CompreFace.NET.Sdk
1.0.0
See the version list below for details.
dotnet add package CompreFace.NET.Sdk --version 1.0.0
NuGet\Install-Package CompreFace.NET.Sdk -Version 1.0.0
<PackageReference Include="CompreFace.NET.Sdk" Version="1.0.0" />
paket add CompreFace.NET.Sdk --version 1.0.0
#r "nuget: CompreFace.NET.Sdk, 1.0.0"
// Install CompreFace.NET.Sdk as a Cake Addin #addin nuget:?package=CompreFace.NET.Sdk&version=1.0.0 // Install CompreFace.NET.Sdk as a Cake Tool #tool nuget:?package=CompreFace.NET.Sdk&version=1.0.0
CompreFace .NET SDK
CompreFace NET SDK makes face recognition into your application even easier.
Table of content
- Requirements
- Installation
- Usage
- Reference
- Contributing
- License info
Requirements
Before using our SDK make sure you have installed CompreFace and .NET on your machine.
- CompreFace
- .NET (Version 7+)
CompreFace compatibility matrix
CompreFace .NET SDK version | CompreFace 1.1.0 |
---|---|
1.0.0 | ✔ |
Explanation:
- ✔ SDK supports all functionality from CompreFace.
- :yellow_circle: SDK works with this CompreFace version. In case if CompreFace version is newer - SDK won't support new features of CompreFace. In case if CompreFace version is older - new SDK features will fail.
- ✘ There are major backward compatibility issues. It is not recommended to use these versions together
Installation
To use SDK install NuGet package
Install-Package CompreFace.NET.Sdk
Usage
All examples below you can find in repository inside examples folder.
Initialization
To start using Compreface .NET SDK you need to import CompreFace
object from 'compreface-sdk' dependency.
Then you need to create CompreFaceClient
object and initialize it with DOMAIN
and PORT
. By default, if you run CompreFace on your local machine, it's DOMAIN
will be http://localhost
, and PORT
in this case will be 8000
.
You can pass optional options
object when call method to set default parameters, see reference for more information.
You should use RecognitionService
service in CompreFaceClient
object to recognize faces.
However, before recognizing you need first to add subject into the face collection. To do this, get the Subject
object with the help of RecognitionService
. Subject
is included in RecognitionService
class.
var client = new CompreFaceClient(
domain: "http://localhost",
port: "8000");
var recognitionService = client.GetCompreFaceService<RecognitionService>(recognition api key);
var subject = recognitionService.Subject;
var subjectRequest = new AddSubjectRequest()
{
Subject = "Subject name"
};
var subjectResponse = await subject.AddAsync(subjectRequest);
Adding faces into a face collection
Here is example that shows how to add an image to your face collection from your file system:
var faceCollection = recognitionService.FaceCollection;
var request = new AddSubjectExampleRequestByFilePath()
{
DetProbThreShold = 0.81m,
Subject = "Subject name",
FilePath = "Full file path"
};
var response = await faceCollection.AddAsync(request);
Recognition
This code snippet shows how to recognize unknown face. Recognize faces from a given image
var recognizeRequest = new RecognizeFaceFromImageRequestByFilePath()
{
FilePath = "Full file path",
DetProbThreshold = 0.81m,
FacePlugins = new List<string>()
{
"landmarks",
"gender",
"age",
"detector",
"calculator"
},
Limit = 0,
PredictionCount = 1,
Status = true
};
var recognizeResponse = await recognitionService.RecognizeFaceFromImage.RecognizeAsync(recognizeRequest);
Reference
CompreFace Global Object
Global CompreFace Object is used for initializing connection to CompreFace and setting default values for options. Default values will be used in every service method if applicable.
Constructor:
CompreFaceClient(domain, port)
Argument | Type | Required | Notes |
---|---|---|---|
domain | string | required | Domain with protocol where CompreFace is located. E.g. http://localhost |
port | string | required | CompreFace port. E.g. 8000 |
Example:
var client = new CompreFaceClient(
domain: "http://localhost",
port: "8000");
Services
client.GetCompreFaceService<RecognitionService>(apiKey)
Inits face recognition service object.
Argument | Type | Required | Notes |
---|---|---|---|
apiKey | string | required | Face Recognition Api Key in UUID format |
Example:
var apiKey = "00000000-0000-0000-0000-000000000002";
var recognitionService = client.GetCompreFaceService<RecognitionService>(apiKey);
client.GetCompreFaceService<FaceDetectionService>(apiKey)
Inits face detection service object.
