修改路径，从src放到根目录
This commit is contained in:
831
api/routes/algorithm_router.py
Normal file
831
api/routes/algorithm_router.py
Normal file
@@ -0,0 +1,831 @@
|
||||
"""
|
||||
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"]
|
||||
417
api/routes/face_features.py
Normal file
417
api/routes/face_features.py
Normal file
@@ -0,0 +1,417 @@
|
||||
"""
|
||||
人脸特征API路由
|
||||
"""
|
||||
|
||||
from typing import List, Optional
|
||||
from datetime import datetime
|
||||
from fastapi import APIRouter, Depends, HTTPException, status, Query, BackgroundTasks
|
||||
from fastapi.responses import JSONResponse
|
||||
|
||||
from schemas.face_feature import (
|
||||
FaceFeatureCreate,
|
||||
FaceFeatureUpdate,
|
||||
FaceFeatureQuery,
|
||||
FaceFeatureResponse,
|
||||
FaceFeatureListResponse,
|
||||
FaceFeatureStatsResponse,
|
||||
BatchFaceFeatureCreate,
|
||||
FeatureStatus
|
||||
)
|
||||
from api.dependencies import (
|
||||
get_face_feature_service,
|
||||
get_face_feature_by_id
|
||||
)
|
||||
from services.face_feature_service import FaceFeatureService
|
||||
from api.errors import (
|
||||
FaceFeatureProcessingError,
|
||||
FeatureNotFoundError,
|
||||
DuplicateFeatureError
|
||||
)
|
||||
from config import settings
|
||||
|
||||
# 创建路由器
|
||||
router = APIRouter(
|
||||
prefix="/face-features",
|
||||
tags=["人脸特征管理"],
|
||||
responses={
|
||||
404: {"description": "资源不存在"},
|
||||
400: {"description": "请求参数错误"},
|
||||
500: {"description": "服务器内部错误"}
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
@router.post(
|
||||
"/",
|
||||
response_model=FaceFeatureResponse,
|
||||
status_code=status.HTTP_201_CREATED,
|
||||
summary="创建人脸特征记录",
|
||||
description="创建新的人脸特征记录"
|
||||
)
|
||||
async def create_face_feature(
|
||||
feature_data: FaceFeatureCreate,
|
||||
service: FaceFeatureService = Depends(get_face_feature_service)
|
||||
):
|
||||
"""
|
||||
创建人脸特征记录
|
||||
|
||||
- **person_id**: 人员ID (必须，大于0)
|
||||
- **feature_type**: 特征类型 (可选，大于等于0)
|
||||
- **pic_id**: 图片ID (可选)
|
||||
- **status**: 计算状态 (默认: NOT_STARTED)
|
||||
- **feature_data**: 特征数据 (可选，二进制)
|
||||
"""
|
||||
try:
|
||||
return service.create_feature(feature_data)
|
||||
except ValueError as e:
|
||||
if "already exists" in str(e):
|
||||
# 解析错误信息中的person_id和feature_type
|
||||
raise DuplicateFeatureError(
|
||||
person_id=feature_data.person_id,
|
||||
feature_type=feature_data.feature_type or 0
|
||||
)
|
||||
raise FaceFeatureProcessingError(detail=str(e))
|
||||
|
||||
|
||||
@router.get(
|
||||
"/{feature_id}",
|
||||
response_model=FaceFeatureResponse,
|
||||
summary="获取人脸特征记录",
|
||||
description="根据ID获取人脸特征记录"
|
||||
)
|
||||
async def get_face_feature(
|
||||
feature: FaceFeatureResponse = Depends(get_face_feature_by_id)
|
||||
):
|
||||
"""
|
||||
根据ID获取人脸特征记录
|
||||
|
||||
- **feature_id**: 特征记录ID (路径参数)
|
||||
"""
|
||||
return feature
|
||||
|
||||
|
||||
@router.get(
|
||||
"/",
|
||||
response_model=FaceFeatureListResponse,
|
||||
summary="查询人脸特征记录",
|
||||
description="查询人脸特征记录列表，支持分页和过滤"
|
||||
)
|
||||
async def list_face_features(
