From 3c06e59699c87c744377ec668056b14d4e9da8c2 Mon Sep 17 00:00:00 2001 From: Long Li Date: Wed, 10 Jun 2020 15:12:12 -0700 Subject: [PATCH 1/2] Add definition and description about recognition_03 --- .../data-plane/Face/stable/v1.0/Face.json | 20 ++++++++++--------- 1 file changed, 11 insertions(+), 9 deletions(-) diff --git a/specification/cognitiveservices/data-plane/Face/stable/v1.0/Face.json b/specification/cognitiveservices/data-plane/Face/stable/v1.0/Face.json index c1ffa742a19a..98ea0a03c556 100644 --- a/specification/cognitiveservices/data-plane/Face/stable/v1.0/Face.json +++ b/specification/cognitiveservices/data-plane/Face/stable/v1.0/Face.json @@ -513,7 +513,7 @@ }, "/persongroups/{personGroupId}": { "put": { - "description": "Create a new person group with specified personGroupId, name, user-provided userData and recognitionModel.\n
A person group is the container of the uploaded person data, including face recognition features.\n
After creation, use [PersonGroup Person - Create](https://docs.microsoft.com/rest/api/cognitiveservices/face/persongroupperson/create) to add persons into the group, and then call [PersonGroup - Train](https://docs.microsoft.com/rest/api/cognitiveservices/face/persongroup/train) to get this group ready for [Face - Identify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/identify).\n
No image will be stored. Only the person's extracted face features and userData will be stored on server until [PersonGroup Person - Delete](https://docs.microsoft.com/rest/api/cognitiveservices/face/persongroupperson/delete) or [PersonGroup - Delete](https://docs.microsoft.com/rest/api/cognitiveservices/face/persongroup/delete) is called.\n
'recognitionModel' should be specified to associate with this person group. The default value for 'recognitionModel' is 'recognition_01', if the latest model needed, please explicitly specify the model you need in this parameter. New faces that are added to an existing person group will use the recognition model that's already associated with the collection. Existing face features in a person group can't be updated to features extracted by another version of recognition model.\n* 'recognition_01': The default recognition model for [PersonGroup - Create](https://docs.microsoft.com/rest/api/cognitiveservices/face/persongroup/create). All those person groups created before 2019 March are bonded with this recognition model.\n* 'recognition_02': Recognition model released in 2019 March. 'recognition_02' is recommended since its overall accuracy is improved compared with 'recognition_01'.\n\nPerson group quota:\n* Free-tier subscription quota: 1,000 person groups. Each holds up to 1,000 persons.\n* S0-tier subscription quota: 1,000,000 person groups. Each holds up to 10,000 persons.\n* to handle larger scale face identification problem, please consider using [LargePersonGroup](https://docs.microsoft.com/rest/api/cognitiveservices/face/largepersongroup).", + "description": "Create a new person group with specified personGroupId, name, user-provided userData and recognitionModel.\n
A person group is the container of the uploaded person data, including face recognition features.\n
After creation, use [PersonGroup Person - Create](https://docs.microsoft.com/rest/api/cognitiveservices/face/persongroupperson/create) to add persons into the group, and then call [PersonGroup - Train](https://docs.microsoft.com/rest/api/cognitiveservices/face/persongroup/train) to get this group ready for [Face - Identify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/identify).\n
No image will be stored. Only the person's extracted face features and userData will be stored on server until [PersonGroup Person - Delete](https://docs.microsoft.com/rest/api/cognitiveservices/face/persongroupperson/delete) or [PersonGroup - Delete](https://docs.microsoft.com/rest/api/cognitiveservices/face/persongroup/delete) is called.\n
'recognitionModel' should be specified to associate with this person group. The default value for 'recognitionModel' is 'recognition_01', if the latest model needed, please explicitly specify the model you need in this parameter. New faces that are added to an existing person group will use the recognition model that's already associated with the collection. Existing face features in a person group can't be updated to features extracted by another version of recognition model.\n* 'recognition_01': The default recognition model for [PersonGroup - Create](https://docs.microsoft.com/rest/api/cognitiveservices/face/persongroup/create). All those person groups created before 2019 March are bonded with this recognition model.\n* 'recognition_02': Recognition model released in 2019 March.\n* 'recognition_03': Recognition model released in 2020 May. 'recognition_03' is recommended since its overall accuracy is improved compared with 'recognition_01' and 'recognition_02'.\n\nPerson group quota:\n* Free-tier subscription quota: 1,000 person groups. Each holds up to 1,000 persons.\n* S0-tier subscription quota: 1,000,000 person groups. Each holds up to 10,000 persons.\n* to handle larger scale face identification problem, please consider using [LargePersonGroup](https://docs.microsoft.com/rest/api/cognitiveservices/face/largepersongroup).", "operationId": "PersonGroup_Create", "parameters": [ { @@ -764,7 +764,7 @@ }, "/facelists/{faceListId}": { "put": { - "description": "Create an empty face list with user-specified faceListId, name, an optional userData and recognitionModel. Up to 64 face lists are allowed in one subscription.\n