Argument | Type | Required | Notes |
---|---|---|---|
apiKey | string | required | Face Detection Api Key in UUID format |
Example:
var apiKey = "00000000-0000-0000-0000-000000000003";
var faceDetectionService = client.GetCompreFaceService<FaceDetectionService>(api_key);
client.GetCompreFaceService<FaceVerificationService>(apiKey)
Inits face verification service object.
Argument | Type | Required | Notes |
---|---|---|---|
apiKey | string | required | Face Verification Api Key in UUID format |
Example:
var apiKey = "00000000-0000-0000-0000-000000000004";
var faceVerificationService = client.GetCompreFaceService<FaceVerificationService>(api_key);
Optional properties
All optional properties are located in the BaseFaceRequest
class.
public class BaseFaceRequest
{
public int? Limit { get; set; }
public decimal DetProbThreshold { get; set; }
public IList<string> FacePlugins { get; set; }
public bool Status { get; set; }
}
BaseFaceRequest
class is inherited by several DTO classes which are serialized to request format.
Here is description how it looks like in request body. | Option | Type | Notes | | --------------------| ------ | ----------------------------------------- | | det_prob_threshold | float | minimum required confidence that a recognized face is actually a face. Value is between 0.0 and 1.0 | | limit | integer | maximum number of faces on the image to be recognized. It recognizes the biggest faces first. Value of 0 represents no limit. Default value: 0 | | prediction_count | integer | maximum number of subject predictions per face. It returns the most similar subjects. Default value: 1 | | face_plugins | string | comma-separated slugs of face plugins. If empty, no additional information is returned. Learn more | | status | boolean | if true includes system information like execution_time and plugin_version fields. Default value is false |
Example of face recognition with object:
var recognizeRequest = new RecognizeFaceFromImageRequestByFilePath()
{
FilePath = "Full file path",
DetProbThreshold = 0.81m,
FacePlugins = new List<string>()
{
"landmarks",
"gender",
"age",
"detector",
"calculator"
},
Limit = 0,
PredictionCount = 1,
Status = true
};
var recognizeResponse = await recognitionService.RecognizeFaceFromImage.RecognizeAsync(recognizeRequest);
Face Recognition Service
Face recognition service is used for face identification. This means that you first need to upload known faces to face collection and then recognize unknown faces among them. When you upload an unknown face, the service returns the most similar faces to it. Also, face recognition service supports verify endpoint to check if this person from face collection is the correct one. For more information, see CompreFace page.
Face Recognition
Methods:
Recognize Faces from a Given Image
Recognizes all faces from the image. The first argument is the image location, it can be an url, local path or bytes.
await recognitionService.RecognizeFaceFromImage.RecognizeAsync(recognizeRequest)
Argument | Type | Required | Notes |
---|---|---|---|
recognizeRequest | RecognizeFaceFromImageRequestByFilePath | required |
RecognizeFaceFromImageRequestByFilePath
this is data transfer object which is serialized to JSON.
public class RecognizeFaceFromImageRequestByFilePath : BaseRecognizeFaceFromImageRequest
{
public string FilePath { get; set; }
}
BaseRecognizeFaceFromImageRequest
class:
public class BaseRecognizeFaceFromImageRequest : BaseFaceRequest
{
public int? PredictionCount { get; set; }
}
BaseFaceRequest
class contains optional properties:
public class BaseFaceRequest
{
public int? Limit { get; set; }
public decimal DetProbThreshold { get; set; }
public IList<string> FacePlugins { get; set; } = new List<string>()
public bool Status { get; set; }
}
Option | Type | Notes |
---|---|---|
det_prob_threshold | float | minimum required confidence that a recognized face is actually a face. Value is between 0.0 and 1.0 |
limit | integer | maximum number of faces on the image to be recognized. It recognizes the biggest faces first. Value of 0 represents no limit. Default value: 0 |
prediction_count | integer | maximum number of subject predictions per face. It returns the most similar subjects. Default value: 1 |
face_plugins | string | comma-separated slugs of face plugins. If empty, no additional information is returned. Learn more |
status | boolean | if true includes system information like execution_time and plugin_version fields. Default value is false |
Response from ComreFace API:
