feat: 尝试优化人脸识别速度

apps/hrm/apps.py

@@ -7,8 +7,8 @@ class HrmConfig(AppConfig):
     verbose_name = '人力资源管理'
 
     def ready(self):
-        if cache.get('update_global_face_pd_task', True):
-            from apps.hrm.tasks import update_global_face_pd
-            update_global_face_pd.delay()
-            cache.set('update_global_face_pd_task', False, timeout=30)
+        # if cache.get('update_global_face_pd_task', True):
+        #     from apps.hrm.tasks import update_global_face_pd
+        #     update_global_face_pd.delay()
+        #     cache.set('update_global_face_pd_task', False, timeout=30)
         return super().ready()

apps/hrm/serializers.py

@@ -77,8 +77,8 @@ class EmployeeCreateUpdateSerializer(CustomModelSerializer):
                 instance.save()
             else:
                 raise ParseError(msg)
-            from apps.hrm.tasks import update_global_face_pd
-            update_global_face_pd.delay()
+            from apps.hrm.tasks import update_global_face
+            update_global_face.delay()
         if instance.user and instance != old_name:
             instance.user.name = instance.name
             instance.user.save()

apps/hrm/services.py

@@ -405,18 +405,18 @@ class HrmService:
 
     @classmethod
     def face_find_from_base64(cls, base64_data):
-        from deepface import DeepFace
+        # from deepface import DeepFace
         img_name = str(uuid.uuid4())
         img_path = settings.BASE_DIR +'/temp/face_' + img_name +'.jpg'
         with open(img_path, 'wb') as f:
             f.write(base64_data)
         # db_path = os.path.join(settings.BASE_DIR, 'media/face')
-        face_df = cache.get('global_face_df', None)
-        if face_df is None:
-            from apps.hrm.tasks import update_global_face_pd
-            face_df = update_global_face_pd()
-            face_df = cache.get('global_face_df')
-        dfs = face_find(img_path=img_path, global_df=face_df)
+        global_face = cache.get('global_face', None)
+        if global_face is None:
+            from apps.hrm.tasks import update_global_face
+            global_face = update_global_face()
+            global_face = cache.get('global_face')
+        dfs = face_find(img_path=img_path, global_face=global_face)
         # dfs = DeepFace.find(img_path=img_path, db_path=db_path)
         df = dfs[0]
         if not df.empty:

apps/hrm/tasks.py

@@ -127,9 +127,7 @@ def delete_face_pkl(epId):
 
 
 @shared_task(base=CustomTask)
-def update_global_face_pd():
-    import pandas as pd
+def update_global_face():
     facedata = Employee.objects.filter(face_data__isnull=False, 
                     user__is_active=True).values_list('id', 'face_data')
-    face_df = pd.DataFrame(list(facedata), columns=["identity", "VGG-Face_representation"])
-    cache.set('global_face_df', face_df, timeout=None)
+    cache.set('global_face', list(facedata), timeout=None)

apps/utils/face.py

@@ -5,7 +5,7 @@ import time
 
 def face_find(
     img_path,
-    global_df,
+    global_face: list,
     model_name="VGG-Face",
     distance_metric="cosine",
     enforce_detection=True,
@@ -17,7 +17,7 @@ def face_find(
     tic = time.time()
     target_size = functions.find_target_size(model_name=model_name)
     # now, we got representations for facial database
-    df = global_df
+    df = pd.DataFrame(global_face, columns=["identity", f"{model_name}_representation"])
 
     # img path might have more than once face
     target_objs = functions.extract_faces(