|
||||
person_id: Optional[int] = Query(None, description="人员ID", gt=0),
|
||||
feature_type: Optional[int] = Query(None, description="特征类型", ge=0),
|
||||
status: Optional[FeatureStatus] = Query(None, description="计算状态"),
|
||||
start_date: Optional[datetime] = Query(None, description="开始时间"),
|
||||
end_date: Optional[datetime] = Query(None, description="结束时间"),
|
||||
has_feature_data: Optional[bool] = Query(None, description="是否有特征数据"),
|
||||
page: int = Query(1, description="页码", ge=1),
|
||||
page_size: int = Query(20, description="每页数量", ge=1, le=100),
|
||||
service: FaceFeatureService = Depends(get_face_feature_service)
|
||||
):
|
||||
"""
|
||||
查询人脸特征记录
|
||||
|
||||
- **person_id**: 按人员ID过滤 (可选)
|
||||
- **feature_type**: 按特征类型过滤 (可选)
|
||||
- **status**: 按计算状态过滤 (可选)
|
||||
- **start_date**: 开始时间过滤 (可选)
|
||||
- **end_date**: 结束时间过滤 (可选)
|
||||
- **has_feature_data**: 是否有特征数据过滤 (可选)
|
||||
- **page**: 页码 (默认: 1)
|
||||
- **page_size**: 每页数量 (默认: 20, 最大: 100)
|
||||
"""
|
||||
# 构建查询参数
|
||||
query = FaceFeatureQuery(
|
||||
person_id=person_id,
|
||||
feature_type=feature_type,
|
||||
status=status,
|
||||
start_date=start_date,
|
||||
end_date=end_date,
|
||||
has_feature_data=has_feature_data
|
||||
)
|
||||
|
||||
return service.query_features(
|
||||
query=query,
|
||||
page=page,
|
||||
page_size=page_size,
|
||||
order_by="created_time",
|
||||
desc_order=True
|
||||
)
|
||||
|
||||
|
||||
@router.put(
|
||||
"/{feature_id}",
|
||||
response_model=FaceFeatureResponse,
|
||||
summary="更新人脸特征记录",
|
||||
description="更新指定ID的人脸特征记录"
|
||||
)
|
||||
async def update_face_feature(
|
||||
feature_id: int,
|
||||
update_data: FaceFeatureUpdate,
|
||||
service: FaceFeatureService = Depends(get_face_feature_service)
|
||||
):
|
||||
"""
|
||||
更新人脸特征记录
|
||||
|
||||
- **feature_id**: 特征记录ID (路径参数)
|
||||
- **update_data**: 更新数据 (请求体)
|
||||
"""
|
||||
try:
|
||||
result = service.update_feature(feature_id, update_data)
|
||||
if not result:
|
||||
raise FeatureNotFoundError(feature_id)
|
||||
return result
|
||||
except ValueError as e:
|
||||
raise FaceFeatureProcessingError(detail=str(e), feature_id=feature_id)
|
||||
|
||||
|
||||
@router.delete(
|
||||
"/{feature_id}",
|
||||
status_code=status.HTTP_204_NO_CONTENT,
|
||||
summary="删除人脸特征记录",
|
||||
description="删除指定ID的人脸特征记录"
|
||||
)
|
||||
async def delete_face_feature(
|
||||
feature_id: int,
|
||||
service: FaceFeatureService = Depends(get_face_feature_service)
|
||||
):
|
||||
"""
|
||||
删除人脸特征记录
|
||||
|
||||
- **feature_id**: 特征记录ID (路径参数)
|
||||
"""
|
||||
success = service.delete_feature(feature_id)
|
||||
if not success:
|
||||
raise FeatureNotFoundError(feature_id)
|
||||
|
||||
return JSONResponse(
|
||||
status_code=status.HTTP_204_NO_CONTENT,
|
||||
content=None
|
||||
)
|
||||
|
||||
|
||||
@router.post(
|
||||
"/{feature_id}/start-processing",
|
||||
response_model=FaceFeatureResponse,
|
||||
summary="开始处理人脸特征",
|
||||
description="开始计算指定ID的人脸特征值"
|
||||
)
|
||||
async def start_face_feature_processing(
|
||||
feature_id: int,