{
"result" : [ {
"age" : {
"probability": 0.9308982491493225,
"high": 32,
"low": 25
},
"gender" : {
"probability": 0.9898611307144165,
"value": "female"
},
"mask" : {
"probability": 0.9999470710754395,
"value": "without_mask"
},
"embedding" : [ 9.424854069948196E-4, "...", -0.011415496468544006 ],
"box" : {
"probability" : 1.0,
"x_max" : 1420,
"y_max" : 1368,
"x_min" : 548,
"y_min" : 295
},
"landmarks" : [ [ 814, 713 ], [ 1104, 829 ], [ 832, 937 ], [ 704, 1030 ], [ 1017, 1133 ] ],
"subjects" : [ {
"similarity" : 0.97858,
"subject" : "subject1"
} ],
"execution_time" : {
"age" : 28.0,
"gender" : 26.0,
"detector" : 117.0,
"calculator" : 45.0,
"mask": 36.0
}
} ],
"plugins_versions" : {
"age" : "agegender.AgeDetector",
"gender" : "agegender.GenderDetector",
"detector" : "facenet.FaceDetector",
"calculator" : "facenet.Calculator",
"mask": "facemask.MaskDetector"
}
}
Element | Type | Description |
---|---|---|
age | object | detected age range. Return only if age plugin is enabled |
gender | object | detected gender. Return only if gender plugin is enabled |
mask | object | detected mask. Return only if face mask plugin is enabled. |
embedding | array | face embeddings. Return only if calculator plugin is enabled |
box | object | list of parameters of the bounding box for this face |
probability | float | probability that a found face is actually a face |
x_max, y_max, x_min, y_min | integer | coordinates of the frame containing the face |
landmarks | array | list of the coordinates of the frame containing the face-landmarks. |
subjects | list | list of similar subjects with size of <prediction_count> order by similarity |
similarity | float | similarity that on that image predicted person |
subject | string | name of the subject in Face Collection |
execution_time | object | execution time of all plugins |
plugins_versions | object | contains information about plugin versions |
This JSON response is deserialized to RecognizeFaceFromImageResponse
data transfer object(DTO).
public class RecognizeFaceFromImageResponse
{
public IList<Result> Result { get; set; }
public PluginVersions PluginsVersions { get; set; }
}
public class Result : BaseResult
{
public IList<SimilarSubject> Subjects { get; set; }
}
BaseResult
class:
public class BaseResult
{
public Age Age { get; set; }
public Gender Gender { get; set; }
public Mask Mask { get; set; }
public Box Box { get; set; }
public IList<List<int>> Landmarks { get; set; }
public ExecutionTime ExecutionTime { get; set; }
public IList<decimal> Embedding { get; set; }
}
Verify Faces from a Given Image
await recognitionService.RecognizeFaceFromImage.VerifyAsync(request);
Compares similarities of given image with image from your face collection.
Argument | Type | Required | Notes |
---|---|---|---|
request | VerifyFacesFromImageRequest | required |
VerifyFacesFromImageRequest
this is data transfer object which is serialized to JSON.
public class VerifyFacesFromImageRequest : BaseVerifyFacesFromImageRequest
{
public string FilePath { get; set; }
}
BaseVerifyFacesFromImageRequest
class:
public class BaseVerifyFacesFromImageRequest : BaseFaceRequest
{
public Guid ImageId { get; set; }
}
BaseFaceRequest
class contains optional properties:
public class BaseFaceRequest
{
public int? Limit { get; set; }
public decimal DetProbThreshold { get; set; }
public IList<string> FacePlugins { get; set; }
public bool Status { get; set; }
}
Option | Type | Notes |
---|---|---|
det_prob_threshold | float | minimum required confidence that a recognized face is actually a face. Value is between 0.0 and 1.0 |
limit | integer | maximum number of faces on the image to be recognized. It recognizes the biggest faces first. Value of 0 represents no limit. Default value: 0 |
prediction_count | integer | maximum number of subject predictions per face. It returns the most similar subjects. Default value: 1 |
face_plugins | string | comma-separated slugs of face plugins. If empty, no additional information is returned. Learn more |
status | boolean | if true includes system information like execution_time and plugin_version fields. Default value is false |
Response:
{
"result" : [ {
"age" : {
"probability": 0.9308982491493225,
"high": 32,
"low": 25
},
"gender" : {
"probability": 0.9898611307144165,
"value": "female"
},
"mask" : {
"probability": 0.9999470710754395,
"value": "without_mask"
},
"embedding" : [ 9.424854069948196E-4, "...", -0.011415496468544006 ],
"box" : {
"probability" : 1.0,
"x_max" : 1420,
