修改代码与文档

FaceRegWeb5.2/FaceRegWeb/flushredis.py

@@ -2,7 +2,7 @@ import redis
 import os 
 
 # Redis config
-redis_host = str(os.getenv("REDIS_HOST", 'localhost')) 
+redis_host = str(os.getenv("REDIS_HOST", '192.168.0.14'))
 redis_port = int(os.getenv("REDIS_PORT", 2012))
 redis_password = str(os.getenv("REDIS_PASSWORD", 'Xjsfzb@Redis123!')) 
 num_workers = int(os.getenv("NUM_WORKERS", 10))

FaceRegWeb5.2/FaceRegWeb/process.py

@@ -20,17 +20,16 @@ from models import FaceRecoger, FaceBoxesV2, Landmark5er, FaceAlign, QualityOfCl
 so = onnxruntime.SessionOptions()
 so.log_severity_level = 3  # 0=VERBOSE, 1=INFO, 2=WARNING, 3=ERROR, 4=FATAL
 
-
+# # 获取workers
-# 获取workers 
+# if "NUM_WORKERS" not in os.environ:
-if "NUM_WORKERS" not in os.environ:
+#     raise RuntimeError("Environment variable NUM_WORKERS is required but not set.")
-    raise RuntimeError("Environment variable NUM_WORKERS is required but not set.")
 NUM_WORKERS = int(os.getenv("NUM_WORKERS", 10))
 
 # max readers 
 max_readers = int(os.getenv("MAX_READERS", 60))
 
 # 连接到 Redis
-redis_host = str(os.getenv("REDIS_HOST", 'localhost')) 
+redis_host = str(os.getenv("REDIS_HOST", '192.168.0.14'))
 redis_port = int(os.getenv("REDIS_PORT", 2012))
 redis_password = str(os.getenv("REDIS_PASSWORD", 'Xjsfzb@Redis123!'))
 # connected
@@ -73,26 +72,31 @@ ErrorMsg = {
     "30019": "identity already exists; for database protection, operation rejected at this time"
 }
 
+
 class FileError(Exception):
     def __init__(self, arg: str):
         self.code = arg
         self.args = [f"{str(self.__class__.__name__)} {str(arg)}: {ErrorMsg[arg]}"]
 
+
 class NotImpltError(Exception):
     def __init__(self, arg: str):
         self.code = arg
         self.args = [f"{str(self.__class__.__name__)} {str(arg)}: {ErrorMsg[arg]}"]
 
+
 class FaceError(Exception):
     def __init__(self, arg: str):
         self.code = arg
         self.args = [f"{str(self.__class__.__name__)} {str(arg)}: {ErrorMsg[arg]}"]
 
+
 class UpdatedbError(Exception):
     def __init__(self, arg: str):
         self.code = arg
         self.args = [f"{str(self.__class__.__name__)} {str(arg)}: {ErrorMsg[arg]}"]
 
+
 # setting Logger
 current_time = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
 log_dir = f"{os.path.dirname(os.path.abspath(__file__))}/log"
@@ -102,6 +106,7 @@ logging.basicConfig(filename=f'{log_dir}/{current_time}.log', level=logging.INFO
 logger = logging.getLogger(__name__)  # @@@@
 print(log_dir)
 
+
 def list_images(path: str):
     """
     List images in a given path
@@ -150,6 +155,7 @@ def find_image_hash(file_path: str) -> str:
     hasher.update(properties.encode("utf-8"))
     return hasher.hexdigest()
 
+
 # 支持base64 local-path url 等多种检索图片的方式，返回 numpy
 def load_img(img_path: str):
     image = None
@@ -206,16 +212,21 @@ class FaceHelper:
             config = yaml.safe_load(f)
 
         self.sim_threshold = config['faceReg']['sim_threshold']  # 0.7
-        self.rotclsifer = onnxruntime.InferenceSession( config['ck_paths']['rotifer'], so) # "./checkpoints/model_gray_mobilenetv2_rotcls.onnx"
+        self.rotclsifer = onnxruntime.InferenceSession(config['ck_paths']['rotifer'],
+                                                       so)  # "./checkpoints/model_gray_mobilenetv2_rotcls.onnx"
         self.db_path = os.path.join(db_dir, "seetaface6.pkl").lower()
 
