class Azure::CognitiveServices::Face::V1_0::LargePersonGroupPerson
An API for face detection, verification, and identification.
Attributes
@return [FaceClient] reference to the FaceClient
Private Class Methods
Creates and initializes a new instance of the LargePersonGroupPerson
class. @param client service class for accessing basic functionality.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 17 def initialize(client) @client = client end
Private Instance Methods
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](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 [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param image An image stream. @param user_data [String] User-specified data about the face for any purpose. The maximum length is 1KB. @param target_face [Array<Integer>] A face rectangle to specify the target face to be added to a person in the format of “targetFace=left,top,width,height”. E.g. “targetFace=10,10,100,100”. If there is more than one face in the image, targetFace is required to specify which face to add. No targetFace means there is only one face detected in the entire image. @param detection_model [DetectionModel] 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' @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [PersistedFace] operation results.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 1255 def add_face_from_stream(large_person_group_id, person_id, image, user_data:nil, target_face:nil, detection_model:nil, custom_headers:nil) response = add_face_from_stream_async(large_person_group_id, person_id, image, user_data:user_data, target_face:target_face, detection_model:detection_model, custom_headers:custom_headers).value! response.body unless response.nil? end
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](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 [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param image An image stream. @param user_data [String] User-specified data about the face for any purpose. The maximum length is 1KB. @param target_face [Array<Integer>] A face rectangle to specify the target face to be added to a person in the format of “targetFace=left,top,width,height”. E.g. “targetFace=10,10,100,100”. If there is more than one face in the image, targetFace is required to specify which face to add. No targetFace means there is only one face detected in the entire image. @param detection_model [DetectionModel] 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' @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 1404 def add_face_from_stream_async(large_person_group_id, person_id, image, user_data:nil, target_face:nil, detection_model:nil, custom_headers:nil) fail ArgumentError, '@client.endpoint is nil' if @client.endpoint.nil? fail ArgumentError, 'large_person_group_id is nil' if large_person_group_id.nil? fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'MaxLength': '64'" if !large_person_group_id.nil? && large_person_group_id.length > 64 fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'Pattern': '^[a-z0-9-_]+$'" if !large_person_group_id.nil? && large_person_group_id.match(Regexp.new('^^[a-z0-9-_]+$$')).nil? fail ArgumentError, 'person_id is nil' if person_id.nil? fail ArgumentError, "'user_data' should satisfy the constraint - 'MaxLength': '1024'" if !user_data.nil? && user_data.length > 1024 fail ArgumentError, 'image is nil' if image.nil? request_headers = {} request_headers['Content-Type'] = 'application/octet-stream' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? # Serialize Request request_mapper = { client_side_validation: true, required: true, serialized_name: 'Image', type: { name: 'Stream' } } request_content = @client.serialize(request_mapper, image) path_template = 'largepersongroups/{largePersonGroupId}/persons/{personId}/persistedfaces' request_url = @base_url || @client.base_url request_url = request_url.gsub('{Endpoint}', @client.endpoint) options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'largePersonGroupId' => large_person_group_id,'personId' => person_id}, query_params: {'userData' => user_data,'targetFace' => target_face.nil? ? nil : target_face.join(','),'detectionModel' => detection_model}, body: request_content, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:post, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRest::HttpOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? # Deserialize Response if status_code == 200 begin parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content) result_mapper = Azure::CognitiveServices::Face::V1_0::Models::PersistedFace.mapper() result.body = @client.deserialize(result_mapper, parsed_response) rescue Exception => e fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result) end end result end promise.execute end
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](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 [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param image An image stream. @param user_data [String] User-specified data about the face for any purpose. The maximum length is 1KB. @param target_face [Array<Integer>] A face rectangle to specify the target face to be added to a person in the format of “targetFace=left,top,width,height”. E.g. “targetFace=10,10,100,100”. If there is more than one face in the image, targetFace is required to specify which face to add. No targetFace means there is only one face detected in the entire image. @param detection_model [DetectionModel] 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' @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 1330 def add_face_from_stream_with_http_info(large_person_group_id, person_id, image, user_data:nil, target_face:nil, detection_model:nil, custom_headers:nil) add_face_from_stream_async(large_person_group_id, person_id, image, user_data:user_data, target_face:target_face, detection_model:detection_model, custom_headers:custom_headers).value! end