"y_max" : 1368,
"x_min" : 548,
"y_min" : 295
},
"landmarks" : [ [ 814, 713 ], [ 1104, 829 ], [ 832, 937 ], [ 704, 1030 ], [ 1017, 1133 ] ],
"subjects" : [ {
"similarity" : 0.97858,
"subject" : "subject1"
} ],
"execution_time" : {
"age" : 28.0,
"gender" : 26.0,
"detector" : 117.0,
"calculator" : 45.0,
"mask": 36.0
}
} ],
"plugins_versions" : {
"age" : "agegender.AgeDetector",
"gender" : "agegender.GenderDetector",
"detector" : "facenet.FaceDetector",
"calculator" : "facenet.Calculator",
"mask": "facemask.MaskDetector"
}
}
Element | Type | Description |
---|---|---|
age | object | detected age range. Return only if age plugin is enabled |
gender | object | detected gender. Return only if gender plugin is enabled |
mask | object | detected mask. Return only if face mask plugin is enabled. |
embedding | array | face embeddings. Return only if calculator plugin is enabled |
box | object | list of parameters of the bounding box for this face |
probability | float | probability that a found face is actually a face |
x_max, y_max, x_min, y_min | integer | coordinates of the frame containing the face |
landmarks | array | list of the coordinates of the frame containing the face-landmarks. Return only if landmarks plugin is enabled |
similarity | float | similarity that on that image predicted person |
execution_time | object | execution time of all plugins |
plugins_versions | object | contains information about plugin versions |
This JSON response is deserialized to VerifyFacesFromImageResponse
data transfer object(DTO).
public class VerifyFacesFromImageResponse
{
public IList<Result> Result { get; set; }
public PluginVersions PluginsVersions { get; set; }
}
public class Result : BaseResult
{
public string Subject { get; set; }
public decimal Similarity { get; set; }
}
BaseResult
class:
public class BaseResult
{
public Age Age { get; set; }
public Gender Gender { get; set; }
public Mask Mask { get; set; }
public Box Box { get; set; }
public IList<List<int>> Landmarks { get; set; }
public ExecutionTime ExecutionTime { get; set; }
public IList<decimal> Embedding { get; set; }
}
ExecutionTime
class:
public class ExecutionTime
{
public decimal Age { get; set; }
public decimal Gender { get; set; }
public decimal Detector { get; set; }
public decimal Calculator { get; set; }
public decimal Mask { get; set; }
}
Get Face Collection
recognitionService.FaceCollection
Returns Face collection object
Face collection could be used to manage known faces, e.g. add, list, or delete them.
Face recognition is performed for the saved known faces in face collection, so before using the recognize
method you need to save at least one face into the face collection.
More information about face collection and managing examples here
Methods:
Add an Example of a Subject
This creates an example of the subject by saving images. You can add as many images as you want to train the system. Image should contain only one face.
await recognitionService.FaceCollection.AddAsync(request);
Argument | Type | Required | Notes |
---|---|---|---|
request | AddSubjectExampleRequestByFilePath | required |
AddSubjectExampleRequestByFilePath
this is data transfer object which is serialized to JSON.
public class AddSubjectExampleRequestByFilePath : BaseExampleRequest
{
public string FilePath { get; set; }
}
BaseExampleRequest
class:
namespace Exadel.Compreface.DTOs.HelperDTOs.BaseDTOs
{
public class BaseExampleRequest
{
public string Subject { get; set; }
public decimal? DetProbThreShold { get; set; }
}
}
Option | Type | Notes |
---|---|---|
det_prob_threshold | float | minimum required confidence that a recognized face is actually a face. Value is between 0.0 and 1.0 |
DetProbThreShold
is optional property.
Response:
{
"image_id": "6b135f5b-a365-4522-b1f1-4c9ac2dd0728",
"subject": "SubjectName"
}
Element | Type | Description |
---|---|---|
image_id | UUID | UUID of uploaded image |
subject | string | Subject of the saved image |
This JSON response is deserialized to AddSubjectExampleResponse
data transfer object(DTO).
public class AddSubjectExampleResponse
{
public Guid ImageId { get; set; }
public string Subject { get; set; }
}
List of All Saved Examples of the Subject
To retrieve a list of subjects saved in a Face Collection:
await recognitionService.FaceCollection.ListAsync(request);
Argument | Type | Required | Notes |
---|---|---|---|
request | ListAllSubjectExamplesRequest | required |
ListAllSubjectExamplesRequest
this is data transfer object which is serialized to JSON.