Face list is a list of faces, up to 1,000 faces, and used by [Face - Find Similar](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/findsimilar).\n
After creation, user should use [FaceList - Add Face](https://docs.microsoft.com/rest/api/cognitiveservices/face/facelist/addfacefromurl) to import the faces. No image will be stored. Only the extracted face features are stored on server until [FaceList - Delete](https://docs.microsoft.com/rest/api/cognitiveservices/face/facelist/delete) is called.\n
Find Similar is used for scenario like finding celebrity-like faces, similar face filtering, or as a light way face identification. But if the actual use is to identify person, please use [PersonGroup](https://docs.microsoft.com/rest/api/cognitiveservices/face/persongroup) / [LargePersonGroup](https://docs.microsoft.com/rest/api/cognitiveservices/face/largepersongroup) and [Face - Identify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/identify).\n
Please consider [LargeFaceList](https://docs.microsoft.com/rest/api/cognitiveservices/face/largefacelist) when the face number is large. It can support up to 1,000,000 faces.\n
'recognitionModel' should be specified to associate with this face list. The default value for 'recognitionModel' is 'recognition_01', if the latest model needed, please explicitly specify the model you need in this parameter. New faces that are added to an existing face list will use the recognition model that's already associated with the collection. Existing face features in a face list can't be updated to features extracted by another version of recognition model.\n* 'recognition_01': The default recognition model for [FaceList- Create](https://docs.microsoft.com/rest/api/cognitiveservices/face/facelist/create). All those face lists created before 2019 March are bonded with this recognition model.\n* 'recognition_02': Recognition model released in 2019 March. 'recognition_02' is recommended since its overall accuracy is improved compared with 'recognition_01'.", + "description": "Create an empty face list with user-specified faceListId, name, an optional userData and recognitionModel. Up to 64 face lists are allowed in one subscription.\n
Face list is a list of faces, up to 1,000 faces, and used by [Face - Find Similar](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/findsimilar).\n
After creation, user should use [FaceList - Add Face](https://docs.microsoft.com/rest/api/cognitiveservices/face/facelist/addfacefromurl) to import the faces. No image will be stored. Only the extracted face features are stored on server until [FaceList - Delete](https://docs.microsoft.com/rest/api/cognitiveservices/face/facelist/delete) is called.\n
Find Similar is used for scenario like finding celebrity-like faces, similar face filtering, or as a light way face identification. But if the actual use is to identify person, please use [PersonGroup](https://docs.microsoft.com/rest/api/cognitiveservices/face/persongroup) / [LargePersonGroup](https://docs.microsoft.com/rest/api/cognitiveservices/face/largepersongroup) and [Face - Identify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/identify).\n
Please consider [LargeFaceList](https://docs.microsoft.com/rest/api/cognitiveservices/face/largefacelist) when the face number is large. It can support up to 1,000,000 faces.\n
'recognitionModel' should be specified to associate with this face list. The default value for 'recognitionModel' is 'recognition_01', if the latest model needed, please explicitly specify the model you need in this parameter. New faces that are added to an existing face list will use the recognition model that's already associated with the collection. Existing face features in a face list can't be updated to features extracted by another version of recognition model.\n* 'recognition_01': The default recognition model for [FaceList- Create](https://docs.microsoft.com/rest/api/cognitiveservices/face/facelist/create). All those face lists created before 2019 March are bonded with this recognition model.\n* 'recognition_02': Recognition model released in 2019 March.\n* 'recognition_03': Recognition model released in 2020 May. 'recognition_03' is recommended since its overall accuracy is improved compared with 'recognition_01' and 'recognition_02'.", "operationId": "FaceList_Create", "parameters": [ { @@ -1018,7 +1018,7 @@ }, "/detect": { "post": { - "description": "Detect human faces in an image, return face rectangles, and optionally with faceIds, landmarks, and attributes.