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](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 [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param url [String] Publicly reachable URL of an image @param user_data [String] User-specified data about the face for any purpose. The maximum length is 1KB. @param target_face [Array<Integer>] A face rectangle to specify the target face to be added to a person in the format of “targetFace=left,top,width,height”. E.g. “targetFace=10,10,100,100”. If there is more than one face in the image, targetFace is required to specify which face to add. No targetFace means there is only one face detected in the entire image. @param detection_model [DetectionModel] 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' @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [PersistedFace] operation results.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 966 def add_face_from_url(large_person_group_id, person_id, url, user_data:nil, target_face:nil, detection_model:nil, custom_headers:nil) response = add_face_from_url_async(large_person_group_id, person_id, url, user_data:user_data, target_face:target_face, detection_model:detection_model, custom_headers:custom_headers).value! response.body unless response.nil? end
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](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 [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param url [String] Publicly reachable URL of an image @param user_data [String] User-specified data about the face for any purpose. The maximum length is 1KB. @param target_face [Array<Integer>] A face rectangle to specify the target face to be added to a person in the format of “targetFace=left,top,width,height”. E.g. “targetFace=10,10,100,100”. If there is more than one face in the image, targetFace is required to specify which face to add. No targetFace means there is only one face detected in the entire image. @param detection_model [DetectionModel] 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' @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 1115 def add_face_from_url_async(large_person_group_id, person_id, url, user_data:nil, target_face:nil, detection_model:nil, custom_headers:nil) fail ArgumentError, '@client.endpoint is nil' if @client.endpoint.nil? fail ArgumentError, 'large_person_group_id is nil' if large_person_group_id.nil? fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'MaxLength': '64'" if !large_person_group_id.nil? && large_person_group_id.length > 64 fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'Pattern': '^[a-z0-9-_]+$'" if !large_person_group_id.nil? && large_person_group_id.match(Regexp.new('^^[a-z0-9-_]+$$')).nil? fail ArgumentError, 'person_id is nil' if person_id.nil? fail ArgumentError, "'user_data' should satisfy the constraint - 'MaxLength': '1024'" if !user_data.nil? && user_data.length > 1024 fail ArgumentError, 'url is nil' if url.nil? image_url = ImageUrl.new unless url.nil? image_url.url = url end request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? # Serialize Request request_mapper = Azure::CognitiveServices::Face::V1_0::Models::ImageUrl.mapper() request_content = @client.serialize(request_mapper, image_url) request_content = request_content != nil ? JSON.generate(request_content, quirks_mode: true) : nil path_template = 'largepersongroups/{largePersonGroupId}/persons/{personId}/persistedfaces' request_url = @base_url || @client.base_url request_url = request_url.gsub('{Endpoint}', @client.endpoint) options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'largePersonGroupId' => large_person_group_id,'personId' => person_id}, query_params: {'userData' => user_data,'targetFace' => target_face.nil? ? nil : target_face.join(','),'detectionModel' => detection_model}, body: request_content, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:post, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRest::HttpOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? # Deserialize Response if status_code == 200 begin parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content) result_mapper = Azure::CognitiveServices::Face::V1_0::Models::PersistedFace.mapper() result.body = @client.deserialize(result_mapper, parsed_response) rescue Exception => e fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result) end end result end promise.execute end
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](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 [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param url [String] Publicly reachable URL of an image @param user_data [String] User-specified data about the face for any purpose. The maximum length is 1KB. @param target_face [Array<Integer>] A face rectangle to specify the target face to be added to a person in the format of “targetFace=left,top,width,height”. E.g. “targetFace=10,10,100,100”. If there is more than one face in the image, targetFace is required to specify which face to add. No targetFace means there is only one face detected in the entire image. @param detection_model [DetectionModel] 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' @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 1041 def add_face_from_url_with_http_info(large_person_group_id, person_id, url, user_data:nil, target_face:nil, detection_model:nil, custom_headers:nil) add_face_from_url_async(large_person_group_id, person_id, url, user_data:user_data, target_face:target_face, detection_model:detection_model, custom_headers:custom_headers).value! end
Create a new person in a specified large person group.
