diff --git a/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/models/__init__.py b/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/models/__init__.py
index 39c2758f7e00..eb488346f616 100644
--- a/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/models/__init__.py
+++ b/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/models/__init__.py
@@ -114,6 +114,7 @@
     SnapshotObjectType,
     OperationStatusType,
     FaceAttributeType,
+    DetectionModel,
 )
 
 __all__ = [
@@ -175,4 +176,5 @@
     'SnapshotObjectType',
     'OperationStatusType',
     'FaceAttributeType',
+    'DetectionModel',
 ]
diff --git a/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/models/face_client_enums.py b/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/models/face_client_enums.py
index 6eb661a0b2c3..b3fed2fd6d7f 100644
--- a/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/models/face_client_enums.py
+++ b/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/models/face_client_enums.py
@@ -123,3 +123,9 @@ class FaceAttributeType(str, Enum):
     blur = "blur"
     exposure = "exposure"
     noise = "noise"
+
+
+class DetectionModel(str, Enum):
+
+    detection_01 = "detection_01"
+    detection_02 = "detection_02"
diff --git a/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/face_list_operations.py b/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/face_list_operations.py
index 5e8c39a10751..9a7420dea8ff 100644
--- a/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/face_list_operations.py
+++ b/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/face_list_operations.py
@@ -397,7 +397,7 @@ def delete_face(
     delete_face.metadata = {'url': '/facelists/{faceListId}/persistedfaces/{persistedFaceId}'}
 
     def add_face_from_url(
-            self, face_list_id, url, user_data=None, target_face=None, custom_headers=None, raw=False, **operation_config):
+            self, face_list_id, url, user_data=None, target_face=None, detection_model="detection_01", custom_headers=None, raw=False, **operation_config):
         """Add a face to a specified face list, up to 1,000 faces.
         <br /> To deal with an image contains multiple faces, input face can be
         specified as an image with a targetFace rectangle. It returns a
@@ -425,6 +425,21 @@ def add_face_from_url(
         head-pose, or large occlusions will cause failures.
         * Adding/deleting faces to/from a same face list are processed
         sequentially and to/from different face lists are in parallel.
+        * The minimum detectable face size is 36x36 pixels in an image no
+        larger than 1920x1080 pixels. Images with dimensions higher than
+        1920x1080 pixels will need a proportionally larger minimum face size.
+        * Different 'detectionModel' values can be provided. To use and compare
+        different detection models, please refer to [How to specify a detection
+        model](https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model)
+        | Model | Recommended use-case(s) |
+        | ---------- | -------- |
+        | 'detection_01': | The default detection model for [FaceList - Add
+        Face](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395250).
+        Recommend for near frontal face detection. For scenarios with
+        exceptionally large angle (head-pose) faces, occluded faces or wrong
+        image orientation, the faces in such cases may not be detected. |
+        | 'detection_02': | Detection model released in 2019 May with improved
+        accuracy especially on small, side and blurry faces. |.
 
         :param face_list_id: Id referencing a particular face list.
         :type face_list_id: str
@@ -439,6 +454,14 @@ def add_face_from_url(
          image, targetFace is required to specify which face to add. No
          targetFace means there is only one face detected in the entire image.
         :type target_face: list[int]
+        :param detection_model: Name of detection model. Detection model is
+         used to detect faces in the submitted image. A detection model name
+         can be provided when performing Face - Detect or (Large)FaceList - Add
+         Face or (Large)PersonGroup - Add Face. The default value is
+         'detection_01', if another model is needed, please explicitly specify
+         it. Possible values include: 'detection_01', 'detection_02'
+        :type detection_model: str or
+         ~azure.cognitiveservices.vision.face.models.DetectionModel
         :param dict custom_headers: headers that will be added to the request
         :param bool raw: returns the direct response alongside the
          deserialized response
@@ -466,6 +489,8 @@ def add_face_from_url(
             query_parameters['userData'] = self._serialize.query("user_data", user_data, 'str', max_length=1024)
         if target_face is not None:
             query_parameters['targetFace'] = self._serialize.query("target_face", target_face, '[int]', div=',')
+        if detection_model is not None:
+            query_parameters['detectionModel'] = self._serialize.query("detection_model", detection_model, 'str')
 
         # Construct headers
         header_parameters = {}
@@ -497,10 +522,49 @@ def add_face_from_url(
     add_face_from_url.metadata = {'url': '/facelists/{faceListId}/persistedfaces'}
 
