Awesome

CompreFace .NET SDK

CompreFace NET SDK makes face recognition into your application even easier.

Table of content

• Requirements
• Installation
• Usage
  • Initialization
  • Adding faces into a face collection
  • Recognition
  • Recognition cross-platform demo app
• Reference
  • CompreFace Global Object
    • Services
  • Optional properties
  • Face Recognition Service
    • Face Recognition
      • Recognize Faces from a Given Image
      • Verify Faces from a Given Image
    • Get Face Collection
      • Add an Example of a Subject
      • List of All Saved Examples of the Subject
      • Delete All Examples of the Subject by Name
      • Delete an Example of the Subject by ID
      • Direct Download an Image example of the Subject by ID
      • Download an Image example of the Subject by ID
    • Get Subjects
      • Add a Subject
      • List Subjects
      • Rename a Subject
      • Delete a Subject
      • Delete All Subjects
    • Face Detection Service
      • Detect
    • Face Verification Service
      • Verify
• Contributing
  • Report Bugs
  • Submit Feedback
• License info

Requirements

Before using our SDK make sure you have installed CompreFace and .NET on your machine.

1. CompreFace
2. .NET (Version 6+)

CompreFace compatibility matrix

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. Also you can review Recognition example application. It is a simple example of CompreFace usage.

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)

Example:

var client = new CompreFaceClient(
    domain: "http://localhost",
    port: "8000");

Services

1. client.GetCompreFaceService<RecognitionService>(apiKey)

Inits face recognition service object.

Example:

var apiKey = "00000000-0000-0000-0000-000000000002";

var recognitionService = client.GetCompreFaceService<RecognitionService>(apiKey);

2. client.GetCompreFaceService<FaceDetectionService>(apiKey)

Inits face detection service object.

Example:

var apiKey = "00000000-0000-0000-0000-000000000003";

var faceDetectionService = client.GetCompreFaceService<FaceDetectionService>(api_key);

3. client.GetCompreFaceService<FaceVerificationService>(apiKey)

Inits face verification service object.

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.

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)

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; }
}

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"
  }
}

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.

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; }
}

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"
  }
}

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);

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; }
    }
}

DetProbThreShold is optional property.

Response:

{
  "image_id": "6b135f5b-a365-4522-b1f1-4c9ac2dd0728",
  "subject": "SubjectName"
}

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);

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; }
}

Response:

{
  "faces": [
    {
      "image_id": <image_id>,
      "subject": <subject>
    },
    ...
  ]
}

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);

DeleteAllExamplesRequest this is data transfer object which is serialized to JSON.

public class DeleteMultipleExampleRequest
{
	public IList<Guid> ImageIdList { get; set; }
}

Response:

{
    "deleted": <count>
}

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);

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>
}

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);

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);

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);

AddSubjectRequest this is data transfer object which is serialized to JSON.

public class AddSubjectRequest
{
    public string Subject { get; set; }
}

Response:

{
  "subject": "subject1"
}

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>"
  ]
}

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);

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"
}

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);

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"
}

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>"
}

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.

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; }
}

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"
  }
}

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.

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; }
}

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"
    }
  }]
}

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.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. 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.