Commit:

regula/facesdk/webclient/gen/api/match_api.py

@@ -347,7 +347,7 @@ def match(
     ) -> MatchResponse:
         """compare faces (1:1)
 
-        To perform a comparison of faces in the same image or in two different images, use POST `/api/match`. It's possible to compare faces in the same image or in two different images, this is defined by the `images.type` parameter. <br><br> Note that no more than two images of the same `type` are allowed for comparison.<br><br> The face detection result is displayed in the `detections` field. Each face is identified by two parameters: `faceIndex` (the index number of the face) and `imageIndex` (the index number of the image on which the face is detected). So, if there are two images each of which has two faces in them, the parameters will be the following: - First face in the first image: `faceIndex: 0`, `imageIndex: 0` - Second face in the first image: `faceIndex: 1`, `imageIndex: 0` - First face of the second image: `faceIndex: 0`, `imageIndex: 1` - Second face in the second image: `faceIndex: 1`, `imageIndex: 1`
+        To perform a comparison of faces in the same image or in two different images, use POST `/api/match`. It's possible to compare faces in the same image or in two different images, this is defined by the `images.type` parameter. <br><br> Note that no more than two images of the same `type` are allowed for comparison.<br><br> It's also possible to perform matching by using the face captured during the liveness check as one of the comparison inputs. In this case, pass `livenessTransactionId` instead of one of the images.<br><br> The face detection result is displayed in the `detections` field. Each face is identified by two parameters: `faceIndex` (the index number of the face) and `imageIndex` (the index number of the image on which the face is detected). So, if there are two images each of which has two faces in them, the parameters will be the following: - First face in the first image: `faceIndex: 0`, `imageIndex: 0` - Second face in the first image: `faceIndex: 1`, `imageIndex: 0` - First face of the second image: `faceIndex: 0`, `imageIndex: 1` - Second face in the second image: `faceIndex: 1`, `imageIndex: 1`
 
         :param match_request: (required)
         :type match_request: MatchRequest
@@ -419,7 +419,7 @@ def match_with_http_info(
     ) -> ApiResponse[MatchResponse]:
         """compare faces (1:1)
 
-        To perform a comparison of faces in the same image or in two different images, use POST `/api/match`. It's possible to compare faces in the same image or in two different images, this is defined by the `images.type` parameter. <br><br> Note that no more than two images of the same `type` are allowed for comparison.<br><br> The face detection result is displayed in the `detections` field. Each face is identified by two parameters: `faceIndex` (the index number of the face) and `imageIndex` (the index number of the image on which the face is detected). So, if there are two images each of which has two faces in them, the parameters will be the following: - First face in the first image: `faceIndex: 0`, `imageIndex: 0` - Second face in the first image: `faceIndex: 1`, `imageIndex: 0` - First face of the second image: `faceIndex: 0`, `imageIndex: 1` - Second face in the second image: `faceIndex: 1`, `imageIndex: 1`
+        To perform a comparison of faces in the same image or in two different images, use POST `/api/match`. It's possible to compare faces in the same image or in two different images, this is defined by the `images.type` parameter. <br><br> Note that no more than two images of the same `type` are allowed for comparison.<br><br> It's also possible to perform matching by using the face captured during the liveness check as one of the comparison inputs. In this case, pass `livenessTransactionId` instead of one of the images.<br><br> The face detection result is displayed in the `detections` field. Each face is identified by two parameters: `faceIndex` (the index number of the face) and `imageIndex` (the index number of the image on which the face is detected). So, if there are two images each of which has two faces in them, the parameters will be the following: - First face in the first image: `faceIndex: 0`, `imageIndex: 0` - Second face in the first image: `faceIndex: 1`, `imageIndex: 0` - First face of the second image: `faceIndex: 0`, `imageIndex: 1` - Second face in the second image: `faceIndex: 1`, `imageIndex: 1`
 
         :param match_request: (required)
         :type match_request: MatchRequest
@@ -491,7 +491,7 @@ def match_without_preload_content(
     ) -> RESTResponseType:
         """compare faces (1:1)
 