     def add_face_from_stream(
-            self, face_list_id, image, user_data=None, target_face=None, custom_headers=None, raw=False, callback=None, **operation_config):
-        """Add a face to a face list. The input face is specified as an image with
-        a targetFace rectangle. It returns a persistedFaceId representing the
-        added face, and persistedFaceId will not expire.
+            self, face_list_id, image, user_data=None, target_face=None, detection_model="detection_01", custom_headers=None, raw=False, callback=None, **operation_config):
+        """Add a face to a specified face list, up to 1,000 faces.
+        <br /> To deal with an image contains multiple faces, input face can be
+        specified as an image with a targetFace rectangle. It returns a
+        persistedFaceId representing the added face. No image will be stored.
+        Only the extracted face feature will be stored on server until
+        [FaceList - Delete
+        Face](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395251)
+        or [FaceList -
+        Delete](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f3039524f)
+        is called.
+        <br /> Note persistedFaceId is different from faceId generated by [Face
+        -
+        Detect](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236).
+        * Higher face image quality means better detection and recognition
+        precision. Please consider high-quality faces: frontal, clear, and face
+        size is 200x200 pixels (100 pixels between eyes) or bigger.
+        * JPEG, PNG, GIF (the first frame), and BMP format are supported. The
+        allowed image file size is from 1KB to 6MB.
+        * "targetFace" rectangle should contain one face. Zero or multiple
+        faces will be regarded as an error. If the provided "targetFace"
+        rectangle is not returned from [Face -
+        Detect](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236),
+        there’s no guarantee to detect and add the face successfully.
+        * Out of detectable face size (36x36 - 4096x4096 pixels), large
+        head-pose, or large occlusions will cause failures.
+        * Adding/deleting faces to/from a same face list are processed
+        sequentially and to/from different face lists are in parallel.
+        * The minimum detectable face size is 36x36 pixels in an image no
+        larger than 1920x1080 pixels. Images with dimensions higher than
+        1920x1080 pixels will need a proportionally larger minimum face size.
+        * Different 'detectionModel' values can be provided. To use and compare
+        different detection models, please refer to [How to specify a detection
+        model](https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model)
+        | Model | Recommended use-case(s) |
+        | ---------- | -------- |
+        | 'detection_01': | The default detection model for [FaceList - Add
+        Face](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395250).
+        Recommend for near frontal face detection. For scenarios with
+        exceptionally large angle (head-pose) faces, occluded faces or wrong
+        image orientation, the faces in such cases may not be detected. |
+        | 'detection_02': | Detection model released in 2019 May with improved
+        accuracy especially on small, side and blurry faces. |.
 
         :param face_list_id: Id referencing a particular face list.
         :type face_list_id: str
@@ -515,6 +579,14 @@ def add_face_from_stream(
          image, targetFace is required to specify which face to add. No
          targetFace means there is only one face detected in the entire image.
         :type target_face: list[int]
+        :param detection_model: Name of detection model. Detection model is
+         used to detect faces in the submitted image. A detection model name
+         can be provided when performing Face - Detect or (Large)FaceList - Add
+         Face or (Large)PersonGroup - Add Face. The default value is
+         'detection_01', if another model is needed, please explicitly specify
+         it. Possible values include: 'detection_01', 'detection_02'
+        :type detection_model: str or
+         ~azure.cognitiveservices.vision.face.models.DetectionModel
         :param dict custom_headers: headers that will be added to the request
         :param bool raw: returns the direct response alongside the
          deserialized response
@@ -545,6 +617,8 @@ def add_face_from_stream(
             query_parameters['userData'] = self._serialize.query("user_data", user_data, 'str', max_length=1024)
         if target_face is not None:
             query_parameters['targetFace'] = self._serialize.query("target_face", target_face, '[int]', div=',')
+        if detection_model is not None:
+            query_parameters['detectionModel'] = self._serialize.query("detection_model", detection_model, 'str')
 
         # Construct headers
         header_parameters = {}
diff --git a/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/face_operations.py b/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/face_operations.py
index 85f8696dbe58..6339928243a6 100644
--- a/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/face_operations.py
+++ b/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/face_operations.py
@@ -397,13 +397,9 @@ def verify_face_to_face(
     verify_face_to_face.metadata = {'url': '/verify'}
 
     def detect_with_url(
-            self, url, return_face_id=True, return_face_landmarks=False, return_face_attributes=None, recognition_model="recognition_01", return_recognition_model=False, custom_headers=None, raw=False, **operation_config):
+            self, url, return_face_id=True, return_face_landmarks=False, return_face_attributes=None, recognition_model="recognition_01", return_recognition_model=False, detection_model="detection_01", custom_headers=None, raw=False, **operation_config):
         """Detect human faces in an image, return face rectangles, and optionally
         with faceIds, landmarks, and attributes.<br />
-        * Optional parameters including faceId, landmarks, and attributes.
-        Attributes include age, gender, headPose, smile, facialHair, glasses,
-        emotion, hair, makeup, occlusion, accessories, blur, exposure and
-        noise.
         * No image will be stored. Only the extracted face feature will be
         stored on server. The faceId is an identifier of the face feature and
         will be used in [Face -
@@ -412,23 +408,40 @@ def detect_with_url(
         Verify](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f3039523a),
         and [Face - Find
         Similar](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395237).
-        It will expire 24 hours after the detection call.
-        * Higher face image quality means better detection and recognition
-        precision. Please consider high-quality faces: frontal, clear, and face
-        size is 200x200 pixels (100 pixels between eyes) or bigger.
+        The stored face feature(s) will expire and be deleted 24 hours after
+        the original detection call.
+        * Optional parameters include faceId, landmarks, and attributes.
+        Attributes include age, gender, headPose, smile, facialHair, glasses,
+        emotion, hair, makeup, occlusion, accessories, blur, exposure and
+        noise. Some of the results returned for specific attributes may not be
+        highly accurate.
         * JPEG, PNG, GIF (the first frame), and BMP format are supported. The
         allowed image file size is from 1KB to 6MB.
-        * Faces are detectable when its size is 36x36 to 4096x4096 pixels. If
-        need to detect very small but clear faces, please try to enlarge the
-        input image.
-        * Up to 64 faces can be returned for an image. Faces are ranked by face
-        rectangle size from large to small.
-        * Face detector prefer frontal and near-frontal faces. There are cases
-        that faces may not be detected, e.g. exceptionally large face angles
-        (head-pose) or being occluded, or wrong image orientation.
-        * Attributes (age, gender, headPose, smile, facialHair, glasses,
-        emotion, hair, makeup, occlusion, accessories, blur, exposure and
-        noise) may not be perfectly accurate.
+        * Up to 100 faces can be returned for an image. Faces are ranked by
+        face rectangle size from large to small.
+        * For optimal results when querying [Face -
+        Identify](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395239),
+        [Face -
+        Verify](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f3039523a),
+        and [Face - Find
+        Similar](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395237)
+        ('returnFaceId' is true), please use faces that are: frontal, clear,
+        and with a minimum size of 200x200 pixels (100 pixels between eyes).
+        * The minimum detectable face size is 36x36 pixels in an image no
+        larger than 1920x1080 pixels. Images with dimensions higher than
+        1920x1080 pixels will need a proportionally larger minimum face size.
+        * Different 'detectionModel' values can be provided. To use and compare
+        different detection models, please refer to [How to specify a detection
+        model](https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model)
+        | Model | Recommended use-case(s) |
+        | ---------- | -------- |
+        | 'detection_01': | The default detection model for [Face -
+        Detect](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236).
+        Recommend for near frontal face detection. For scenarios with
+        exceptionally large angle (head-pose) faces, occluded faces or wrong
+        image orientation, the faces in such cases may not be detected. |
+        | 'detection_02': | Detection model released in 2019 May with improved
+        accuracy especially on small, side and blurry faces. |
         * Different 'recognitionModel' values are provided. If follow-up
         operations like Verify, Identify, Find Similar are needed, please
         specify the recognition model with 'recognitionModel' parameter. The
@@ -437,7 +450,16 @@ def detect_with_url(
         parameter. Once specified, the detected faceIds will be associated with
         the specified recognition model. More details, please refer to [How to
         specify a recognition
-        model](https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/specify-recognition-model).
+        model](https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/specify-recognition-model)
+        | Model | Recommended use-case(s) |
+        | ---------- | -------- |
+        | 'recognition_01': | The default recognition model for [Face -
+        Detect](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236).
+        All those faceIds created before 2019 March are bonded with this
+        recognition model. |
+        | 'recognition_02': | Recognition model released in 2019 March.
+        'recognition_02' is recommended since its overall accuracy is improved
+        compared with 'recognition_01'. |.
 