\n* 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](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/identify), [Face - Verify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/verifyfacetoface), and [Face - Find Similar](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/findsimilar). The stored face feature(s) will expire and be deleted 24 hours after the original detection call.\n* 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.\n* JPEG, PNG, GIF (the first frame), and BMP format are supported. The allowed image file size is from 1KB to 6MB.\n* Up to 100 faces can be returned for an image. Faces are ranked by face rectangle size from large to small.\n* For optimal results when querying [Face - Identify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/identify), [Face - Verify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/verifyfacetoface), and [Face - Find Similar](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/findsimilar) ('returnFaceId' is true), please use faces that are: frontal, clear, and with a minimum size of 200x200 pixels (100 pixels between eyes).\n* 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.\n* 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/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model)\n | Model | Recommended use-case(s) |\n | ---------- | -------- |\n | 'detection_01': | The default detection model for [Face - Detect](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/detectwithurl). 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. |\n | 'detection_02': | Detection model released in 2019 May with improved accuracy especially on small, side and blurry faces. |\n\n* 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/azure/cognitive-services/face/face-api-how-to-topics/specify-recognition-model)\n | Model | Recommended use-case(s) |\n | ---------- | -------- |\n | 'recognition_01': | The default recognition model for [Face - Detect](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/detectwithurl). All those faceIds created before 2019 March are bonded with this recognition model. |\n | 'recognition_02': | Recognition model released in 2019 March. 'recognition_02' is recommended since its overall accuracy is improved compared with 'recognition_01'. |", + "description": "Detect human faces in an image, return face rectangles, and optionally with faceIds, landmarks, and attributes.
\n* 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](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/identify), [Face - Verify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/verifyfacetoface), and [Face - Find Similar](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/findsimilar). The stored face feature(s) will expire and be deleted 24 hours after the original detection call.\n* 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.\n* JPEG, PNG, GIF (the first frame), and BMP format are supported. The allowed image file size is from 1KB to 6MB.\n* Up to 100 faces can be returned for an image. Faces are ranked by face rectangle size from large to small.\n* For optimal results when querying [Face - Identify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/identify), [Face - Verify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/verifyfacetoface), and [Face - Find Similar](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/findsimilar) ('returnFaceId' is true), please use faces that are: frontal, clear, and with a minimum size of 200x200 pixels (100 pixels between eyes).\n* 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.\n* 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/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model)\n | Model | Recommended use-case(s) |\n | ---------- | -------- |\n | 'detection_01': | The default detection model for [Face - Detect](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/detectwithurl). 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. |\n | 'detection_02': | Detection model released in 2019 May with improved accuracy especially on small, side and blurry faces. |\n\n* 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/azure/cognitive-services/face/face-api-how-to-topics/specify-recognition-model)\n | Model | Recommended use-case(s) |\n | ---------- | -------- |\n | 'recognition_01': | The default recognition model for [Face - Detect](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/detectwithurl). All those faceIds created before 2019 March are bonded with this recognition model. |\n | 'recognition_02': | Recognition model released in 2019 March. |\n | 'recognition_03': | Recognition model released in 2020 May. 'recognition_03' is recommended since its overall accuracy is improved compared with 'recognition_01' and 'recognition_02'. |", "operationId": "Face_DetectWithUrl", "parameters": [ { @@ -1440,7 +1440,7 @@ }, "/largepersongroups/{largePersonGroupId}": { "put": { - "description": "Create a new large person group with user-specified largePersonGroupId, name, an optional userData and recognitionModel.\n
