CompreFaceLearning

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https://cdn.pixabay.com/photo/2018/07/09/21/03/integration-3527268__340.jpg

1. Configuration

  • registry - this is the docker hub registry. For release and pre-build images, it should be set to exadel/ value
  • postgres_password - password for Postgres database. It should be changed for production systems from the default value.
  • postgres_domain - the domain where Postgres database is run
  • postgres_port - Postgres database port
  • enable_email_server - if true, it will enable email verification for users. You should set email_host, email_username, and email_password variables for the correct work.
  • email_host - a host of the email provider. It should be set if enable_email_server variable is true
  • email_username - a username of email provider for authentication. It should be set if enable_email_server variable is true
  • email_password - a password of email provider for authentication. It should be set if enable_email_server variable is true
  • email_from - this value will see users in from fields when they receive emails from CompreFace. Corresponds to From field in rfc2822. Optional, if not set, then email_username will be used instead
  • save_images_to_db - should the CompreFace save photos to the database. Be careful, migrations could be run only if this value is true
  • compreface_api_java_options - java options of compreface-api container
  • compreface_admin_java_options - java options of compreface-admin container
  • ADMIN_VERSION - docker image tag of compreface-admin container
  • API_VERSION - docker image tag of compreface-api container
  • FE_VERSION - docker image tag of compreface-fe container
  • CORE_VERSION - docker image tag of compreface-core container
Custom-build Base library CPU GPU Face detection model / accuracy on WIDER Face (Hard) Face recognition model / accuracy on LFW Age and gender detection Comment
FaceNet (default) FaceNet x86 (AVX instructions) not supported MTCNN / 80.9% FaceNet (20180402-114759) / 99.63% Custom, the model is taken here For general purposes. Support CPU without AVX2
Mobilenet InsightFace x86 (AVX2 instructions) not supported RetinaFace-MobileNet0.25 / 82.5% MobileFaceNet,ArcFace / 99.50% InsightFace The fastest model among CPU only models
Mobilenet-gpu InsightFace x86 (AVX2 instructions) GPU (CUDA required) RetinaFace-MobileNet0.25 / 82.5% MobileFaceNet,ArcFace / 99.50% InsightFace The fastest model
SubCenter-ArcFace-r100 InsightFace x86 (AVX2 instructions) not supported retinaface_r50_v1 / 91.4% arcface-r100-msfdrop75 / 99.80% InsightFace The most accurate model, but the most slow
SubCenter-ArcFace-r100-gpu InsightFace x86 (AVX2 instructions) GPU (CUDA required) retinaface_r50_v1 / 91.4% arcface-r100-msfdrop75 / 99.80% InsightFace The most accurate model

2. Run

  • run custom-builds
docker-compose up -d
#http://localhost:8000/login 
docker-compose start
docker-compose stop
  • build own custom-build

  1. Upload your model to Google Drive and add it to one the following files into the Calculator class:

    • embedding-calculator/src/services/facescan/plugins/facenet/facenet.py
    • embedding-calculator/src/services/facescan/plugins/insightface/insightface.py

  2. Take the docker-compose file from /dev folder as a template

  3. Specify new model name in build arguments. For more information look at [this documentation](https://github. com/exadel-inc/CompreFace/tree/master/embedding-calculator#run-service). E.g. here is a part of docker-compose file for building with custom model with GPU support.

Step 1. Install and run CompreFace using our Getting Started guide

Step 2. You need to sign up for the system and log in into the account you’ve just created or use the one you already have. After that, the system redirects you to the main page.

Step 3. Create an application (left section) using the “Create” link at the bottom of the page. An application is where you can create and manage your Face Collections.

Step 4. Enter your application by clicking on its name. Here you will have two options: you can either add new users and manage their access roles or create new Face Services.