         :param url: Publicly reachable URL of an image
         :type url: str
@@ -468,6 +490,14 @@ def detect_with_url(
         :param return_recognition_model: A value indicating whether the
          operation should return 'recognitionModel' in response.
         :type return_recognition_model: bool
+        :param detection_model: Name of detection model. Detection model is
+         used to detect faces in the submitted image. A detection model name
+         can be provided when performing Face - Detect or (Large)FaceList - Add
+         Face or (Large)PersonGroup - Add Face. The default value is
+         'detection_01', if another model is needed, please explicitly specify
+         it. Possible values include: 'detection_01', 'detection_02'
+        :type detection_model: str or
+         ~azure.cognitiveservices.vision.face.models.DetectionModel
         :param dict custom_headers: headers that will be added to the request
         :param bool raw: returns the direct response alongside the
          deserialized response
@@ -500,6 +530,8 @@ def detect_with_url(
             query_parameters['recognitionModel'] = self._serialize.query("recognition_model", recognition_model, 'str')
         if return_recognition_model is not None:
             query_parameters['returnRecognitionModel'] = self._serialize.query("return_recognition_model", return_recognition_model, 'bool')
+        if detection_model is not None:
+            query_parameters['detectionModel'] = self._serialize.query("detection_model", detection_model, 'str')
 
         # Construct headers
         header_parameters = {}
@@ -604,9 +636,69 @@ def verify_face_to_person(
     verify_face_to_person.metadata = {'url': '/verify'}
 
     def detect_with_stream(
-            self, image, return_face_id=True, return_face_landmarks=False, return_face_attributes=None, recognition_model="recognition_01", return_recognition_model=False, custom_headers=None, raw=False, callback=None, **operation_config):
-        """Detect human faces in an image and returns face locations, and
-        optionally with faceIds, landmarks, and attributes.
+            self, image, return_face_id=True, return_face_landmarks=False, return_face_attributes=None, recognition_model="recognition_01", return_recognition_model=False, detection_model="detection_01", custom_headers=None, raw=False, callback=None, **operation_config):
+        """Detect human faces in an image, return face rectangles, and optionally
+        with faceIds, landmarks, and attributes.<br />
+        * No image will be stored. Only the extracted face feature will be
+        stored on server. The faceId is an identifier of the face feature and
+        will be used in [Face -
+        Identify](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395239),
+        [Face -
+        Verify](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f3039523a),
+        and [Face - Find
+        Similar](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395237).
+        The stored face feature(s) will expire and be deleted 24 hours after
+        the original detection call.
+        * Optional parameters include faceId, landmarks, and attributes.
+        Attributes include age, gender, headPose, smile, facialHair, glasses,
+        emotion, hair, makeup, occlusion, accessories, blur, exposure and
+        noise. Some of the results returned for specific attributes may not be
+        highly accurate.
+        * JPEG, PNG, GIF (the first frame), and BMP format are supported. The
+        allowed image file size is from 1KB to 6MB.
+        * Up to 100 faces can be returned for an image. Faces are ranked by
+        face rectangle size from large to small.
+        * For optimal results when querying [Face -
+        Identify](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395239),
+        [Face -
+        Verify](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f3039523a),
+        and [Face - Find
+        Similar](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395237)
+        ('returnFaceId' is true), please use faces that are: frontal, clear,
+        and with a minimum size of 200x200 pixels (100 pixels between eyes).
+        * The minimum detectable face size is 36x36 pixels in an image no
+        larger than 1920x1080 pixels. Images with dimensions higher than
+        1920x1080 pixels will need a proportionally larger minimum face size.
+        * Different 'detectionModel' values can be provided. To use and compare
+        different detection models, please refer to [How to specify a detection
+        model](https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model)
+        | Model | Recommended use-case(s) |
+        | ---------- | -------- |
+        | 'detection_01': | The default detection model for [Face -
+        Detect](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236).
+        Recommend for near frontal face detection. For scenarios with
+        exceptionally large angle (head-pose) faces, occluded faces or wrong
+        image orientation, the faces in such cases may not be detected. |
+        | 'detection_02': | Detection model released in 2019 May with improved
+        accuracy especially on small, side and blurry faces. |
+        * Different 'recognitionModel' values are provided. If follow-up
+        operations like Verify, Identify, Find Similar are needed, please
+        specify the recognition model with 'recognitionModel' parameter. The
+        default value for 'recognitionModel' is 'recognition_01', if latest
+        model needed, please explicitly specify the model you need in this
+        parameter. Once specified, the detected faceIds will be associated with
+        the specified recognition model. More details, please refer to [How to
+        specify a recognition
+        model](https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/specify-recognition-model)
+        | Model | Recommended use-case(s) |
+        | ---------- | -------- |
+        | 'recognition_01': | The default recognition model for [Face -
+        Detect](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236).
+        All those faceIds created before 2019 March are bonded with this
+        recognition model. |
+        | 'recognition_02': | Recognition model released in 2019 March.
+        'recognition_02' is recommended since its overall accuracy is improved
+        compared with 'recognition_01'. |.
 