A large person group is the container of the uploaded person data, including face recognition feature, and up to 1,000,000\npeople.\n
After creation, use [LargePersonGroup Person - Create](https://docs.microsoft.com/rest/api/cognitiveservices/face/largepersongroupperson/create) to add person into the group, and call [LargePersonGroup - Train](https://docs.microsoft.com/rest/api/cognitiveservices/face/largepersongroup/train) to get this group ready for [Face - Identify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/identify).\n
No image will be stored. Only the person's extracted face features and userData will be stored on server until [LargePersonGroup Person - Delete](https://docs.microsoft.com/rest/api/cognitiveservices/face/largepersongroupperson/delete) or [LargePersonGroup - Delete](https://docs.microsoft.com/rest/api/cognitiveservices/face/largepersongroup/delete) is called.\n
'recognitionModel' should be specified to associate with this large person group. The default value for 'recognitionModel' is 'recognition_01', if the latest model needed, please explicitly specify the model you need in this parameter. New faces that are added to an existing large person group will use the recognition model that's already associated with the collection. Existing face features in a large person group can't be updated to features extracted by another version of recognition model.\n* 'recognition_01': The default recognition model for [LargePersonGroup - Create](https://docs.microsoft.com/rest/api/cognitiveservices/face/largepersongroup/create). All those large person groups created before 2019 March are bonded with this recognition model.\n* 'recognition_02': Recognition model released in 2019 March. 'recognition_02' is recommended since its overall accuracy is improved compared with 'recognition_01'.\n\nLarge person group quota:\n* Free-tier subscription quota: 1,000 large person groups.\n* S0-tier subscription quota: 1,000,000 large person groups.", + "description": "Create a new large person group with user-specified largePersonGroupId, name, an optional userData and recognitionModel.\n
A large person group is the container of the uploaded person data, including face recognition feature, and up to 1,000,000\npeople.\n
After creation, use [LargePersonGroup Person - Create](https://docs.microsoft.com/rest/api/cognitiveservices/face/largepersongroupperson/create) to add person into the group, and call [LargePersonGroup - Train](https://docs.microsoft.com/rest/api/cognitiveservices/face/largepersongroup/train) to get this group ready for [Face - Identify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/identify).\n
No image will be stored. Only the person's extracted face features and userData will be stored on server until [LargePersonGroup Person - Delete](https://docs.microsoft.com/rest/api/cognitiveservices/face/largepersongroupperson/delete) or [LargePersonGroup - Delete](https://docs.microsoft.com/rest/api/cognitiveservices/face/largepersongroup/delete) is called.\n
'recognitionModel' should be specified to associate with this large person group. The default value for 'recognitionModel' is 'recognition_01', if the latest model needed, please explicitly specify the model you need in this parameter. New faces that are added to an existing large person group will use the recognition model that's already associated with the collection. Existing face features in a large person group can't be updated to features extracted by another version of recognition model.\n* 'recognition_01': The default recognition model for [LargePersonGroup - Create](https://docs.microsoft.com/rest/api/cognitiveservices/face/largepersongroup/create). All those large person groups created before 2019 March are bonded with this recognition model.\n* 'recognition_02': Recognition model released in 2019 March.\n* 'recognition_03': Recognition model released in 2020 May. 'recognition_03' is recommended since its overall accuracy is improved compared with 'recognition_01' and 'recognition_02'.\n\nLarge person group quota:\n* Free-tier subscription quota: 1,000 large person groups.\n* S0-tier subscription quota: 1,000,000 large person groups.", "operationId": "LargePersonGroup_Create", "parameters": [ { @@ -1742,7 +1742,7 @@ }, "/largefacelists/{largeFaceListId}": { "put": { - "description": "Create an empty large face list with user-specified largeFaceListId, name, an optional userData and recognitionModel.\n
Large face list is a list of faces, up to 1,000,000 faces, and used by [Face - Find Similar](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/findsimilar).\n