public class ListAllSubjectExamplesRequest
{
public int? Page { get; set; }
public int? Size { get; set; }
public string Subject { get; set; }
}
Argument | Type | Required | Notes |
---|---|---|---|
Page | int | optional | Page number of examples to return. Can be used for pagination. Default value is 0. Since 0.6 version. |
Size | int | optional | Faces on page (page size). Can be used for pagination. Default value is 20. Since 0.6 version. |
Subject | int | optional | What subject examples endpoint should return. If empty, return examples for all subjects. Since 1.0 version |
Response:
{
"faces": [
{
"image_id": <image_id>,
"subject": <subject>
},
...
]
}
Element | Type | Description |
---|---|---|
image_id | UUID | UUID of the face |
subject | string | <subject> of the person, whose picture was saved for this api key |
This JSON response is deserialized to ListAllSubjectExamplesResponse
data transfer object(DTO).
public class ListAllSubjectExamplesResponse
{
public IList<Face> Faces { get; set; }
public int PageNumber { get; set; }
public int PageSize { get; set; }
public int TotalPages { get; set; }
public int TotalElements { get; set; }
}
Face
class:
public class Face
{
public Guid ImageId { get; set; }
public string Subject{ get; set; }
}
Delete All Examples of the Subject by Name
To delete all image examples of the <subject>:
recognitionService.FaceCollection.DeleteAllAsync(request);
Argument | Type | Required | Notes |
---|---|---|---|
request | DeleteAllExamplesRequest | required |
DeleteAllExamplesRequest
this is data transfer object which is serialized to JSON.
public class DeleteMultipleExampleRequest
{
public IList<Guid> ImageIdList { get; set; }
}
Response:
{
"deleted": <count>
}
Element | Type | Description |
---|---|---|
deleted | integer | Number of deleted faces |
This JSON response is deserialized to DeleteMultipleExamplesResponse
data transfer object(DTO).
public class DeleteMultipleExamplesResponse
{
public IList<Face> Faces { get; set; }
}
Delete an Example of the Subject by ID
To delete an image by ID:
await recognitionService.FaceCollection.DeleteAsync(request);
Argument | Type | Required | Notes |
---|---|---|---|
request | DeleteImageByIdRequest | required |
DeleteImageByIdRequest
this is data transfer object which is serialized to JSON.
public class DeleteImageByIdRequest
{
public Guid ImageId { get; set; }
}
Response:
{
"image_id": <image_id>,
"subject": <subject>
}
Element | Type | Description |
---|---|---|
image_id | UUID | UUID of the removed face |
subject | string | <subject> of the person, whose picture was saved for this api key |
This JSON response is deserialized to DeleteImageByIdResponse
data transfer object(DTO).
public class DeleteImageByIdResponse
{
public Guid ImageId { get; set; }
public string Subject { get; set; }
}
Direct Download an Image example of the Subject by ID
To download an image by ID:
await recognitionService.FaceCollection.DownloadAsync(downloadImageByIdRequest);
Argument | Type | Required | Notes |
---|---|---|---|
request | DownloadImageByIdDirectlyRequest | required |
DownloadImageByIdDirectlyRequest
this is data transfer object which is serialized to JSON.
public class DownloadImageByIdDirectlyRequest
{
public Guid ImageId { get; set; }
public Guid RecognitionApiKey { get; set; }
}
Response body is binary image. Empty bytes if image not found.
Download an Image example of the Subject by ID
since 0.6 version
To download an image example of the Subject by ID:
await recognitionService.FaceCollection.DownloadAsync(downloadImageBySubjectIdRequest);
Argument | Type | Required | Notes |
---|---|---|---|
request | DownloadImageByIdFromSubjectRequest | required |
DownloadImageByIdFromSubjectRequest
this is data transfer object which is serialized to JSON.
public class DownloadImageByIdFromSubjectRequest
{
public Guid ImageId { get; set; }
}
Response body is binary image. Empty bytes if image not found.
