_biz.set_registered_faces(registered_faces)
|
||
if success:
|
||
logger.info(f"✅ 同步黑名单完成，加载了 {loaded_count} 个黑名单人员")
|
||
else:
|
||
logger.error("❌ 设置黑名单失败")
|
||
|
||
return loaded_count
|
||
|
||
except Exception as e:
|
||
logger.error(f"❌ 同步黑名单失败: {e}")
|
||
return 0
|
||
|
||
@router.post("/sync-videofacebiz-params", summary="同步VideoFaceBiz参数")
|
||
async def sync_videofacebiz_params_endpoint():
|
||
"""
|
||
同步VideoFaceBiz的参数
|
||
|
||
从sur_config表同步参数到VideoFaceBiz实例
|
||
"""
|
||
try:
|
||
updated_count = sync_videofacebiz_params()
|
||
|
||
return {
|
||
"success": True,
|
||
"message": f"同步参数完成，更新了 {updated_count} 个参数",
|
||
"updated_count": updated_count
|
||
}
|
||
|
||
except Exception as e:
|
||
logger.error(f"同步VideoFaceBiz参数失败: {e}")
|
||
raise HTTPException(status_code=500, detail=f"同步参数失败: {str(e)}")
|
||
|
||
@router.post("/sync-videofacebiz-blacklist", summary="同步VideoFaceBiz黑名单")
|
||
async def sync_videofacebiz_blacklist_endpoint():
|
||
"""
|
||
同步VideoFaceBiz的黑名单
|
||
|
||
从sur_person_blacklist表同步黑名单到VideoFaceBiz实例
|
||
"""
|
||
try:
|
||
loaded_count = sync_videofacebiz_blacklist()
|
||
|
||
return {
|
||
"success": True,
|
||
"message": f"同步黑名单完成，加载了 {loaded_count} 个黑名单人员",
|
||
"loaded_count": loaded_count
|
||
}
|
||
|
||
except Exception as e:
|
||
logger.error(f"同步VideoFaceBiz黑名单失败: {e}")
|
||
raise HTTPException(status_code=500, detail=f"同步黑名单失败: {str(e)}")
|
||
|
||
@router.get("/videofacebiz-status", summary="获取VideoFaceBiz状态")
|
||
async def get_videofacebiz_status():
|
||
"""
|
||
获取VideoFaceBiz的当前状态
|
||
"""
|
||
try:
|
||
status = {
|
||
"list_mode": video_face_biz.get_list_mode(),
|
||
"clarity_threshold": video_face_biz.get_clarity_threshold(),
|
||
"min_face_size": video_face_biz.get_min_face_size(),
|
||
"pitch_threshold": video_face_biz.get_pitch_threshold(),
|
||
"yaw_threshold": video_face_biz.get_yaw_threshold(),
|
||
"similarity_threshold": video_face_biz.get_similarity_threshold(),
|
||
"blacklist_count": video_face_biz.get_registered_face_count()
|
||
}
|
||
|
||
return {
|
||
"success": True,
|
||
"data": status
|
||
}
|
||
|
||
except Exception as e:
|
||
logger.error(f"获取VideoFaceBiz状态失败: {e}")
|
||
raise HTTPException(status_code=500, detail=f"获取状态失败: {str(e)}")
|
||
|
||
# 导出路由器
|
||
__all__ = ["router"] |