@param large_person_group_id [String] Id referencing a particular large person group. @param name [String] User defined name, maximum length is 128. @param user_data [String] User specified data. Length should not exceed 16KB. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Person] operation results.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 36 def create(large_person_group_id, name:nil, user_data:nil, custom_headers:nil) response = create_async(large_person_group_id, name:name, user_data:user_data, custom_headers:custom_headers).value! response.body unless response.nil? end
Create a new person in a specified large person group.
@param large_person_group_id [String] Id referencing a particular large person group. @param name [String] User defined name, maximum length is 128. @param user_data [String] User specified data. Length should not exceed 16KB. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 69 def create_async(large_person_group_id, name:nil, user_data:nil, custom_headers:nil) fail ArgumentError, '@client.endpoint is nil' if @client.endpoint.nil? fail ArgumentError, 'large_person_group_id is nil' if large_person_group_id.nil? fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'MaxLength': '64'" if !large_person_group_id.nil? && large_person_group_id.length > 64 fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'Pattern': '^[a-z0-9-_]+$'" if !large_person_group_id.nil? && large_person_group_id.match(Regexp.new('^^[a-z0-9-_]+$$')).nil? fail ArgumentError, "'name' should satisfy the constraint - 'MaxLength': '128'" if !name.nil? && name.length > 128 fail ArgumentError, "'user_data' should satisfy the constraint - 'MaxLength': '16384'" if !user_data.nil? && user_data.length > 16384 body = NameAndUserDataContract.new unless name.nil? && user_data.nil? body.name = name body.user_data = user_data end request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? # Serialize Request request_mapper = Azure::CognitiveServices::Face::V1_0::Models::NameAndUserDataContract.mapper() request_content = @client.serialize(request_mapper, body) request_content = request_content != nil ? JSON.generate(request_content, quirks_mode: true) : nil path_template = 'largepersongroups/{largePersonGroupId}/persons' request_url = @base_url || @client.base_url request_url = request_url.gsub('{Endpoint}', @client.endpoint) options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'largePersonGroupId' => large_person_group_id}, body: request_content, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:post, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRest::HttpOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? # Deserialize Response if status_code == 200 begin parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content) result_mapper = Azure::CognitiveServices::Face::V1_0::Models::Person.mapper() result.body = @client.deserialize(result_mapper, parsed_response) rescue Exception => e fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result) end end result end promise.execute end
Create a new person in a specified large person group.
@param large_person_group_id [String] Id referencing a particular large person group. @param name [String] User defined name, maximum length is 128. @param user_data [String] User specified data. Length should not exceed 16KB. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 53 def create_with_http_info(large_person_group_id, name:nil, user_data:nil, custom_headers:nil) create_async(large_person_group_id, name:name, user_data:user_data, custom_headers:custom_headers).value! end
Delete an existing person from a large person group. The persistedFaceId, userData, person name and face feature in the person entry will all be deleted.
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 281 def delete(large_person_group_id, person_id, custom_headers:nil) response = delete_async(large_person_group_id, person_id, custom_headers:custom_headers).value! nil end
Delete an existing person from a large person group. The persistedFaceId, userData, person name and face feature in the person entry will all be deleted.