Get Subjects
recognitionService.Subject
Returns subjects object Subjects object allows working with subjects directly (not via subject examples). More information about subjects here
Methods:
Add a Subject
Create a new subject in Face Collection.
await recognitionService.Subject.AddAsync(request);
Argument | Type | Required | Notes |
---|---|---|---|
request | AddSubjectRequest | required |
AddSubjectRequest
this is data transfer object which is serialized to JSON.
public class AddSubjectRequest
{
public string Subject { get; set; }
}
Response:
{
"subject": "subject1"
}
Element | Type | Description |
---|---|---|
subject | string | is the name of the subject |
This JSON response is deserialized to AddSubjectResponse
data transfer object(DTO).
public class AddSubjectResponse
{
public string Subject { get; set; }
}
List Subjects
Returns all subject related to Face Collection.
await recognitionService.Subject.ListAsync();
Response:
{
"subjects": [
"<subject_name1>",
"<subject_name2>"
]
}
Element | Type | Description |
---|---|---|
subjects | array | the list of subjects in Face Collection |
This JSON response is deserialized to GetAllSubjectResponse
data transfer object(DTO).
public class GetAllSubjectResponse
{
public IList<string> Subjects { get; set; }
}
Rename a Subject
Rename existing subject. If a new subject name already exists, subjects are merged - all faces from the old subject name are reassigned to the subject with the new name, old subject removed.
await recognitionService.Subject.RenameAsync(request);
Argument | Type | Required | Notes |
---|---|---|---|
request | RenameSubjectRequest | required |
RenameSubjectRequest
this is data transfer object which is serialized to JSON.
public class RenameSubjectRequest
{
public string CurrentSubject { get; set; }
public string Subject { get; set; }
}
Response:
{
"updated": "true|false"
}
Element | Type | Description |
---|---|---|
updated | boolean | failed or success |
This JSON response is deserialized to RenameSubjectResponse
data transfer object(DTO).
public class RenameSubjectResponse
{
public bool Updated { get; set; }
}
Delete a Subject
Delete existing subject and all saved faces.
await recognitionService.Subject.DeleteAsync(request);
Argument | Type | Required | Notes |
---|---|---|---|
request | DeleteSubjectRequest | required |
DeleteSubjectRequest
this is data transfer object which is serialized to JSON.
public class RenameSubjectRequest
{
public string CurrentSubject { get; set; }
public string Subject { get; set; }
}
Response:
{
"subject": "subject1"
}
Element | Type | Description |
---|---|---|
subject | string | is the name of the subject |
This JSON response is deserialized to DeleteSubjectResponse
data transfer object(DTO).
public class DeleteSubjectResponse
{
public string Subject { get; set; }
}
Delete All Subjects
Delete all existing subjects and all saved faces.
await recognitionService.Subject.DeleteAllAsync();
Response:
{
"deleted": "<count>"
}
Element | Type | Description |
---|---|---|
deleted | integer | number of deleted subjects |
This JSON response is deserialized to DeleteAllSubjectsResponse
data transfer object(DTO).
public class DeleteAllSubjectsResponse
{
public int Deleted { get; set; }
}
Face Detection Service
Face detection service is used for detecting faces in the image.
Methods:
Detect
await faceDetectionService.DetectAsync(request);
Finds all faces on the image.
Argument | Type | Required | Notes |
---|---|---|---|
request | FaceDetectionRequestByFilePath | required |
FaceDetectionRequestByFilePath
this is data transfer object which is serialized to JSON.
public class FaceDetectionRequestByFilePath : BaseFaceRequest
{
public string FilePath { get; set; }
}
BaseFaceRequest
class contains optional properties:
public class BaseFaceRequest
{
public int? Limit { get; set; }
public decimal DetProbThreshold { get; set; }
public IList<string> FacePlugins { get; set; }
public bool Status { get; set; }
}
Option | Type | Notes |
---|---|---|
det_prob_threshold | float | minimum required confidence that a recognized face is actually a face. Value is between 0.0 and 1.0 |
limit | integer | maximum number of faces on the image to be recognized. It recognizes the biggest faces first. Value of 0 represents no limit. Default value: 0 |
prediction_count | integer | maximum number of subject predictions per face. It returns the most similar subjects. Default value: 1 |
face_plugins | string | comma-separated slugs of face plugins. If empty, no additional information is returned. Learn more |