|
||||
background_tasks: BackgroundTasks,
|
||||
service: FaceFeatureService = Depends(get_face_feature_service)
|
||||
):
|
||||
"""
|
||||
开始处理人脸特征计算
|
||||
|
||||
- **feature_id**: 特征记录ID (路径参数)
|
||||
|
||||
注意：这是一个异步处理接口，会立即返回开始状态，
|
||||
实际特征计算可能在后台进行。
|
||||
"""
|
||||
try:
|
||||
# 先获取特征记录
|
||||
feature = service.get_feature(feature_id)
|
||||
if not feature:
|
||||
raise FeatureNotFoundError(feature_id)
|
||||
|
||||
# 检查是否可以开始处理
|
||||
if feature.status != FeatureStatus.NOT_STARTED:
|
||||
raise FaceFeatureProcessingError(
|
||||
detail=f"特征记录状态为 {feature.status_name}，无法开始处理",
|
||||
feature_id=feature_id
|
||||
)
|
||||
|
||||
# 开始处理
|
||||
success = service.start_processing(feature_id)
|
||||
if not success:
|
||||
raise FaceFeatureProcessingError(
|
||||
detail="开始处理失败",
|
||||
feature_id=feature_id
|
||||
)
|
||||
|
||||
# 异步任务：模拟特征计算过程
|
||||
# 在实际应用中，这里应该调用实际的特征计算服务
|
||||
background_tasks.add_task(
|
||||
simulate_feature_processing,
|
||||
feature_id=feature_id,
|
||||
service=service
|
||||
)
|
||||
|
||||
# 返回更新后的特征记录
|
||||
return service.get_feature(feature_id)
|
||||
|
||||
except ValueError as e:
|
||||
raise FaceFeatureProcessingError(detail=str(e), feature_id=feature_id)
|
||||
|
||||
|
||||
@router.post(
|
||||
"/{feature_id}/finish-processing",
|
||||
response_model=FaceFeatureResponse,
|
||||
summary="完成人脸特征处理",
|
||||
description="完成指定ID的人脸特征值计算"
|
||||
)
|
||||
async def finish_face_feature_processing(
|
||||
feature_id: int,
|
||||
success: bool = Query(True, description="是否成功完成"),
|
||||
service: FaceFeatureService = Depends(get_face_feature_service)
|
||||
):
|
||||
"""
|
||||
完成人脸特征计算
|
||||
|
||||
- **feature_id**: 特征记录ID (路径参数)
|
||||
- **success**: 是否成功完成 (查询参数，默认: true)
|
||||
"""
|
||||
try:
|
||||
# 检查特征记录
|
||||
feature = service.get_feature(feature_id)
|
||||
if not feature:
|
||||
raise FeatureNotFoundError(feature_id)
|
||||
|
||||
# 检查是否可以完成处理
|
||||
if feature.status != FeatureStatus.PROCESSING:
|
||||
raise FaceFeatureProcessingError(
|
||||
detail=f"特征记录状态为 {feature.status_name}，无法完成处理",
|
||||
feature_id=feature_id
|
||||
)
|
||||
|
||||
# 完成处理
|
||||
finish_success = service.finish_processing(feature_id, success)
|
||||
if not finish_success:
|
||||
raise FaceFeatureProcessingError(
|
||||
detail="完成处理失败",
|
||||
feature_id=feature_id
|
||||
)
|
||||
|
||||
return service.get_feature(feature_id)
|
||||
|
||||
except ValueError as e:
|
||||
raise FaceFeatureProcessingError(detail=str(e), feature_id=feature_id)
|
||||
|
||||
|
||||
@router.post(
|
||||
"/batch",
|
||||
response_model=List[FaceFeatureResponse],
|
||||
status_code=status.HTTP_201_CREATED,
|
||||
summary="批量创建人脸特征记录",
|
||||
description="批量创建多个人脸特征记录"
|
||||
)
|
||||
async def batch_create_face_features(
|
||||
batch_data: BatchFaceFeatureCreate,
|
||||
service: FaceFeatureService = Depends(get_face_feature_service)
|
||||
):
|
||||
"""
|
||||
批量创建人脸特征记录
|
||||
|
||||
- **items**: 特征记录列表 (必须，1-1000条)
|
||||
"""
|
||||
try:
|
||||
return service.create_features_batch(batch_data)
|
||||