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 316 def delete_async(large_person_group_id, person_id, custom_headers:nil) fail ArgumentError, '@client.endpoint is nil' if @client.endpoint.nil? fail ArgumentError, 'large_person_group_id is nil' if large_person_group_id.nil? fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'MaxLength': '64'" if !large_person_group_id.nil? && large_person_group_id.length > 64 fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'Pattern': '^[a-z0-9-_]+$'" if !large_person_group_id.nil? && large_person_group_id.match(Regexp.new('^^[a-z0-9-_]+$$')).nil? fail ArgumentError, 'person_id is nil' if person_id.nil? request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? path_template = 'largepersongroups/{largePersonGroupId}/persons/{personId}' request_url = @base_url || @client.base_url request_url = request_url.gsub('{Endpoint}', @client.endpoint) options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'largePersonGroupId' => large_person_group_id,'personId' => person_id}, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:delete, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRestAzure::AzureOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? result end promise.execute end
Delete a face from a person in a large person group by specified largePersonGroupId, personId and persistedFaceId. <br /> Adding/deleting faces to/from a same person will be processed sequentially. Adding/deleting faces to/from different persons are processed in parallel.
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param persisted_face_id Id referencing a particular persistedFaceId of an existing face. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 586 def delete_face(large_person_group_id, person_id, persisted_face_id, custom_headers:nil) response = delete_face_async(large_person_group_id, person_id, persisted_face_id, custom_headers:custom_headers).value! nil end
Delete a face from a person in a large person group by specified largePersonGroupId, personId and persistedFaceId. <br /> Adding/deleting faces to/from a same person will be processed sequentially. Adding/deleting faces to/from different persons are processed in parallel.
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param persisted_face_id Id referencing a particular persistedFaceId of an existing face. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 629 def delete_face_async(large_person_group_id, person_id, persisted_face_id, custom_headers:nil) fail ArgumentError, '@client.endpoint is nil' if @client.endpoint.nil? fail ArgumentError, 'large_person_group_id is nil' if large_person_group_id.nil? fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'MaxLength': '64'" if !large_person_group_id.nil? && large_person_group_id.length > 64 fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'Pattern': '^[a-z0-9-_]+$'" if !large_person_group_id.nil? && large_person_group_id.match(Regexp.new('^^[a-z0-9-_]+$$')).nil? fail ArgumentError, 'person_id is nil' if person_id.nil? fail ArgumentError, 'persisted_face_id is nil' if persisted_face_id.nil? request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? path_template = 'largepersongroups/{largePersonGroupId}/persons/{personId}/persistedfaces/{persistedFaceId}' request_url = @base_url || @client.base_url request_url = request_url.gsub('{Endpoint}', @client.endpoint) options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'largePersonGroupId' => large_person_group_id,'personId' => person_id,'persistedFaceId' => persisted_face_id}, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:delete, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRestAzure::AzureOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? result end promise.execute end
Delete a face from a person in a large person group by specified largePersonGroupId, personId and persistedFaceId. <br /> Adding/deleting faces to/from a same person will be processed sequentially. Adding/deleting faces to/from different persons are processed in parallel.
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param persisted_face_id Id referencing a particular persistedFaceId of an existing face. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 608 def delete_face_with_http_info(large_person_group_id, person_id, persisted_face_id, custom_headers:nil) delete_face_async(large_person_group_id, person_id, persisted_face_id, custom_headers:custom_headers).value! end
Delete an existing person from a large person group. The persistedFaceId, userData, person name and face feature in the person entry will all be deleted.
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 299 def delete_with_http_info(large_person_group_id, person_id, custom_headers:nil) delete_async(large_person_group_id, person_id, custom_headers:custom_headers).value! end
Retrieve a person's name and userData, and the persisted faceIds representing the registered person face feature.
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Person] operation results.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 374 def get(large_person_group_id, person_id, custom_headers:nil) response = get_async(large_person_group_id, person_id, custom_headers:custom_headers).value! response.body unless response.nil? end
Retrieve a person's name and userData, and the persisted faceIds representing the registered person face feature.