status | boolean | if true includes system information like execution_time and plugin_version fields. Default value is false |
Response:
{
"result" : [ {
"age" : {
"probability": 0.9308982491493225,
"high": 32,
"low": 25
},
"gender" : {
"probability": 0.9898611307144165,
"value": "female"
},
"mask" : {
"probability": 0.9999470710754395,
"value": "without_mask"
},
"embedding" : [ -0.03027934394776821, "...", -0.05117142200469971 ],
"box" : {
"probability" : 0.9987509250640869,
"x_max" : 376,
"y_max" : 479,
"x_min" : 68,
"y_min" : 77
},
"landmarks" : [ [ 156, 245 ], [ 277, 253 ], [ 202, 311 ], [ 148, 358 ], [ 274, 365 ] ],
"execution_time" : {
"age" : 30.0,
"gender" : 26.0,
"detector" : 130.0,
"calculator" : 49.0,
"mask": 36.0
}
} ],
"plugins_versions" : {
"age" : "agegender.AgeDetector",
"gender" : "agegender.GenderDetector",
"detector" : "facenet.FaceDetector",
"calculator" : "facenet.Calculator",
"mask": "facemask.MaskDetector"
}
}
Element | Type | Description |
---|---|---|
age | object | detected age range. Return only if age plugin is enabled |
gender | object | detected gender. Return only if gender plugin is enabled |
mask | object | detected mask. Return only if face mask plugin is enabled. |
embedding | array | face embeddings. Return only if calculator plugin is enabled |
box | object | list of parameters of the bounding box for this face (on processedImage) |
probability | float | probability that a found face is actually a face (on processedImage) |
x_max, y_max, x_min, y_min | integer | coordinates of the frame containing the face (on processedImage) |
landmarks | array | list of the coordinates of the frame containing the face-landmarks. Return only if landmarks plugin is enabled |
execution_time | object | execution time of all plugins |
plugins_versions | object | contains information about plugin versions |
This JSON response is deserialized to FaceDetectionResponse
data transfer object(DTO).
public class FaceDetectionResponse
{
public IList<BaseResult> Result { get; set; }
public PluginVersions PluginsVersions { get; set; }
}
BaseResult
class:
public class BaseResult
{
public Age Age { get; set; }
public Gender Gender { get; set; }
public Mask Mask { get; set; }
public Box Box { get; set; }
public IList<List<int>> Landmarks { get; set; }
public ExecutionTime ExecutionTime { get; set; }
public IList<decimal> Embedding { get; set; }
}
Face Verification Service
Face verification service is used for comparing two images. A source image should contain only one face which will be compared to all faces on the target image.
Methods:
Verify
await faceVerificationService.VerifyAsync(request);
Compares two images provided in arguments. Source image should contain only one face, it will be compared to all faces in the target image.
Argument | Type | Required | Notes |
---|---|---|---|
request | FaceVerificationRequestByFilePath | required |
FaceVerificationRequestByFilePath
this is data transfer object which is serialized to JSON.
public class FaceVerificationRequestByFilePath : BaseFaceRequest
{
public string SourceImageFilePath { get; set; }
public string TargetImageFilePath { get; set; }
}
BaseFaceRequest
class contains optional properties:
public class BaseFaceRequest
{
public int? Limit { get; set; }
public decimal DetProbThreshold { get; set; }
public IList<string> FacePlugins { get; set; }
public bool Status { get; set; }
}
Option | Type | Notes |
---|---|---|
det_prob_threshold | float | minimum required confidence that a recognized face is actually a face. Value is between 0.0 and 1.0 |
limit | integer | maximum number of faces on the image to be recognized. It recognizes the biggest faces first. Value of 0 represents no limit. Default value: 0 |
prediction_count | integer | maximum number of subject predictions per face. It returns the most similar subjects. Default value: 1 |
face_plugins | string | comma-separated slugs of face plugins. If empty, no additional information is returned. Learn more |
status | boolean | if true includes system information like execution_time and plugin_version fields. Default value is false |
Response:
{
"result" : [{
"source_image_face" : {
"age" : {
"probability": 0.9308982491493225,
"high": 32,
"low": 25
},
"gender" : {
"probability": 0.9898611307144165,
"value": "female"
},
"mask" : {
"probability": 0.9999470710754395,
"value": "without_mask"
},
"embedding" : [ -0.0010271212086081505, "...", -0.008746841922402382 ],
"box" : {
"probability" : 0.9997453093528748,
"x_max" : 205,
"y_max" : 167,
"x_min" : 48,
"y_min" : 0
},
"landmarks" : [ [ 92, 44 ], [ 130, 68 ], [ 71, 76 ], [ 60, 104 ], [ 95, 125 ] ],
"execution_time" : {