-        self.fd = FaceBoxesV2(config['ck_paths']['FcBx'], config['ck_paths']['num_threads'] ) # r"./checkpoints/faceboxesv2-640x640.onnx"  4
+        self.fd = FaceBoxesV2(config['ck_paths']['FcBx'],
-        self.ld5er = Landmark5er( onnx_path1 = config['ck_paths']['landmk1'],    # "./checkpoints/face_landmarker_pts5_net1.onnx", 
+                              config['ck_paths']['num_threads'])  # r"./checkpoints/faceboxesv2-640x640.onnx"  4
-                                  onnx_path2 = config['ck_paths']['landmk2'],    # "./checkpoints/face_landmarker_pts5_net2.onnx", 
+        self.ld5er = Landmark5er(onnx_path1=config['ck_paths']['landmk1'],
+                                 # "./checkpoints/face_landmarker_pts5_net1.onnx",
+                                 onnx_path2=config['ck_paths']['landmk2'],
+                                 # "./checkpoints/face_landmarker_pts5_net2.onnx",
                                  num_threads=config['ck_paths']['num_threads']  # 4
                                  )
         self.fa = FaceAlign()
-        self.fr = FaceRecoger(onnx_path = config['ck_paths']['FcReg'], num_threads= config['ck_paths']['num_threads'] )  # "./checkpoints/face_recognizer.onnx"  4 
+        self.fr = FaceRecoger(onnx_path=config['ck_paths']['FcReg'],
+                              num_threads=config['ck_paths']['num_threads'])  # "./checkpoints/face_recognizer.onnx"  4
         self.qc = QualityChecker(config['brightness']['v0'], config['brightness']['v1'],
                                  config['brightness']['v2'], config['brightness']['v3'],
                                  hw=(config['resolution']['height'], config['resolution']['width'])
@@ -224,7 +235,8 @@ class FaceHelper:
                                    var_onnx_path=config['pose']['var_onnx_path'],  # './checkpoints/fsanet-var.onnx',
                                    conv_onnx_path=config['pose']['conv_onnx_path'],  # './checkpoints/fsanet-conv.onnx'
                                    )
-        self.qclarity = QualityOfClarity(low_thresh=config['clarity']['low_thrd'], high_thresh=config['clarity']['high_thrd'])
+        self.qclarity = QualityOfClarity(low_thresh=config['clarity']['low_thrd'],
+                                         high_thresh=config['clarity']['high_thrd'])
 
         # refresh the db  
         try:
@@ -316,10 +328,8 @@ class FaceHelper:
     # 只是提取人脸特征，不要对别的有任何影响
     def featureDetect(self, img_path: str):
         rw_lock.acquire_read()
-
         try:
             image = load_img(img_path)  # get bgr numpy image
-
             unknown_embeddings = []
             image = self.rotadjust(image)  # 调整角度
             detect_result = self.fd.detect(image)
@@ -341,7 +351,7 @@ class FaceHelper:
             ret_data = []
             for _, (facebox, feature) in enumerate(zip(detect_result, unknown_embeddings)):
                 code = self.check_face("None", image, facebox, prefix='featuredetect')
-                ret_data.append({'code':code,  'msg': ErrorMsg[code],  'data': [f"{feature.tobytes()},{str(feature.dtype)}", facebox]})
+                ret_data.append({'code': code, 'msg': ErrorMsg[code], 'data': [{str(num) for num in feature}, facebox]})
 
             if len(ret_data) != 1:
                 ret_data = {'code': "30008", 'msg': ErrorMsg["30008"], 'data': ret_data}
@@ -371,14 +381,16 @@ class FaceHelper:
                         self.db_embeddings, self.db_identities = None, None
                     else:
                         self.db_embeddings = np.array([rep["embedding"] for rep in representations], dtype=np.float32)
-                        self.db_identities = [os.path.splitext(os.path.basename(rep["identity"]))[0] for rep in representations]
+                        self.db_identities = [os.path.splitext(os.path.basename(rep["identity"]))[0] for rep in
+                                              representations]
                     redis_client.set(f"worker_{self.pid}", 1)  # 同步完毕
 
                 img = load_img(img_path)
                 img = self.rotadjust(img)  # 调整角度
                 if opt in ["add", "replace"]:
                     if opt == "add" and self.db_identities is not None and identity in self.db_identities:
-                        raise UpdatedbError("30019") # push: identity has exist. to pretect the db, reject opt of this time 
+                        raise UpdatedbError(
+                            "30019")  # push: identity has exist. to pretect the db, reject opt of this time
                     else:
 