         :param image: An image stream.
         :type image: Generator
@@ -637,6 +729,14 @@ def detect_with_stream(
         :param return_recognition_model: A value indicating whether the
          operation should return 'recognitionModel' in response.
         :type return_recognition_model: bool
+        :param detection_model: Name of detection model. Detection model is
+         used to detect faces in the submitted image. A detection model name
+         can be provided when performing Face - Detect or (Large)FaceList - Add
+         Face or (Large)PersonGroup - Add Face. The default value is
+         'detection_01', if another model is needed, please explicitly specify
+         it. Possible values include: 'detection_01', 'detection_02'
+        :type detection_model: str or
+         ~azure.cognitiveservices.vision.face.models.DetectionModel
         :param dict custom_headers: headers that will be added to the request
         :param bool raw: returns the direct response alongside the
          deserialized response
@@ -672,6 +772,8 @@ def detect_with_stream(
             query_parameters['recognitionModel'] = self._serialize.query("recognition_model", recognition_model, 'str')
         if return_recognition_model is not None:
             query_parameters['returnRecognitionModel'] = self._serialize.query("return_recognition_model", return_recognition_model, 'bool')
+        if detection_model is not None:
+            query_parameters['detectionModel'] = self._serialize.query("detection_model", detection_model, 'str')
 
         # Construct headers
         header_parameters = {}
diff --git a/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/large_face_list_operations.py b/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/large_face_list_operations.py
index 33a5970a3d9e..ba70e8c6b02f 100644
--- a/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/large_face_list_operations.py
+++ b/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/large_face_list_operations.py
@@ -639,7 +639,7 @@ def update_face(
     update_face.metadata = {'url': '/largefacelists/{largeFaceListId}/persistedfaces/{persistedFaceId}'}
 
     def add_face_from_url(
-            self, large_face_list_id, url, user_data=None, target_face=None, custom_headers=None, raw=False, **operation_config):
+            self, large_face_list_id, url, user_data=None, target_face=None, detection_model="detection_01", custom_headers=None, raw=False, **operation_config):
         """Add a face to a specified large face list, up to 1,000,000 faces.
         <br /> To deal with an image contains multiple faces, input face can be
         specified as an image with a targetFace rectangle. It returns a
@@ -667,6 +667,22 @@ def add_face_from_url(
         head-pose, or large occlusions will cause failures.
         * Adding/deleting faces to/from a same face list are processed
         sequentially and to/from different face lists are in parallel.
+        * The minimum detectable face size is 36x36 pixels in an image no
+        larger than 1920x1080 pixels. Images with dimensions higher than
+        1920x1080 pixels will need a proportionally larger minimum face size.
+        * Different 'detectionModel' values can be provided. To use and compare
+        different detection models, please refer to [How to specify a detection
+        model](https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model)
+        | Model | Recommended use-case(s) |
+        | ---------- | -------- |
+        | 'detection_01': | The default detection model for [LargeFaceList -
+        Add
+        Face](/docs/services/563879b61984550e40cbbe8d/operations/5a158c10d2de3616c086f2d3).
+        Recommend for near frontal face detection. For scenarios with
+        exceptionally large angle (head-pose) faces, occluded faces or wrong
+        image orientation, the faces in such cases may not be detected. |
+        | 'detection_02': | Detection model released in 2019 May with improved
+        accuracy especially on small, side and blurry faces. |
         Quota:
         * Free-tier subscription quota: 1,000 faces per large face list.
         * S0-tier subscription quota: 1,000,000 faces per large face list.
@@ -685,6 +701,14 @@ def add_face_from_url(
          image, targetFace is required to specify which face to add. No
          targetFace means there is only one face detected in the entire image.
         :type target_face: list[int]
+        :param detection_model: Name of detection model. Detection model is
+         used to detect faces in the submitted image. A detection model name
+         can be provided when performing Face - Detect or (Large)FaceList - Add
+         Face or (Large)PersonGroup - Add Face. The default value is
+         'detection_01', if another model is needed, please explicitly specify
+         it. Possible values include: 'detection_01', 'detection_02'
+        :type detection_model: str or
+         ~azure.cognitiveservices.vision.face.models.DetectionModel
         :param dict custom_headers: headers that will be added to the request
         :param bool raw: returns the direct response alongside the
          deserialized response
@@ -712,6 +736,8 @@ def add_face_from_url(
             query_parameters['userData'] = self._serialize.query("user_data", user_data, 'str', max_length=1024)
         if target_face is not None:
             query_parameters['targetFace'] = self._serialize.query("target_face", target_face, '[int]', div=',')
+        if detection_model is not None:
+            query_parameters['detectionModel'] = self._serialize.query("detection_model", detection_model, 'str')
 