After creation, user should use [LargeFaceList Face - Add](https://docs.microsoft.com/rest/api/cognitiveservices/face/largefacelist/addfacefromurl) to import the faces and [LargeFaceList - Train](https://docs.microsoft.com/rest/api/cognitiveservices/face/largefacelist/train) to make it ready for [Face - Find Similar](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/findsimilar). No image will be stored. Only the extracted face features are stored on server until [LargeFaceList - Delete](https://docs.microsoft.com/rest/api/cognitiveservices/face/largefacelist/delete) is called.\n
Find Similar is used for scenario like finding celebrity-like faces, similar face filtering, or as a light way face identification. But if the actual use is to identify person, please use [PersonGroup](https://docs.microsoft.com/rest/api/cognitiveservices/face/persongroup) / [LargePersonGroup](https://docs.microsoft.com/rest/api/cognitiveservices/face/largepersongroup) and [Face - Identify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/identify).\n
'recognitionModel' should be specified to associate with this large face list. The default value for 'recognitionModel' is 'recognition_01', if the latest model needed, please explicitly specify the model you need in this parameter. New faces that are added to an existing large face list will use the recognition model that's already associated with the collection. Existing face features in a large face list can't be updated to features extracted by another version of recognition model.\n* 'recognition_01': The default recognition model for [LargeFaceList- Create](https://docs.microsoft.com/rest/api/cognitiveservices/face/largefacelist/create). All those large face lists created before 2019 March are bonded with this recognition model.\n* 'recognition_02': Recognition model released in 2019 March. 'recognition_02' is recommended since its overall accuracy is improved compared with 'recognition_01'.\n\nLarge face list quota:\n* Free-tier subscription quota: 64 large face lists.\n* S0-tier subscription quota: 1,000,000 large face lists.", + "description": "Create an empty large face list with user-specified largeFaceListId, name, an optional userData and recognitionModel.\n
Large face list is a list of faces, up to 1,000,000 faces, and used by [Face - Find Similar](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/findsimilar).\n
After creation, user should use [LargeFaceList Face - Add](https://docs.microsoft.com/rest/api/cognitiveservices/face/largefacelist/addfacefromurl) to import the faces and [LargeFaceList - Train](https://docs.microsoft.com/rest/api/cognitiveservices/face/largefacelist/train) to make it ready for [Face - Find Similar](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/findsimilar). No image will be stored. Only the extracted face features are stored on server until [LargeFaceList - Delete](https://docs.microsoft.com/rest/api/cognitiveservices/face/largefacelist/delete) is called.\n
Find Similar is used for scenario like finding celebrity-like faces, similar face filtering, or as a light way face identification. But if the actual use is to identify person, please use [PersonGroup](https://docs.microsoft.com/rest/api/cognitiveservices/face/persongroup) / [LargePersonGroup](https://docs.microsoft.com/rest/api/cognitiveservices/face/largepersongroup) and [Face - Identify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/identify).\n
'recognitionModel' should be specified to associate with this large face list. The default value for 'recognitionModel' is 'recognition_01', if the latest model needed, please explicitly specify the model you need in this parameter. New faces that are added to an existing large face list will use the recognition model that's already associated with the collection. Existing face features in a large face list can't be updated to features extracted by another version of recognition model.\n* 'recognition_01': The default recognition model for [LargeFaceList- Create](https://docs.microsoft.com/rest/api/cognitiveservices/face/largefacelist/create). All those large face lists created before 2019 March are bonded with this recognition model.\n* 'recognition_02': Recognition model released in 2019 March.\n* 'recognition_03': Recognition model released in 2020 May. 'recognition_03' is recommended since its overall accuracy is improved compared with 'recognition_01' and 'recognition_02'.\n\nLarge face list quota:\n* Free-tier subscription quota: 64 large face lists.\n* S0-tier subscription quota: 1,000,000 large face lists.", "operationId": "LargeFaceList_Create", "parameters": [ { @@ -2495,7 +2495,7 @@ }, "/detect?overload=stream": { "post": { - "description": "Detect human faces in an image, return face rectangles, and optionally with faceIds, landmarks, and attributes.