                         detect_result = self.fd.detect(img)
@@ -391,12 +403,15 @@ class FaceHelper:
                             areas = [box.area() for box in detect_result]
                             max_idx = areas.index(max(areas))
                             facebox = detect_result[max_idx]
-                            facebox = (facebox.x1, facebox.y1, facebox.x2, facebox.y2) # top_left point,  bottom_right point
+                            facebox = (
-                            FaceError_number = self.check_face(img_path=img_path[:200], img=img, facebox=facebox, prefix='update')
+                                facebox.x1, facebox.y1, facebox.x2, facebox.y2)  # top_left point,  bottom_right point
+                            FaceError_number = self.check_face(img_path=img_path[:200], img=img, facebox=facebox,
+                                                               prefix='update')
                             if FaceError_number != "30002":
                                 raise FaceError(FaceError_number)
 
-                        cv2.imwrite(os.path.join(self.db_dir, identity+'.jpg'),img,[cv2.IMWRITE_JPEG_QUALITY, 100])  # 如果file已经存在，则会替换它
+                        cv2.imwrite(os.path.join(self.db_dir, identity + '.jpg'), img,
+                                    [cv2.IMWRITE_JPEG_QUALITY, 100])  # 如果file已经存在，则会替换它
 
                 elif opt == "delete":
                     try:
@@ -405,7 +420,6 @@ class FaceHelper:
                         pass
                 else:
                     raise NotImpltError("30007")  # push: this updateDB type is not support
-                
                 print("end the updateDB")
                 logger.info(f"end the updateDB")
 
@@ -446,7 +460,9 @@ class FaceHelper:
             storage_images[idx] = base_path + '.jpg'
 
         must_save_pickle = False
-        new_images = []; old_images = []; replaced_images = []
+        new_images = [];
+        old_images = [];
+        replaced_images = []
 
         new_images = list(set(storage_images) - set(pickle_images))
         old_images = list(set(pickle_images) - set(storage_images))
@@ -492,7 +508,8 @@ class FaceHelper:
                     facebox = (facebox.x1, facebox.y1, facebox.x2, facebox.y2)  # top_left point,  bottom_right point
 
                     if check:
-                        FaceError_number = self.check_face(img_path=new_image[:200], img=image, facebox=facebox, prefix='refreshdb')
+                        FaceError_number = self.check_face(img_path=new_image[:200], img=image, facebox=facebox,
+                                                           prefix='refreshdb')
                         if FaceError_number != "30002":
                             continue
 
@@ -631,3 +648,70 @@ class FaceHelper:
             return "30017"  # poor clarity of face in the image
 
         return "30002"
+
+    def imageComparison(self, firstImage, secondImage):
+        rw_lock.acquire_read()
+        try:
+            # Load and adjust images
+            imageFirst = self.rotadjust(load_img(firstImage))
+            imageSecond = self.rotadjust(load_img(secondImage))
+            print("1")
+            # Detect faces
+            detect_result_first = self.fd.detect(imageFirst)
+            detect_result_second = self.fd.detect(imageSecond)
+            detect_result_first = [(box.x1, box.y1, box.x2, box.y2) for box in detect_result_first]
+            detect_result_second = [(box.x1, box.y1, box.x2, box.y2) for box in detect_result_second]
+            if len(detect_result_first) < 1:
+                raise FaceError("30018")
+            if len(detect_result_second) < 1:
+                raise FaceError("30018")
+            if len(detect_result_first) > 1:
+                raise FaceError("30008")
+            if len(detect_result_second) > 1:
+                raise FaceError("30008")
+
+            # Validate detected faces
+            self._validate_face_detection(detect_result_first, "firstImage")
+            self._validate_face_detection(detect_result_second, "secondImage")
+            # 提取人脸特征
+            features_first = self._extract_single_feature(imageFirst, detect_result_first)
+            features_second = self._extract_single_feature(imageSecond, detect_result_second)
+            # Calculate the Euclidean distance between features
+            distance = calculate_euclidean_distance(features_first, features_second)
+            # Compare distance with threshold
+            return distance >= 0.75
+
+        except Exception as e:
+            logger.error(f"Error occurred: {e}")
+            raise e
+        finally:
+            rw_lock.release_read()
+
+    def _validate_face_detection(self, detect_result, image_name):
+        if not detect_result:
+            logger.warning(f"No face detected in the image: {image_name}")
+            raise FaceError("30018")  # no face in the image
+
+    def extract_features(self, image, detect_result):
+        return [
+            self._extract_single_feature(image, facebox)
+            for facebox in detect_result
+        ]
+
+    def _extract_single_feature(self, image, detect_result):
+        for facebox in detect_result:
+            landmarks5 = self.ld5er.inference(image, facebox)
+            landmarks5 = np.array([[ld5[0], ld5[1]] for ld5 in landmarks5])
+            cropped_face = self.fa.align(image, landmarks5=landmarks5)
+            return self.fr.inference(cropped_face)
+
+
+def calculate_euclidean_distance(features1, features2):
+    if len(features1) != len(features2):
+        raise ValueError("Feature arrays must have the same length")
+    # Calculate the Euclidean distance
+    total = 0
+    for f1, f2 in zip(features1, features2):
+        total += f1 * f2
+
+    return total