         # Construct headers
         header_parameters = {}
@@ -810,10 +836,53 @@ def list_faces(
     list_faces.metadata = {'url': '/largefacelists/{largeFaceListId}/persistedfaces'}
 
     def add_face_from_stream(
-            self, large_face_list_id, image, user_data=None, target_face=None, custom_headers=None, raw=False, callback=None, **operation_config):
-        """Add a face to a large face list. The input face is specified as an
-        image with a targetFace rectangle. It returns a persistedFaceId
-        representing the added face, and persistedFaceId will not expire.
+            self, large_face_list_id, image, user_data=None, target_face=None, detection_model="detection_01", custom_headers=None, raw=False, callback=None, **operation_config):
+        """Add a face to a specified large face list, up to 1,000,000 faces.
+        <br /> To deal with an image contains multiple faces, input face can be
+        specified as an image with a targetFace rectangle. It returns a
+        persistedFaceId representing the added face. No image will be stored.
+        Only the extracted face feature will be stored on server until
+        [LargeFaceList Face -
+        Delete](/docs/services/563879b61984550e40cbbe8d/operations/5a158c8ad2de3616c086f2d4)
+        or [LargeFaceList -
+        Delete](/docs/services/563879b61984550e40cbbe8d/operations/5a1580d5d2de3616c086f2cd)
+        is called.
+        <br /> Note persistedFaceId is different from faceId generated by [Face
+        -
+        Detect](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236).
+        * Higher face image quality means better recognition precision. Please
+        consider high-quality faces: frontal, clear, and face size is 200x200
+        pixels (100 pixels between eyes) or bigger.
+        * JPEG, PNG, GIF (the first frame), and BMP format are supported. The
+        allowed image file size is from 1KB to 6MB.
+        * "targetFace" rectangle should contain one face. Zero or multiple
+        faces will be regarded as an error. If the provided "targetFace"
+        rectangle is not returned from [Face -
+        Detect](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236),
+        there’s no guarantee to detect and add the face successfully.
+        * Out of detectable face size (36x36 - 4096x4096 pixels), large
+        head-pose, or large occlusions will cause failures.
+        * Adding/deleting faces to/from a same face list are processed
+        sequentially and to/from different face lists are in parallel.
+        * The minimum detectable face size is 36x36 pixels in an image no
+        larger than 1920x1080 pixels. Images with dimensions higher than
+        1920x1080 pixels will need a proportionally larger minimum face size.
+        * Different 'detectionModel' values can be provided. To use and compare
+        different detection models, please refer to [How to specify a detection
+        model](https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model)
+        | Model | Recommended use-case(s) |
+        | ---------- | -------- |
+        | 'detection_01': | The default detection model for [LargeFaceList -
+        Add
+        Face](/docs/services/563879b61984550e40cbbe8d/operations/5a158c10d2de3616c086f2d3).
+        Recommend for near frontal face detection. For scenarios with
+        exceptionally large angle (head-pose) faces, occluded faces or wrong
+        image orientation, the faces in such cases may not be detected. |
+        | 'detection_02': | Detection model released in 2019 May with improved
+        accuracy especially on small, side and blurry faces. |
+        Quota:
+        * Free-tier subscription quota: 1,000 faces per large face list.
+        * S0-tier subscription quota: 1,000,000 faces per large face list.
 
         :param large_face_list_id: Id referencing a particular large face
          list.
@@ -829,6 +898,14 @@ def add_face_from_stream(
          image, targetFace is required to specify which face to add. No
          targetFace means there is only one face detected in the entire image.
         :type target_face: list[int]
+        :param detection_model: Name of detection model. Detection model is
+         used to detect faces in the submitted image. A detection model name
+         can be provided when performing Face - Detect or (Large)FaceList - Add
+         Face or (Large)PersonGroup - Add Face. The default value is
+         'detection_01', if another model is needed, please explicitly specify
+         it. Possible values include: 'detection_01', 'detection_02'
+        :type detection_model: str or
+         ~azure.cognitiveservices.vision.face.models.DetectionModel
         :param dict custom_headers: headers that will be added to the request
         :param bool raw: returns the direct response alongside the
          deserialized response
@@ -859,6 +936,8 @@ def add_face_from_stream(
             query_parameters['userData'] = self._serialize.query("user_data", user_data, 'str', max_length=1024)
         if target_face is not None:
             query_parameters['targetFace'] = self._serialize.query("target_face", target_face, '[int]', div=',')
+        if detection_model is not None:
+            query_parameters['detectionModel'] = self._serialize.query("detection_model", detection_model, 'str')
 