-        To perform a comparison of faces in the same image or in two different images, use POST `/api/match`. It's possible to compare faces in the same image or in two different images, this is defined by the `images.type` parameter. <br><br> Note that no more than two images of the same `type` are allowed for comparison.<br><br> The face detection result is displayed in the `detections` field. Each face is identified by two parameters: `faceIndex` (the index number of the face) and `imageIndex` (the index number of the image on which the face is detected). So, if there are two images each of which has two faces in them, the parameters will be the following: - First face in the first image: `faceIndex: 0`, `imageIndex: 0` - Second face in the first image: `faceIndex: 1`, `imageIndex: 0` - First face of the second image: `faceIndex: 0`, `imageIndex: 1` - Second face in the second image: `faceIndex: 1`, `imageIndex: 1`
+        To perform a comparison of faces in the same image or in two different images, use POST `/api/match`. It's possible to compare faces in the same image or in two different images, this is defined by the `images.type` parameter. <br><br> Note that no more than two images of the same `type` are allowed for comparison.<br><br> It's also possible to perform matching by using the face captured during the liveness check as one of the comparison inputs. In this case, pass `livenessTransactionId` instead of one of the images.<br><br> The face detection result is displayed in the `detections` field. Each face is identified by two parameters: `faceIndex` (the index number of the face) and `imageIndex` (the index number of the image on which the face is detected). So, if there are two images each of which has two faces in them, the parameters will be the following: - First face in the first image: `faceIndex: 0`, `imageIndex: 0` - Second face in the first image: `faceIndex: 1`, `imageIndex: 0` - First face of the second image: `faceIndex: 0`, `imageIndex: 1` - Second face in the second image: `faceIndex: 1`, `imageIndex: 1`
 
         :param match_request: (required)
         :type match_request: MatchRequest

regula/facesdk/webclient/gen/models/liveness_type.py

@@ -12,14 +12,15 @@
 
 class LivenessType(int, Enum):
     """
-    Liveness detection can be performed in two modes: active `0` and passive `1`. [Learn more](https://docs.regulaforensics.com/develop/face-sdk/web-service/development/usage/liveness/#active-and-passive-modes)
+    Liveness detection can be performed in three modes: active `0`,  passive `1`, and passive with blink `2`. [Learn more](https://docs.regulaforensics.com/develop/face-sdk/web-service/development/usage/liveness/#active-and-passive-modes)
     """
 
     """
     allowed enum values
     """
     ACTIVE = 0
     PASSIVE = 1
+    PASSIVE_WITH_BLINK = 2
 
     @classmethod
     def from_json(cls, json_str: str) -> Self:

regula/facesdk/webclient/gen/models/match_and_search_request_images_item.py

@@ -23,7 +23,8 @@ class MatchAndSearchRequestImagesItem(BaseModel):
     content: SkipValidation[Optional[bytearray]] = Field(alias="content", default=None, description="Base64-encoded image.")
     image_url: SkipValidation[Optional[str]] = Field(alias="imageUrl", default=None, description="Image URL.")
     type: SkipValidation[Optional[ImageSource]] = Field(alias="type", default=None)
-    __properties: ClassVar[List[str]] = ["content", "imageUrl", "type"]
+    liveness_transaction_id: SkipValidation[Optional[str]] = Field(alias="livenessTransactionId", default=None, description="Identifier of the completed liveness transaction whose captured face is used as one of the comparison inputs. If this parameter is provided, it replaces one of the images in the matching request.")
+    __properties: ClassVar[List[str]] = ["content", "imageUrl", "type", "livenessTransactionId"]
 
     model_config = ConfigDict(
         populate_by_name=True,
@@ -80,7 +81,8 @@ def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
         _obj = cls.model_validate({
             "content": obj.get("content"),
             "imageUrl": obj.get("imageUrl"),
-            "type": obj.get("type")
+            "type": obj.get("type"),
+            "livenessTransactionId": obj.get("livenessTransactionId")
         })
         return _obj
 

regula/facesdk/webclient/gen/models/match_image.py

@@ -24,7 +24,8 @@ class MatchImage(BaseModel):
     type: SkipValidation[Optional[ImageSource]] = Field(alias="type", default=None)
     data: SkipValidation[bytearray] = Field(alias="data", description="Base64-encoded image.")
     detect_all: SkipValidation[Optional[bool]] = Field(alias="detectAll", default=None, description="Whether to detect all faces in the image. If set to `false`, only the most central face is detected.")
-    __properties: ClassVar[List[str]] = ["index", "type", "data", "detectAll"]
+    liveness_transaction_id: SkipValidation[Optional[str]] = Field(alias="livenessTransactionId", default=None, description="Identifier of the completed liveness transaction whose captured face is used as one of the comparison inputs. If this parameter is provided, it replaces one of the images in the matching request.")
+    __properties: ClassVar[List[str]] = ["index", "type", "data", "detectAll", "livenessTransactionId"]
 
     model_config = ConfigDict(
         populate_by_name=True,
@@ -82,7 +83,8 @@ def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
             "index": obj.get("index"),
             "type": obj.get("type"),
             "data": obj.get("data"),
-            "detectAll": obj.get("detectAll") if obj.get("detectAll") is not None else False
+            "detectAll": obj.get("detectAll") if obj.get("detectAll") is not None else False,
+            "livenessTransactionId": obj.get("livenessTransactionId")
         })
         return _obj