Step 5. To recognize subjects among the known subjects, you need to create Face Recognition Service. After creating a new Face Service, you will see it in the Services List with an appropriate name and API key. After this step, you can look at our [demos]

Step 6. To add known subjects to your Face Collection of Face Recognition Service, you can use REST API. Once you’ve uploaded all known faces,you can test the collection using REST API or the TEST page. We recommend that you use an image size no higher than 5MB, as it could slow down the request process. The supported image formats include JPEG/PNG/JPG/ICO/BMP/GIF/TIF/TIFF.

Step 7. Upload your photo and let our open-source face recognition system match the image against the Face Collection. If you use a UI for face recognition, you will see the original picture with marks near every face. If you use REST API, you will receive a response in JSON format.

function saveNewImageToFaceCollection(elem) {
    let subject = encodeURIComponent(document.getElementById("subject").value);
    let apiKey = document.getElementById("apiKey").value;
    let formData = new FormData();
    let photo = elem.files[0];

    formData.append("file", photo);

    fetch('http://localhost:8000/api/v1/recognition/faces/?subject=' + subject,
        {
            method: "POST",
            headers: {
                "x-api-key": apiKey
            },
            body: formData
        }
    ).then(r => r.json()).then(
        function (data) {
            console.log('New example was saved', data);
        })
        .catch(function (error) {
            alert('Request failed: ' + JSON.stringify(error));
        });
}

This function sends the image to our server and shows results in a text area:

function recognizeFace(elem) {
    let apiKey = document.getElementById("apiKey").value;
    let formData = new FormData();
    let photo = elem.files[0];

    formData.append("file", photo);

    fetch('http://localhost:8000/api/v1/recognition/recognize',
        {
            method: "POST",
            headers: {
                "x-api-key": apiKey
            },
            body: formData
        }
    ).then(r => r.json()).then(
        function (data) {
            document.getElementById("result").innerHTML = JSON.stringify(data);
        })
        .catch(function (error) {
            alert('Request failed: ' + JSON.stringify(error));
        });
}

https://lddpicture.oss-cn-beijing.aliyuncs.com/picture/image-20210626200731382.png

3. RestAPI

Add a Subject

Create a new subject in Face Collection. Creating a subject is an optional step, you can upload an example without an existing subject, and a subject will be created automatically.

curl -X POST "http://localhost:8000/api/v1/recognition/subjects" \
-H "Content-Type: application/json" \
-H "x-api-key: <service_api_key>" \
-d '{"subject: <subject_name>"}'
Element Description Type Required Notes
Content-Type header string required application/json
x-api-key header string required api key of the Face recognition service, created by the user
subject body param string required is the name of the subject. It can be a person name, but it can be any string

Response body on success:

{
  "subject": "<subject_name>"
}
Element Type Description
subject string is the name of the subject

Rename a Subject

since 0.6 version

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.

curl -X PUT "http://localhost:8000/api/v1/recognition/subjects/<subject>" \
-H "Content-Type: application/json" \
-H "x-api-key: <service_api_key>" \
-d '{"subject: <subject_name>"}'
Element Description Type Required Notes
Content-Type header string required application/json
x-api-key header string required api key of the Face recognition service, created by the user
subject body param string required is the name of the subject. It can be a person name, but it can be any string

Response body on success:

{
  "updated": "true|false"
}
Element Type Description
updated boolean failed or success

Delete a Subject

since 0.6 version

Delete existing subject and all saved faces.

curl -X DELETE "http://localhost:8000/api/v1/recognition/subjects/<subject>" \
-H "Content-Type: application/json" \
-H "x-api-key: <service_api_key>"
Element Description Type Required Notes
Content-Type header string required application/json
x-api-key header string required api key of the Face recognition service, created by the user
subject body param string required is the name of the subject. It can be a person name, but it can be any string

Response body on success:

{
  "subject": "<subject_name>"
}
Element Type Description
subject string is the name of the subject

Delete All Subjects

since 0.6 version

Delete all existing subjects and all saved faces.