         # Construct headers
         header_parameters = {}
diff --git a/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/large_person_group_person_operations.py b/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/large_person_group_person_operations.py
index 28f5aacf3b41..a61caa0bdd7b 100644
--- a/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/large_person_group_person_operations.py
+++ b/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/large_person_group_person_operations.py
@@ -509,7 +509,7 @@ def update_face(
     update_face.metadata = {'url': '/largepersongroups/{largePersonGroupId}/persons/{personId}/persistedfaces/{persistedFaceId}'}
 
     def add_face_from_url(
-            self, large_person_group_id, person_id, url, user_data=None, target_face=None, custom_headers=None, raw=False, **operation_config):
+            self, large_person_group_id, person_id, url, user_data=None, target_face=None, detection_model="detection_01", custom_headers=None, raw=False, **operation_config):
         """Add a face to a person into a large person group for face
         identification or verification. To deal with an image contains multiple
         faces, input face can be specified as an image with a targetFace
@@ -541,6 +541,22 @@ def add_face_from_url(
         * Adding/deleting faces to/from a same person will be processed
         sequentially. Adding/deleting faces to/from different persons are
         processed in parallel.
+        * The minimum detectable face size is 36x36 pixels in an image no
+        larger than 1920x1080 pixels. Images with dimensions higher than
+        1920x1080 pixels will need a proportionally larger minimum face size.
+        * Different 'detectionModel' values can be provided. To use and compare
+        different detection models, please refer to [How to specify a detection
+        model](https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model)
+        | Model | Recommended use-case(s) |
+        | ---------- | -------- |
+        | 'detection_01': | The default detection model for [LargePersonGroup
+        Person - Add
+        Face](/docs/services/563879b61984550e40cbbe8d/operations/599adf2a3a7b9412a4d53f42).
+        Recommend for near frontal face detection. For scenarios with
+        exceptionally large angle (head-pose) faces, occluded faces or wrong
+        image orientation, the faces in such cases may not be detected. |
+        | 'detection_02': | Detection model released in 2019 May with improved
+        accuracy especially on small, side and blurry faces. |.
 
         :param large_person_group_id: Id referencing a particular large person
          group.
@@ -558,6 +574,14 @@ def add_face_from_url(
          image, targetFace is required to specify which face to add. No
          targetFace means there is only one face detected in the entire image.
         :type target_face: list[int]
+        :param detection_model: Name of detection model. Detection model is
+         used to detect faces in the submitted image. A detection model name
+         can be provided when performing Face - Detect or (Large)FaceList - Add
+         Face or (Large)PersonGroup - Add Face. The default value is
+         'detection_01', if another model is needed, please explicitly specify
+         it. Possible values include: 'detection_01', 'detection_02'
+        :type detection_model: str or
+         ~azure.cognitiveservices.vision.face.models.DetectionModel
         :param dict custom_headers: headers that will be added to the request
         :param bool raw: returns the direct response alongside the
          deserialized response
@@ -586,6 +610,8 @@ def add_face_from_url(
             query_parameters['userData'] = self._serialize.query("user_data", user_data, 'str', max_length=1024)
         if target_face is not None:
             query_parameters['targetFace'] = self._serialize.query("target_face", target_face, '[int]', div=',')
+        if detection_model is not None:
+            query_parameters['detectionModel'] = self._serialize.query("detection_model", detection_model, 'str')
 
         # Construct headers
         header_parameters = {}
@@ -617,9 +643,54 @@ def add_face_from_url(
     add_face_from_url.metadata = {'url': '/largepersongroups/{largePersonGroupId}/persons/{personId}/persistedfaces'}
 
     def add_face_from_stream(
-            self, large_person_group_id, person_id, image, user_data=None, target_face=None, custom_headers=None, raw=False, callback=None, **operation_config):
-        """Add a representative face to a person for identification. The input
-        face is specified as an image with a targetFace rectangle.
+            self, large_person_group_id, person_id, image, user_data=None, target_face=None, detection_model="detection_01", custom_headers=None, raw=False, callback=None, **operation_config):
+        """Add a face to a person into a large person group for face
+        identification or verification. To deal with an image contains multiple
+        faces, input face can be specified as an image with a targetFace
+        rectangle. It returns a persistedFaceId representing the added face. No
+        image will be stored. Only the extracted face feature will be stored on
+        server until [LargePersonGroup PersonFace -
+        Delete](/docs/services/563879b61984550e40cbbe8d/operations/599ae2966ac60f11b48b5aa3),
+        [LargePersonGroup Person -
+        Delete](/docs/services/563879b61984550e40cbbe8d/operations/599ade5c6ac60f11b48b5aa2)
+        or [LargePersonGroup -
+        Delete](/docs/services/563879b61984550e40cbbe8d/operations/599adc216ac60f11b48b5a9f)
+        is called.
+        <br /> Note persistedFaceId is different from faceId generated by [Face
+        -
+        Detect](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236).
+        * Higher face image quality means better recognition precision. Please
+        consider high-quality faces: frontal, clear, and face size is 200x200
+        pixels (100 pixels between eyes) or bigger.
+        * Each person entry can hold up to 248 faces.
+        * JPEG, PNG, GIF (the first frame), and BMP format are supported. The
+        allowed image file size is from 1KB to 6MB.
+        * "targetFace" rectangle should contain one face. Zero or multiple
+        faces will be regarded as an error. If the provided "targetFace"
+        rectangle is not returned from [Face -
+        Detect](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236),
+        there’s no guarantee to detect and add the face successfully.
+        * Out of detectable face size (36x36 - 4096x4096 pixels), large
+        head-pose, or large occlusions will cause failures.
+        * Adding/deleting faces to/from a same person will be processed
+        sequentially. Adding/deleting faces to/from different persons are
+        processed in parallel.
+        * The minimum detectable face size is 36x36 pixels in an image no
+        larger than 1920x1080 pixels. Images with dimensions higher than
+        1920x1080 pixels will need a proportionally larger minimum face size.
+        * Different 'detectionModel' values can be provided. To use and compare
+        different detection models, please refer to [How to specify a detection
+        model](https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model)
+        | Model | Recommended use-case(s) |
+        | ---------- | -------- |
+        | 'detection_01': | The default detection model for [LargePersonGroup
+        Person - Add
+        Face](/docs/services/563879b61984550e40cbbe8d/operations/599adf2a3a7b9412a4d53f42).
+        Recommend for near frontal face detection. For scenarios with
+        exceptionally large angle (head-pose) faces, occluded faces or wrong
+        image orientation, the faces in such cases may not be detected. |
+        | 'detection_02': | Detection model released in 2019 May with improved
+        accuracy especially on small, side and blurry faces. |.
 