FaceRegWeb5.2/FaceRegWeb/setup.bat

@@ -0,0 +1,36 @@
+@echo off
+setlocal enabledelayedexpansion
+
+rem 从 redis.yaml 文件中读取 Redis 相关配置信息
+set "REDIS_CONFIG="
+for /f "delims=" %%i in (redis.yaml) do (
+    set "REDIS_CONFIG=!REDIS_CONFIG! %%i"
+)
+
+rem 工作进程数 workers
+set "NUM_WORKERS=%3"
+
+rem 提取 Redis 配置信息
+for %%i in (!REDIS_CONFIG!) do (
+    for /f "tokens=1,* delims==" %%j in (%%i) do (
+        if "%%j"=="REDIS_HOST" set "REDIS_HOST=%%k"
+        if "%%j"=="REDIS_PORT" set "REDIS_PORT=%%k"
+        if "%%j"=="REDIS_PASSWORD" set "REDIS_PASSWORD=%%k"
+    )
+)
+
+echo num_workers: %NUM_WORKERS%
+echo redis_host: %REDIS_HOST%; redis_port: %REDIS_PORT%
+
+rem 运行 Python 脚本
+set REDIS_HOST=%REDIS_HOST%
+set REDIS_PORT=%REDIS_PORT%
+set REDIS_PASSWORD=%REDIS_PASSWORD%
+set NUM_WORKERS=%NUM_WORKERS%
+
+rem 确保 Python 脚本能够正确读取环境变量
+python flushredis.py
+
+rem 启动 uvicorn
+set MAX_READERS=%4%
+uvicorn webmain:app --host %1 --port %2 --workers %NUM_WORKERS%

FaceRegWeb5.2/FaceRegWeb/webmain.py

@@ -1,83 +1,154 @@
-from fastapi import FastAPI
+from fastapi import FastAPI, HTTPException
 from pydantic import BaseModel
 from process import FaceHelper, FileError, ErrorMsg
 import threading
-import os 
 import time
+
+# 创建 FastAPI 实例
 app = FastAPI()
+
+# 创建线程锁，确保在多线程环境中对共享资源的访问是线程安全的
 lock = threading.Lock()
 
+# 全局变量 facehelper，稍后将用于管理人脸识别相关操作
+facehelper = None
 
-facehelper = FaceHelper(
-    db_dir="./dbface",
-)
 
-class face(BaseModel):
+def get_facehelper():
+    """
+    懒加载模式初始化 facehelper 对象。
+    只有在第一次调用时才会创建 FaceHelper 实例。
+    使用线程锁以确保 facehelper 实例在多线程环境下的安全初始化。
+    """
+    global facehelper
+    if facehelper is None:
+        with lock:
+            if facehelper is None:
+                facehelper = FaceHelper(db_dir="./dbface")
+    return facehelper
+
+
+# 定义请求模型，用于接收前端传递的图像数据
+class FaceRequest(BaseModel):
     img: str
 
-class dbface(BaseModel):
+
+# 定义请求模型，用于接收前端传递的数据库操作数据
+class DBFaceRequest(BaseModel):
     img: str
     optMode: str
     uniqueKey: str
 
+
+# 接两图片对比的参数
+class ImageComparison(BaseModel):
+    firstImage: str
+    secondImage: str
+
+
 @app.post("/refreshdb")
-@app.post("/refreshdb/")
 def refresh():
-    global facehelper
+    """
+    刷新人脸数据库的接口。
+    该接口将调用 facehelper 的 updateDB 方法，刷新数据库内容。
+    """
+    facehelper = get_facehelper()
     try:
+        # 加锁确保数据库更新操作的线程安全性
         with lock:
             facehelper.updateDB(None, None, None, Onlyrefresh=True)
     except FileError as e:
-        # return {"status":e.code, "detail":f"{e}"}
+        # 处理文件错误，返回相应的错误代码和信息
-        return {'code': e.code, 'msg': f"{e}", 'data': 'None'}
+        return {'code': e.code, 'msg': str(e), 'data': None}
     else:
-        return {'code': "30002", 'msg': ErrorMsg['30002'], 'data': 'None'}
+        # 成功刷新数据库后返回相应的状态码和消息
+        return {'code': "30002", 'msg': ErrorMsg['30002'], 'data': None}
+
 