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 407 def get_async(large_person_group_id, person_id, custom_headers:nil) fail ArgumentError, '@client.endpoint is nil' if @client.endpoint.nil? fail ArgumentError, 'large_person_group_id is nil' if large_person_group_id.nil? fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'MaxLength': '64'" if !large_person_group_id.nil? && large_person_group_id.length > 64 fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'Pattern': '^[a-z0-9-_]+$'" if !large_person_group_id.nil? && large_person_group_id.match(Regexp.new('^^[a-z0-9-_]+$$')).nil? fail ArgumentError, 'person_id is nil' if person_id.nil? request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? path_template = 'largepersongroups/{largePersonGroupId}/persons/{personId}' request_url = @base_url || @client.base_url request_url = request_url.gsub('{Endpoint}', @client.endpoint) options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'largePersonGroupId' => large_person_group_id,'personId' => person_id}, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:get, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRest::HttpOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? # Deserialize Response if status_code == 200 begin parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content) result_mapper = Azure::CognitiveServices::Face::V1_0::Models::Person.mapper() result.body = @client.deserialize(result_mapper, parsed_response) rescue Exception => e fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result) end end result end promise.execute end
Retrieve information about a persisted face (specified by persistedFaceId, personId and its belonging largePersonGroupId).
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param persisted_face_id Id referencing a particular persistedFaceId of an existing face. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [PersistedFace] operation results.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 690 def get_face(large_person_group_id, person_id, persisted_face_id, custom_headers:nil) response = get_face_async(large_person_group_id, person_id, persisted_face_id, custom_headers:custom_headers).value! response.body unless response.nil? end
Retrieve information about a persisted face (specified by persistedFaceId, personId and its belonging largePersonGroupId).
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param persisted_face_id Id referencing a particular persistedFaceId of an existing face. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 727 def get_face_async(large_person_group_id, person_id, persisted_face_id, custom_headers:nil) fail ArgumentError, '@client.endpoint is nil' if @client.endpoint.nil? fail ArgumentError, 'large_person_group_id is nil' if large_person_group_id.nil? fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'MaxLength': '64'" if !large_person_group_id.nil? && large_person_group_id.length > 64 fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'Pattern': '^[a-z0-9-_]+$'" if !large_person_group_id.nil? && large_person_group_id.match(Regexp.new('^^[a-z0-9-_]+$$')).nil? fail ArgumentError, 'person_id is nil' if person_id.nil? fail ArgumentError, 'persisted_face_id is nil' if persisted_face_id.nil? request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? path_template = 'largepersongroups/{largePersonGroupId}/persons/{personId}/persistedfaces/{persistedFaceId}' request_url = @base_url || @client.base_url request_url = request_url.gsub('{Endpoint}', @client.endpoint) options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'largePersonGroupId' => large_person_group_id,'personId' => person_id,'persistedFaceId' => persisted_face_id}, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:get, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRest::HttpOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? # Deserialize Response if status_code == 200 begin parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content) result_mapper = Azure::CognitiveServices::Face::V1_0::Models::PersistedFace.mapper() result.body = @client.deserialize(result_mapper, parsed_response) rescue Exception => e fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result) end end result end promise.execute end
Retrieve information about a persisted face (specified by persistedFaceId, personId and its belonging largePersonGroupId).
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param persisted_face_id Id referencing a particular persistedFaceId of an existing face. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 709 def get_face_with_http_info(large_person_group_id, person_id, persisted_face_id, custom_headers:nil) get_face_async(large_person_group_id, person_id, persisted_face_id, custom_headers:custom_headers).value! end
Retrieve a person's name and userData, and the persisted faceIds representing the registered person face feature.
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 391 def get_with_http_info(large_person_group_id, person_id, custom_headers:nil) get_async(large_person_group_id, person_id, custom_headers:custom_headers).value! end
List all persons in a large person group, and retrieve person information (including personId, name, userData and persistedFaceIds of registered faces of the person).
@param large_person_group_id [String] Id referencing a particular large person group. @param start [String] Starting person id to return (used to list a range of persons). @param top [Integer] Number of persons to return starting with the person id indicated by the 'start' parameter. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Array] operation results.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 154 def list(large_person_group_id, start:nil, top:nil, custom_headers:nil) response = list_async(large_person_group_id, start:start, top:top, custom_headers:custom_headers).value! response.body unless response.nil? end
List all persons in a large person group, and retrieve person information (including personId, name, userData and persistedFaceIds of registered faces of the person).