         :param large_person_group_id: Id referencing a particular large person
          group.
@@ -637,6 +708,14 @@ def add_face_from_stream(
          image, targetFace is required to specify which face to add. No
          targetFace means there is only one face detected in the entire image.
         :type target_face: list[int]
+        :param detection_model: Name of detection model. Detection model is
+         used to detect faces in the submitted image. A detection model name
+         can be provided when performing Face - Detect or (Large)FaceList - Add
+         Face or (Large)PersonGroup - Add Face. The default value is
+         'detection_01', if another model is needed, please explicitly specify
+         it. Possible values include: 'detection_01', 'detection_02'
+        :type detection_model: str or
+         ~azure.cognitiveservices.vision.face.models.DetectionModel
         :param dict custom_headers: headers that will be added to the request
         :param bool raw: returns the direct response alongside the
          deserialized response
@@ -668,6 +747,8 @@ def add_face_from_stream(
             query_parameters['userData'] = self._serialize.query("user_data", user_data, 'str', max_length=1024)
         if target_face is not None:
             query_parameters['targetFace'] = self._serialize.query("target_face", target_face, '[int]', div=',')
+        if detection_model is not None:
+            query_parameters['detectionModel'] = self._serialize.query("detection_model", detection_model, 'str')
 
         # Construct headers
         header_parameters = {}
diff --git a/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/person_group_person_operations.py b/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/person_group_person_operations.py
index 401dcdc8dc65..8dc83c2c5860 100644
--- a/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/person_group_person_operations.py
+++ b/sdk/cognitiveservices/azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/person_group_person_operations.py
@@ -531,18 +531,18 @@ def update_face(
     update_face.metadata = {'url': '/persongroups/{personGroupId}/persons/{personId}/persistedfaces/{persistedFaceId}'}
 
     def add_face_from_url(
-            self, person_group_id, person_id, url, user_data=None, target_face=None, custom_headers=None, raw=False, **operation_config):
-        """Add a face to a person into a large person group for face
-        identification or verification. To deal with an image contains multiple
-        faces, input face can be specified as an image with a targetFace
-        rectangle. It returns a persistedFaceId representing the added face. No
-        image will be stored. Only the extracted face feature will be stored on
-        server until [LargePersonGroup PersonFace -
-        Delete](/docs/services/563879b61984550e40cbbe8d/operations/599ae2966ac60f11b48b5aa3),
-        [LargePersonGroup Person -
-        Delete](/docs/services/563879b61984550e40cbbe8d/operations/599ade5c6ac60f11b48b5aa2)
-        or [LargePersonGroup -
-        Delete](/docs/services/563879b61984550e40cbbe8d/operations/599adc216ac60f11b48b5a9f)
+            self, person_group_id, person_id, url, user_data=None, target_face=None, detection_model="detection_01", custom_headers=None, raw=False, **operation_config):
+        """Add a face to a person into a person group for face identification or
+        verification. To deal with an image contains multiple faces, input face
+        can be specified as an image with a targetFace rectangle. It returns a
+        persistedFaceId representing the added face. No image will be stored.
+        Only the extracted face feature will be stored on server until
+        [PersonGroup PersonFace -
+        Delete](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f3039523e),
+        [PersonGroup Person -
+        Delete](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f3039523d)
+        or [PersonGroup -
+        Delete](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395245)
         is called.
         <br /> Note persistedFaceId is different from faceId generated by [Face
         -
@@ -563,6 +563,22 @@ def add_face_from_url(
         *   Adding/deleting faces to/from a same person will be processed
         sequentially. Adding/deleting faces to/from different persons are
         processed in parallel.
+        * The minimum detectable face size is 36x36 pixels in an image no
+        larger than 1920x1080 pixels. Images with dimensions higher than
+        1920x1080 pixels will need a proportionally larger minimum face size.
+        * Different 'detectionModel' values can be provided. To use and compare
+        different detection models, please refer to [How to specify a detection
+        model](https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model)
+        | Model | Recommended use-case(s) |
+        | ---------- | -------- |
+        | 'detection_01': | The default detection model for [PersonGroup Person
+        - Add
+        Face](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f3039523b).
+        Recommend for near frontal face detection. For scenarios with
+        exceptionally large angle (head-pose) faces, occluded faces or wrong
+        image orientation, the faces in such cases may not be detected. |
+        | 'detection_02': | Detection model released in 2019 May with improved
+        accuracy especially on small, side and blurry faces. |.
 