"age" : 85.0,
"gender" : 51.0,
"detector" : 67.0,
"calculator" : 116.0,
"mask": 36.0
}
},
"face_matches": [
{
"age" : {
"probability": 0.9308982491493225,
"high": 32,
"low": 25
},
"gender" : {
"probability": 0.9898611307144165,
"value": "female"
},
"mask" : {
"probability": 0.9999470710754395,
"value": "without_mask"
},
"embedding" : [ -0.049007344990968704, "...", -0.01753818802535534 ],
"box" : {
"probability" : 0.99975,
"x_max" : 308,
"y_max" : 180,
"x_min" : 235,
"y_min" : 98
},
"landmarks" : [ [ 260, 129 ], [ 273, 127 ], [ 258, 136 ], [ 257, 150 ], [ 269, 148 ] ],
"similarity" : 0.97858,
"execution_time" : {
"age" : 59.0,
"gender" : 30.0,
"detector" : 177.0,
"calculator" : 70.0,
"mask": 36.0
}
}],
"plugins_versions" : {
"age" : "agegender.AgeDetector",
"gender" : "agegender.GenderDetector",
"detector" : "facenet.FaceDetector",
"calculator" : "facenet.Calculator",
"mask": "facemask.MaskDetector"
}
}]
}
Element | Type | Description |
---|---|---|
source_image_face | object | additional info about source image face |
face_matches | array | result of face verification |
age | object | detected age range. Return only if age plugin is enabled |
gender | object | detected gender. Return only if gender plugin is enabled |
mask | object | detected mask. Return only if face mask plugin is enabled. |
embedding | array | face embeddings. Return only if calculator plugin is enabled |
box | object | list of parameters of the bounding box for this face |
probability | float | probability that a found face is actually a face |
x_max, y_max, x_min, y_min | integer | coordinates of the frame containing the face |
landmarks | array | list of the coordinates of the frame containing the face-landmarks. Return only if landmarks plugin is enabled |
similarity | float | similarity between this face and the face on the source image |
execution_time | object | execution time of all plugins |
plugins_versions | object | contains information about plugin versions |
This JSON response is deserialized to FaceVerificationResponse
data transfer object(DTO).
public class FaceVerificationResponse
{
public IList<Result> Result { get; set; }
}
public class Result
{
public SourceImageFace SourceImageFace { get; set; }
public IList<FaceMatches> FaceMatches { get; set; }
public PluginVersions PluginsVersions { get; set; }
}
public class SourceImageFace : BaseResult
{ }
public class FaceMatches : BaseResult
{
public decimal Similarity { get; set; }
}
BaseResult
class:
public class BaseResult
{
public Age Age { get; set; }
public Gender Gender { get; set; }
public Mask Mask { get; set; }
public Box Box { get; set; }
public IList<List<int>> Landmarks { get; set; }
public ExecutionTime ExecutionTime { get; set; }
public IList<decimal> Embedding { get; set; }
}
Contributing
Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature
) - Commit your Changes (
git commit -m 'Add some AmazingFeature'
) - Push to the Branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
After creating your first contributing pull request, you will receive a request to sign our Contributor License Agreement by commenting your pull request with a special message.
Report Bugs
Please report any bugs here.
If you are reporting a bug, please specify:
- Your operating system name and version
- Any details about your local setup that might be helpful in troubleshooting
- Detailed steps to reproduce the bug
Submit Feedback
The best way to send us feedback is to file an issue at https://github.com/exadel-inc/compreface-net-sdk/issues.
If you are proposing a feature, please:
- Explain in detail how it should work.
- Keep the scope as narrow as possible to make it easier to implement.
License info
CompreFace .NET SDK is open-source facial recognition SDK released under the Apache 2.0 license.
Product | Versions Compatible and additional computed target framework versions. |
---|---|
.NET | net7.0 is compatible. net7.0-android was computed. net7.0-ios was computed. net7.0-maccatalyst was computed. net7.0-macos was computed. net7.0-tvos was computed. net7.0-windows was computed. net8.0 was computed. net8.0-android was computed. net8.0-browser was computed. net8.0-ios was computed. net8.0-maccatalyst was computed. net8.0-macos was computed. net8.0-tvos was computed. net8.0-windows was computed. |
-
net7.0
- Flurl.Http (>= 4.0.0-pre2)
- Microsoft.Extensions.Hosting (>= 7.0.0)
- Microsoft.Extensions.Http (>= 7.0.0)
- System.Net.Http (>= 4.3.4)
NuGet packages
This package is not used by any NuGet packages.
GitHub repositories
This package is not used by any popular GitHub repositories.