@param large_person_group_id [String] Id referencing a particular large person group. @param start [String] Starting person id to return (used to list a range of persons). @param top [Integer] Number of persons to return starting with the person id indicated by the 'start' parameter. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 195 def list_async(large_person_group_id, start:nil, top:nil, custom_headers:nil) fail ArgumentError, '@client.endpoint is nil' if @client.endpoint.nil? fail ArgumentError, 'large_person_group_id is nil' if large_person_group_id.nil? fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'MaxLength': '64'" if !large_person_group_id.nil? && large_person_group_id.length > 64 fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'Pattern': '^[a-z0-9-_]+$'" if !large_person_group_id.nil? && large_person_group_id.match(Regexp.new('^^[a-z0-9-_]+$$')).nil? fail ArgumentError, "'top' should satisfy the constraint - 'InclusiveMaximum': '1000'" if !top.nil? && top > 1000 fail ArgumentError, "'top' should satisfy the constraint - 'InclusiveMinimum': '1'" if !top.nil? && top < 1 request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? path_template = 'largepersongroups/{largePersonGroupId}/persons' request_url = @base_url || @client.base_url request_url = request_url.gsub('{Endpoint}', @client.endpoint) options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'largePersonGroupId' => large_person_group_id}, query_params: {'start' => start,'top' => top}, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:get, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRest::HttpOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? # Deserialize Response if status_code == 200 begin parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content) result_mapper = { client_side_validation: true, required: false, serialized_name: 'parsed_response', type: { name: 'Sequence', element: { client_side_validation: true, required: false, serialized_name: 'PersonElementType', type: { name: 'Composite', class_name: 'Person' } } } } result.body = @client.deserialize(result_mapper, parsed_response) rescue Exception => e fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result) end end result end promise.execute end
List all persons in a large person group, and retrieve person information (including personId, name, userData and persistedFaceIds of registered faces of the person).
@param large_person_group_id [String] Id referencing a particular large person group. @param start [String] Starting person id to return (used to list a range of persons). @param top [Integer] Number of persons to return starting with the person id indicated by the 'start' parameter. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 175 def list_with_http_info(large_person_group_id, start:nil, top:nil, custom_headers:nil) list_async(large_person_group_id, start:start, top:top, custom_headers:custom_headers).value! end
Update name or userData of a person.
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param name [String] User defined name, maximum length is 128. @param user_data [String] User specified data. Length should not exceed 16KB. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 475 def update(large_person_group_id, person_id, name:nil, user_data:nil, custom_headers:nil) response = update_async(large_person_group_id, person_id, name:name, user_data:user_data, custom_headers:custom_headers).value! nil end
Update name or userData of a person.
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param name [String] User defined name, maximum length is 128. @param user_data [String] User specified data. Length should not exceed 16KB. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 510 def update_async(large_person_group_id, person_id, name:nil, user_data:nil, custom_headers:nil) fail ArgumentError, '@client.endpoint is nil' if @client.endpoint.nil? fail ArgumentError, 'large_person_group_id is nil' if large_person_group_id.nil? fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'MaxLength': '64'" if !large_person_group_id.nil? && large_person_group_id.length > 64 fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'Pattern': '^[a-z0-9-_]+$'" if !large_person_group_id.nil? && large_person_group_id.match(Regexp.new('^^[a-z0-9-_]+$$')).nil? fail ArgumentError, 'person_id is nil' if person_id.nil? fail ArgumentError, "'name' should satisfy the constraint - 'MaxLength': '128'" if !name.nil? && name.length > 128 fail ArgumentError, "'user_data' should satisfy the constraint - 'MaxLength': '16384'" if !user_data.nil? && user_data.length > 16384 body = NameAndUserDataContract.new unless name.nil? && user_data.nil? body.name = name body.user_data = user_data end request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? # Serialize Request request_mapper = Azure::CognitiveServices::Face::V1_0::Models::NameAndUserDataContract.mapper() request_content = @client.serialize(request_mapper, body) request_content = request_content != nil ? JSON.generate(request_content, quirks_mode: true) : nil path_template = 'largepersongroups/{largePersonGroupId}/persons/{personId}' request_url = @base_url || @client.base_url request_url = request_url.gsub('{Endpoint}', @client.endpoint) options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'largePersonGroupId' => large_person_group_id,'personId' => person_id}, body: request_content, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:patch, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRestAzure::AzureOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? result end promise.execute end
Update a person persisted face's userData field.