curl -X DELETE "http://localhost:8000/api/v1/recognition/subjects" \
-H "Content-Type: application/json" \
-H "x-api-key: <service_api_key>"
Element Description Type Required Notes
Content-Type header string required application/json
x-api-key header string required api key of the Face recognition service, created by the user

Response body on success:

{
  "deleted": "<count>"
}
Element Type Description
deleted integer number of deleted subjects

List Subjects

since 0.6 version

This returns all subject related to Face Collection.

curl -X GET "http://localhost:8000/api/v1/recognition/subjects/" \
-H "Content-Type: application/json" \
-H "x-api-key: <service_api_key>"
Element Description Type Required Notes
Content-Type header string required application/json
x-api-key header string required api key of the Face recognition service, created by the user

Response body on success:

{
  "subjects": [
    "<subject_name1>",
    "<subject_name2>"
    ]
}
Element Type Description
subjects array the list of subjects in Face Collection

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.

curl -X POST "http://localhost:8000/api/v1/recognition/faces?subject=<subject>&det_prob_threshold=<det_prob_threshold>" \
-H "Content-Type: multipart/form-data" \
-H "x-api-key: <service_api_key>" \
-F file=@<local_file>
Element Description Type Required Notes
Content-Type header string required multipart/form-data
x-api-key header string required api key of the Face recognition service, created by the user
subject param string required is the name you assign to the image you save
det_prob_threshold param string optional minimum required confidence that a recognized face is actually a face. Value is between 0.0 and 1.0.
file body image required allowed image formats: jpeg, jpg, ico, png, bmp, gif, tif, tiff, webp. Max size is 5Mb

Response body on success:

{
  "image_id": "6b135f5b-a365-4522-b1f1-4c9ac2dd0728",
  "subject": "subject1"
}
Element Type Description
image_id UUID UUID of uploaded image
subject string Subject of the saved image

Recognize Faces from a Given Image

To recognize faces from the uploaded image:

curl  -X POST "http://localhost:8000/api/v1/recognition/recognize?limit=<limit>&prediction_count=<prediction_count>&det_prob_threshold=<det_prob_threshold>&face_plugins=<face_plugins>&status=<status>" \
-H "Content-Type: multipart/form-data" \
-H "x-api-key: <service_api_key>" \
-F file=<local_file>
Element Description Type Required Notes
Content-Type header string required multipart/form-data
x-api-key header string required api key of the Face recognition service, created by the user
file body image required allowed image formats: jpeg, jpg, ico, png, bmp, gif, tif, tiff, webp. Max size is 5Mb
limit param integer optional 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
det_prob_threshold param string optional minimum required confidence that a recognized face is actually a face. Value is between 0.0 and 1.0.
prediction_count param integer optional maximum number of subject predictions per face. It returns the most similar subjects. Default value: 1
face_plugins param string optional comma-separated slugs of face plugins. If empty, no additional information is returned. Learn more
status param boolean optional if true includes system information like execution_time and plugin_version fields. Default value is false

Response body on success:

{
  "result" : [ {
    "age" : [ 25, 32 ],
    "gender" : "female",
    "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
    }
  } ],
  "plugins_versions" : {
    "age" : "agegender.AgeDetector",
    "gender" : "agegender.GenderDetector",
    "detector" : "facenet.FaceDetector",
    "calculator" : "facenet.Calculator"
  }
}
Element Type Description
age array detected age range. Return only if age plugin is enabled
gender string detected gender. Return only if gender 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
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

List of All Saved Examples of the Subject

To retrieve a list of subjects saved in a Face Collection:

curl -X GET "http://localhost:8000/api/v1/recognition/faces?page=<page>&size=<size>" \
-H "x-api-key: <service_api_key>" \
Element Description Type Required Notes
x-api-key header string required api key of the Face recognition service, created by the user
page param integer optional page number of examples to return. Can be used for pagination. Default value is 0. Since 0.6 version
size param integer optional faces on page (page size). Can be used for pagination. Default value is 20. Since 0.6 version