         :param person_group_id: Id referencing a particular person group.
         :type person_group_id: str
@@ -579,6 +595,14 @@ def add_face_from_url(
          image, targetFace is required to specify which face to add. No
          targetFace means there is only one face detected in the entire image.
         :type target_face: list[int]
+        :param detection_model: Name of detection model. Detection model is
+         used to detect faces in the submitted image. A detection model name
+         can be provided when performing Face - Detect or (Large)FaceList - Add
+         Face or (Large)PersonGroup - Add Face. The default value is
+         'detection_01', if another model is needed, please explicitly specify
+         it. Possible values include: 'detection_01', 'detection_02'
+        :type detection_model: str or
+         ~azure.cognitiveservices.vision.face.models.DetectionModel
         :param dict custom_headers: headers that will be added to the request
         :param bool raw: returns the direct response alongside the
          deserialized response
@@ -607,6 +631,8 @@ def add_face_from_url(
             query_parameters['userData'] = self._serialize.query("user_data", user_data, 'str', max_length=1024)
         if target_face is not None:
             query_parameters['targetFace'] = self._serialize.query("target_face", target_face, '[int]', div=',')
+        if detection_model is not None:
+            query_parameters['detectionModel'] = self._serialize.query("detection_model", detection_model, 'str')
 
         # Construct headers
         header_parameters = {}
@@ -638,9 +664,54 @@ def add_face_from_url(
     add_face_from_url.metadata = {'url': '/persongroups/{personGroupId}/persons/{personId}/persistedfaces'}
 
     def add_face_from_stream(
-            self, person_group_id, person_id, image, user_data=None, target_face=None, custom_headers=None, raw=False, callback=None, **operation_config):
-        """Add a representative face to a person for identification. The input
-        face is specified as an image with a targetFace rectangle.
+            self, person_group_id, person_id, image, user_data=None, target_face=None, detection_model="detection_01", custom_headers=None, raw=False, callback=None, **operation_config):
+        """Add a face to a person into a person group for face identification or
+        verification. To deal with an image contains multiple faces, input face
+        can be specified as an image with a targetFace rectangle. It returns a
+        persistedFaceId representing the added face. No image will be stored.
+        Only the extracted face feature will be stored on server until
+        [PersonGroup PersonFace -
+        Delete](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f3039523e),
+        [PersonGroup Person -
+        Delete](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f3039523d)
+        or [PersonGroup -
+        Delete](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395245)
+        is called.
+        <br /> Note persistedFaceId is different from faceId generated by [Face
+        -
+        Detect](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236).
+        *   Higher face image quality means better recognition precision.
+        Please consider high-quality faces: frontal, clear, and face size is
+        200x200 pixels (100 pixels between eyes) or bigger.
+        *   Each person entry can hold up to 248 faces.
+        *   JPEG, PNG, GIF (the first frame), and BMP format are supported. The
+        allowed image file size is from 1KB to 6MB.
+        *   "targetFace" rectangle should contain one face. Zero or multiple
+        faces will be regarded as an error. If the provided "targetFace"
+        rectangle is not returned from [Face -
+        Detect](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236),
+        there’s no guarantee to detect and add the face successfully.
+        *   Out of detectable face size (36x36 - 4096x4096 pixels), large
+        head-pose, or large occlusions will cause failures.
+        *   Adding/deleting faces to/from a same person will be processed
+        sequentially. Adding/deleting faces to/from different persons are
+        processed in parallel.
+        * The minimum detectable face size is 36x36 pixels in an image no
+        larger than 1920x1080 pixels. Images with dimensions higher than
+        1920x1080 pixels will need a proportionally larger minimum face size.
+        * Different 'detectionModel' values can be provided. To use and compare
+        different detection models, please refer to [How to specify a detection
+        model](https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model)
+        | Model | Recommended use-case(s) |
+        | ---------- | -------- |
+        | 'detection_01': | The default detection model for [PersonGroup Person
+        - Add
+        Face](/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f3039523b).
+        Recommend for near frontal face detection. For scenarios with
+        exceptionally large angle (head-pose) faces, occluded faces or wrong
+        image orientation, the faces in such cases may not be detected. |
+        | 'detection_02': | Detection model released in 2019 May with improved
+        accuracy especially on small, side and blurry faces. |.
 
         :param person_group_id: Id referencing a particular person group.
         :type person_group_id: str
@@ -657,6 +728,14 @@ def add_face_from_stream(
          image, targetFace is required to specify which face to add. No
          targetFace means there is only one face detected in the entire image.
         :type target_face: list[int]
+        :param detection_model: Name of detection model. Detection model is
+         used to detect faces in the submitted image. A detection model name
+         can be provided when performing Face - Detect or (Large)FaceList - Add
+         Face or (Large)PersonGroup - Add Face. The default value is
+         'detection_01', if another model is needed, please explicitly specify
+         it. Possible values include: 'detection_01', 'detection_02'
+        :type detection_model: str or
+         ~azure.cognitiveservices.vision.face.models.DetectionModel
         :param dict custom_headers: headers that will be added to the request
         :param bool raw: returns the direct response alongside the
          deserialized response
@@ -688,6 +767,8 @@ def add_face_from_stream(
             query_parameters['userData'] = self._serialize.query("user_data", user_data, 'str', max_length=1024)
         if target_face is not None:
             query_parameters['targetFace'] = self._serialize.query("target_face", target_face, '[int]', div=',')
+        if detection_model is not None:
+            query_parameters['detectionModel'] = self._serialize.query("detection_model", detection_model, 'str')
 
         # Construct headers
         header_parameters = {}