\n* 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](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/identify), [Face - Verify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/verifyfacetoface), and [Face - Find Similar](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/findsimilar). The stored face feature(s) will expire and be deleted 24 hours after the original detection call.\n* 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.\n* JPEG, PNG, GIF (the first frame), and BMP format are supported. The allowed image file size is from 1KB to 6MB.\n* Up to 100 faces can be returned for an image. Faces are ranked by face rectangle size from large to small.\n* For optimal results when querying [Face - Identify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/identify), [Face - Verify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/verifyfacetoface), and [Face - Find Similar](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/findsimilar) ('returnFaceId' is true), please use faces that are: frontal, clear, and with a minimum size of 200x200 pixels (100 pixels between eyes).\n* 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.\n* 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/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model)\n | Model | Recommended use-case(s) |\n | ---------- | -------- |\n | 'detection_01': | The default detection model for [Face - Detect](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/detectwithurl). 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. |\n | 'detection_02': | Detection model released in 2019 May with improved accuracy especially on small, side and blurry faces. |\n\n* 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/azure/cognitive-services/face/face-api-how-to-topics/specify-recognition-model)\n | Model | Recommended use-case(s) |\n | ---------- | -------- |\n | 'recognition_01': | The default recognition model for [Face - Detect](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/detectwithurl). All those faceIds created before 2019 March are bonded with this recognition model. |\n | 'recognition_02': | Recognition model released in 2019 March. 'recognition_02' is recommended since its overall accuracy is improved compared with 'recognition_01'. |", + "description": "Detect human faces in an image, return face rectangles, and optionally with faceIds, landmarks, and attributes.
\n* 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](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/identify), [Face - Verify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/verifyfacetoface), and [Face - Find Similar](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/findsimilar). The stored face feature(s) will expire and be deleted 24 hours after the original detection call.\n* 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.\n* JPEG, PNG, GIF (the first frame), and BMP format are supported. The allowed image file size is from 1KB to 6MB.\n* Up to 100 faces can be returned for an image. Faces are ranked by face rectangle size from large to small.\n* For optimal results when querying [Face - Identify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/identify), [Face - Verify](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/verifyfacetoface), and [Face - Find Similar](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/findsimilar) ('returnFaceId' is true), please use faces that are: frontal, clear, and with a minimum size of 200x200 pixels (100 pixels between eyes).\n* 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.\n* 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/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model)\n | Model | Recommended use-case(s) |\n | ---------- | -------- |\n | 'detection_01': | The default detection model for [Face - Detect](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/detectwithurl). 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. |\n | 'detection_02': | Detection model released in 2019 May with improved accuracy especially on small, side and blurry faces. |\n\n* 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/azure/cognitive-services/face/face-api-how-to-topics/specify-recognition-model)\n | Model | Recommended use-case(s) |\n | ---------- | -------- |\n | 'recognition_01': | The default recognition model for [Face - Detect](https://docs.microsoft.com/rest/api/cognitiveservices/face/face/detectwithurl). All those faceIds created before 2019 March are bonded with this recognition model. |\n | 'recognition_02': | Recognition model released in 2019 March. |\n | 'recognition_03': | Recognition model released in 2020 May. 'recognition_03' is recommended since its overall accuracy is improved compared with 'recognition_01' and 'recognition_02'. |", "operationId": "Face_DetectWithStream", "parameters": [ { @@ -3874,7 +3874,8 @@ }, "enum": [ "recognition_01", - "recognition_02" + "recognition_02", + "recognition_03" ] }, "ApplyScope": { @@ -4257,7 +4258,8 @@ }, "enum": [ "recognition_01", - "recognition_02" + "recognition_02", + "recognition_03" ] }, "returnRecognitionModel": { @@ -4288,4 +4290,4 @@ ] } } -} +} \ No newline at end of file From 5edc676d8e4332afec6b9e329dd7002bea31e508 Mon Sep 17 00:00:00 2001 From: Long Li Date: Wed, 10 Jun 2020 15:13:15 -0700 Subject: [PATCH 2/2] add newline at EOF --- .../cognitiveservices/data-plane/Face/stable/v1.0/Face.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/specification/cognitiveservices/data-plane/Face/stable/v1.0/Face.json b/specification/cognitiveservices/data-plane/Face/stable/v1.0/Face.json index 98ea0a03c556..d96a1f87d277 100644 --- a/specification/cognitiveservices/data-plane/Face/stable/v1.0/Face.json +++ b/specification/cognitiveservices/data-plane/Face/stable/v1.0/Face.json @@ -4290,4 +4290,4 @@ ] } } -} \ No newline at end of file +}