Response body on success:

{
  "faces": [
    {
      "image_id": <image_id>,
      "subject": <subject>
    },
    ...
  ],
  "page_number": 0,
  "page_size": 10,
  "total_pages": 2,
  "total_elements": 12
}
Element Type Description
face.image_id UUID UUID of the face
fase.subject string of the person, whose picture was saved for this api key
page_number integer page number
page_size integer requested page size
total_pages integer total pages
total_elements integer total faces

Delete All Examples of the Subject by Name

To delete all image examples of the :

curl -X DELETE "http://localhost:8000/api/v1/recognition/faces?subject=<subject>" \
-H "x-api-key: <service_api_key>"
Element Description Type Required Notes
x-api-key header string required api key of the Face recognition service, created by the user
subject param string optional is the name subject. If this parameter is absent, all faces in Face Collection will be removed

Response body on success:

{
    "deleted": <count>
}
Element Type Description
count integer Number of deleted faces

Delete an Example of the Subject by ID

Endpoint to delete an image by ID. If no image found by id - 404.

curl -X DELETE "http://localhost:8000/api/v1/recognition/faces/<image_id>" \
-H "x-api-key: <service_api_key>"
Element Description Type Required Notes
x-api-key header string required api key of the Face recognition service, created by the user
image_id variable UUID required UUID of the removing face

Response body on success:

{
  "image_id": <image_id>,
  "subject": <subject>
}
Element Type Description
image_id UUID UUID of the removed face
subject string of the person, whose picture was saved for this api key

Direct Download an Image example of the Subject by ID

since 0.6 version

You can paste this URL into the html tag to show the image.

curl -X GET "http://localhost:8000/api/v1/static/<service_api_key>/images/<image_id>"
Element Description Type Required Notes
service_api_key variable string required api key of the Face recognition service, created by the user
image_id variable UUID required UUID of the image to download

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:

curl -X GET "http://localhost:8000/api/v1/recognition/faces/<image_id>/img"
-H "x-api-key: <service_api_key>"
Element Description Type Required Notes
x-api-key header string required api key of the Face recognition service, created by the user
image_id variable UUID required UUID of the image to download

Response body is binary image. Empty bytes if image not found.

Verify Faces from a Given Image

To compare faces from the uploaded images with the face in saved image ID:

curl -X POST "http://localhost:8000/api/v1/recognition/faces/<image_id>/verify?
limit=<limit>&det_prob_threshold=<det_prob_threshold>&face_plugins=<face_plugins>&status=<status>" \
-H "Content-Type: multipart/form-data" \
-H "x-api-key: <service_api_key>" \
-F file=<local_file>
Element Description Type Required Notes
Content-Type header string required multipart/form-data
x-api-key header string required api key of the Face recognition service, created by the user
image_id variable UUID required UUID of the verifying face
file body image required allowed image formats: jpeg, jpg, ico, png, bmp, gif, tif, tiff, webp. Max size is 5Mb
limit param integer optional maximum number of faces on the target image to be recognized. It recognizes the biggest faces first. Value of 0 represents no limit. Default value: 0
det_prob_threshold param string optional minimum required confidence that a recognized face is actually a face. Value is between 0.0 and 1.0.
face_plugins param string optional comma-separated slugs of face plugins. If empty, no additional information is returned. Learn more
status param boolean optional if true includes system information like execution_time and plugin_version fields. Default value is false

Response body on success:

{
  "result": [
    {
      "age" : [ 25, 32 ],
      "gender" : "female",
      "embedding" : [ -0.049007344990968704, "...", -0.01753818802535534 ],
      "box" : {
        "probability" : 0.9997453093528748,
        "x_max" : 205,
        "y_max" : 167,
        "x_min" : 48,
        "y_min" : 0
      },
      "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
      }
    }
  ],
  "plugins_versions" : {
    "age" : "agegender.AgeDetector",
    "gender" : "agegender.GenderDetector",
    "detector" : "facenet.FaceDetector",
    "calculator" : "facenet.Calculator"
  }
}
Element Type Description
age array detected age range. Return only if age plugin is enabled
gender string detected gender. Return only if gender 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