except ValueError as e:
|
||||
raise FaceFeatureProcessingError(detail=str(e))
|
||||
|
||||
|
||||
@router.get(
|
||||
"/person/{person_id}",
|
||||
response_model=List[FaceFeatureResponse],
|
||||
summary="获取人员的人脸特征记录",
|
||||
description="根据人员ID获取所有相关的人脸特征记录"
|
||||
)
|
||||
async def get_face_features_by_person(
|
||||
person_id: int,
|
||||
limit: int = Query(100, description="返回数量限制", ge=1, le=1000),
|
||||
service: FaceFeatureService = Depends(get_face_feature_service)
|
||||
):
|
||||
"""
|
||||
获取人员的人脸特征记录
|
||||
|
||||
- **person_id**: 人员ID (路径参数)
|
||||
- **limit**: 返回数量限制 (查询参数，默认: 100, 最大: 1000)
|
||||
"""
|
||||
return service.list_features_by_person(person_id, limit)
|
||||
|
||||
|
||||
@router.get(
|
||||
"/stats/summary",
|
||||
response_model=FaceFeatureStatsResponse,
|
||||
summary="获取特征记录统计信息",
|
||||
description="获取人脸特征记录的统计摘要"
|
||||
)
|
||||
async def get_face_features_stats(
|
||||
service: FaceFeatureService = Depends(get_face_feature_service)
|
||||
):
|
||||
"""
|
||||
获取特征记录统计信息
|
||||
"""
|
||||
return service.get_statistics()
|
||||
|
||||
|
||||
@router.get(
|
||||
"/person/{person_id}/stats",
|
||||
summary="获取人员特征统计信息",
|
||||
description="获取指定人员的特征记录统计信息"
|
||||
)
|
||||
async def get_person_face_features_stats(
|
||||
person_id: int,
|
||||
service: FaceFeatureService = Depends(get_face_feature_service)
|
||||
):
|
||||
"""
|
||||
获取人员特征统计信息
|
||||
|
||||
- **person_id**: 人员ID (路径参数)
|
||||
"""
|
||||
try:
|
||||
stats = service.get_person_statistics(person_id)
|
||||
return {
|
||||
"person_id": person_id,
|
||||
"total_features": stats["total_features"],
|
||||
"status_summary": stats["status_summary"],
|
||||
"feature_types": stats["feature_types"],
|
||||
"avg_processing_time": stats["avg_processing_time"],
|
||||
"successful_count": stats["successful_count"]
|
||||
}
|
||||
except Exception as e:
|
||||
raise FaceFeatureProcessingError(detail=str(e))
|
||||
|
||||
|
||||
async def simulate_feature_processing(
|
||||
feature_id: int,
|
||||
service: FaceFeatureService
|
||||
):
|
||||
"""
|
||||
模拟人脸特征计算过程
|
||||
|
||||
在实际应用中，这里应该调用实际的特征计算算法
|
||||
例如：使用InsightFace、OpenCV等库进行人脸特征提取
|
||||
|
||||
Args:
|
||||
feature_id: 特征记录ID
|
||||
service: 人脸特征服务
|
||||
"""
|
||||
import asyncio
|
||||
import random
|
||||
|
||||
try:
|
||||
# 模拟计算延迟 (3-10秒)
|
||||
delay = random.uniform(3, 10)
|
||||
await asyncio.sleep(delay)
|
||||
|
||||
# 模拟成功或失败 (90%成功率)
|
||||
success = random.random() < 0.9
|
||||
|
||||
# 完成处理
|
||||
service.finish_processing(feature_id, success)
|
||||
|
||||
# 如果成功，添加模拟的特征数据
|
||||
if success:
|
||||
# 生成模拟的512维特征向量 (float32)
|
||||
import numpy as np
|
||||
feature_data = np.random.randn(512).astype(np.float32).tobytes()
|
||||
service.update_feature_data(feature_id, feature_data)
|
||||
|
||||
except Exception as e:
|
||||
# 如果发生异常，标记为失败
|
||||
service.finish_processing(feature_id, False)
|
||||
# 记录日志
|
||||
import logging
|
||||
logger = logging.getLogger(__name__)
|
||||
logger.error(f"特征计算失败 (ID: {feature_id}): {e}")
|
||||
Reference in New Issue
Block a user