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param persisted_face_id Id referencing a particular persistedFaceId of an existing face. @param user_data [String] User-provided data attached to the face. The size limit is 1KB. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 798 def update_face(large_person_group_id, person_id, persisted_face_id, user_data:nil, custom_headers:nil) response = update_face_async(large_person_group_id, person_id, persisted_face_id, user_data:user_data, custom_headers:custom_headers).value! nil end
Update a person persisted face's userData field.
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param persisted_face_id Id referencing a particular persistedFaceId of an existing face. @param user_data [String] User-provided data attached to the face. The size limit is 1KB. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 837 def update_face_async(large_person_group_id, person_id, persisted_face_id, user_data:nil, custom_headers:nil) fail ArgumentError, '@client.endpoint is nil' if @client.endpoint.nil? fail ArgumentError, 'large_person_group_id is nil' if large_person_group_id.nil? fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'MaxLength': '64'" if !large_person_group_id.nil? && large_person_group_id.length > 64 fail ArgumentError, "'large_person_group_id' should satisfy the constraint - 'Pattern': '^[a-z0-9-_]+$'" if !large_person_group_id.nil? && large_person_group_id.match(Regexp.new('^^[a-z0-9-_]+$$')).nil? fail ArgumentError, 'person_id is nil' if person_id.nil? fail ArgumentError, 'persisted_face_id is nil' if persisted_face_id.nil? fail ArgumentError, "'user_data' should satisfy the constraint - 'MaxLength': '1024'" if !user_data.nil? && user_data.length > 1024 body = UpdateFaceRequest.new unless user_data.nil? body.user_data = user_data end request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? # Serialize Request request_mapper = Azure::CognitiveServices::Face::V1_0::Models::UpdateFaceRequest.mapper() request_content = @client.serialize(request_mapper, body) request_content = request_content != nil ? JSON.generate(request_content, quirks_mode: true) : nil path_template = 'largepersongroups/{largePersonGroupId}/persons/{personId}/persistedfaces/{persistedFaceId}' request_url = @base_url || @client.base_url request_url = request_url.gsub('{Endpoint}', @client.endpoint) options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'largePersonGroupId' => large_person_group_id,'personId' => person_id,'persistedFaceId' => persisted_face_id}, body: request_content, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:patch, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRestAzure::AzureOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? result end promise.execute end
Update a person persisted face's userData field.
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param persisted_face_id Id referencing a particular persistedFaceId of an existing face. @param user_data [String] User-provided data attached to the face. The size limit is 1KB. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 818 def update_face_with_http_info(large_person_group_id, person_id, persisted_face_id, user_data:nil, custom_headers:nil) update_face_async(large_person_group_id, person_id, persisted_face_id, user_data:user_data, custom_headers:custom_headers).value! end
Update name or userData of a person.
@param large_person_group_id [String] Id referencing a particular large person group. @param person_id Id referencing a particular person. @param name [String] User defined name, maximum length is 128. @param user_data [String] User specified data. Length should not exceed 16KB. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/1.0/generated/azure_cognitiveservices_face/large_person_group_person.rb, line 493 def update_with_http_info(large_person_group_id, person_id, name:nil, user_data:nil, custom_headers:nil) update_async(large_person_group_id, person_id, name:name, user_data:user_data, custom_headers:custom_headers).value! end