 @app.post("/facerecognition")
-@app.post("/facerecognition/")
+def faceRecognition(input: FaceRequest):
-def faceRecognition(input:face):
+    """
-    start = time.time()
+    进行人脸识别的接口。
-    global facehelper
+    接收前端传递的图像数据，并使用 facehelper 进行人脸识别。
+    返回识别结果和运行时间。
+    """
+    facehelper = get_facehelper()
+    start = time.time()  # 记录开始时间
     try:
+        # 调用 facehelper 的 faceRecognition 方法进行人脸识别
         ret_data = facehelper.faceRecognition(input.img)
-        print("finished recognition...")
-        end = time.time()
-        print("runtime: ", end-start)
     except Exception as e:
-        return {'code': e.code, 'msg': f"{e}", 'data': 'None'}
+        # 处理异常，返回相应的错误代码和信息
-        # return {"status":f"{e.code}", "detail":f"{e}"} 
+        raise HTTPException(status_code=400, detail={'code': e.code, 'msg': str(e), 'data': None})
-    else: 
+    finally:
+        end = time.time()  # 记录结束时间
+        # 打印运行时间
+        print(f"Recognition finished. Runtime: {end - start:.2f} seconds")
+
+    # 返回识别结果
     return ret_data
-        return {"status":1, "name":identity, "resImg":res_img_base64}
+
 
 @app.post("/featuredetect")
-@app.post("/featuredetect/")
+def featureDetect(input: FaceRequest):
-def featureDetect(input:face):
+    """
-    start = time.time()
+    特征检测接口。
-    global facehelper
+    接收前端传递的图像数据，并使用 facehelper 进行特征检测。
+    返回检测结果和运行时间。
+    """
+    facehelper = get_facehelper()
+    start = time.time()  # 记录开始时间
     try:
+        # 调用 facehelper 的 featureDetect 方法进行特征检测
         ret_data = facehelper.featureDetect(input.img)
-        print("finished featuredetect...")
-        end = time.time()
-        print("runtime: ", end-start)
     except Exception as e:
-        return {'code': e.code, 'msg': f"{e}", 'data': 'None'}
+        # 处理异常，返回相应的错误代码和信息
-        # return {"status":f"{e.code}", "detail":f"{e}"} 
+        raise HTTPException(status_code=400, detail={'code': e.code, 'msg': str(e), 'data': None})
-    else: 
+    finally:
+        end = time.time()  # 记录结束时间
+        # 打印运行时间
+        print(f"Feature detection finished. Runtime: {end - start:.2f} seconds")
+
+    # 返回检测结果
     return ret_data
 
-@app.post("/updatedb")
-@app.post("/updatedb/")
-def updateDB(input:dbface):
-    global facehelper
-    # input.uniqueKey = os.path.splitext(os.path.basename(input.uniqueKey))[0]  
 
+@app.post("/updatedb")
+def updateDB(input: DBFaceRequest):
+    """
+    更新人脸数据库的接口。
+    接收前端传递的数据库操作数据，并使用 facehelper 更新数据库。
+    """
+    facehelper = get_facehelper()
     try:
+        # 加锁确保数据库更新操作的线程安全性
         with lock:
             facehelper.updateDB(input.img, input.optMode, input.uniqueKey)
     except Exception as e:
-        return {'code': e.code, 'msg': f"{e}", 'data': 'None'}
+        # 处理异常，返回相应的错误代码和信息
-        # return {"status":f"{e.code}", "detail":f"{e}"}
+        raise HTTPException(status_code=400, detail={'code': e.code, 'msg': str(e), 'data': None})
     else:
-        return {'code': "30002", 'msg': ErrorMsg['30002'], 'data': 'None'}
+        # 成功更新数据库后返回相应的状态码和消息
+        return {'code': "30002", 'msg': ErrorMsg['30002'], 'data': None}
+
+
+@app.post("/imageComparison")
+def imageComparison(input: ImageComparison):
+    """
+    更新人脸数据库的接口。
+    接收前端传递的数据库操作数据，并使用 facehelper 更新数据库。
+    """
+    facehelper = get_facehelper()
+
+    try:
+        # 加锁确保数据库更新操作的线程安全性
+        with lock:
+            state = facehelper.imageComparison(input.firstImage, input.secondImage)
+    except Exception as e:
+        # 处理异常，返回相应的错误代码和信息
+        raise HTTPException(status_code=400, detail={'code': e.code, 'msg': str(e), 'data': None})
+    else:
+        # 成功更新数据库后返回相应的状态码和消息
+        return {'code': "30002", 'msg': ErrorMsg['30002'], 'data': bool(state)}
+