Face Detection Service

To detect faces from the uploaded image:

curl  -X POST "http://localhost:8000/api/v1/detection/detect?limit=<limit>&det_prob_threshold=<det_prob_threshold>&face_plugins=<face_plugins>&status=<status>" \
-H "Content-Type: multipart/form-data" \
-H "x-api-key: <service_api_key>" \
-F file=<local_file>
Element Description Type Required Notes
Content-Type header string required multipart/form-data
x-api-key header string required api key of the Face Detection service, created by the user
file body image required image where to detect faces. Allowed image formats: jpeg, jpg, ico, png, bmp, gif, tif, tiff, webp. Max size is 5Mb
limit param integer optional 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
det_prob_threshold param string optional minimum required confidence that a recognized face is actually a face. Value is between 0.0 and 1.0
face_plugins param string optional comma-separated slugs of face plugins. If empty, no additional information is returned. Learn more
status param boolean optional if true includes system information like execution_time and plugin_version fields. Default value is false

Response body on success:

{
  "result" : [ {
    "age" : [ 25, 32 ],
    "gender" : "female",
    "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
    }
  } ],
  "plugins_versions" : {
    "age" : "agegender.AgeDetector",
    "gender" : "agegender.GenderDetector",
    "detector" : "facenet.FaceDetector",
    "calculator" : "facenet.Calculator"
  }
}
Element Type Description
age array detected age range. Return only if age plugin is enabled
gender string detected gender. Return only if gender 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

Face Verification Service

To compare faces from given two images:

curl  -X POST "http://localhost:8000/api/v1/verification/verify?limit=<limit>&prediction_count=<prediction_count>&det_prob_threshold=<det_prob_threshold>&face_plugins=<face_plugins>&status=<status>" \
-H "Content-Type: multipart/form-data" \
-H "x-api-key: <service_api_key>" \
-F source_image=<local_check_file>
-F target_image=<local_process_file>
Element Description Type Required Notes
Content-Type header string required multipart/form-data
x-api-key header string required api key of the Face verification service, created by the user
source_image body image required file to be verified. Allowed image formats: jpeg, jpg, ico, png, bmp, gif, tif, tiff, webp. Max size is 5Mb
target_image body image required reference file to check the source file. Allowed image formats: jpeg, jpg, ico, png, bmp, gif, tif, tiff, webp. Max size is 5Mb
limit param integer optional maximum number of faces on the target image to be recognized. It recognizes the biggest faces first. Value of 0 represents no limit. Default value: 0
det_prob_threshold param string optional minimum required confidence that a recognized face is actually a face. Value is between 0.0 and 1.0.
face_plugins param string optional comma-separated slugs of face plugins. If empty, no additional information is returned. Learn more
status param boolean optional if true includes system information like execution_time and plugin_version fields. Default value is false

Response body on success:

{
  "result" : [{
    "source_image_face" : {
      "age" : [ 25, 32 ],
      "gender" : "female",
      "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
      }
    },
    "face_matches": [
      {
        "age" : [ 25, 32 ],
        "gender" : "female",
        "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
        }
      }],
    "plugins_versions" : {
      "age" : "agegender.AgeDetector",
      "gender" : "agegender.GenderDetector",
      "detector" : "facenet.FaceDetector",
      "calculator" : "facenet.Calculator"
    }
  }]
}
Element Type Description
source_image_face object additional info about source image face
face_matches array result of face verification
age array detected age range. Return only if age plugin is enabled
gender string detected gender. Return only if gender 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

Base64 Support

since 0.5.1 version

Except multipart/form-data, all CompreFace endpoints, that require images as input, accept images in Base64 format. The base rule is to use Content-Type: application/json header and send JSON in the body. The name of the JSON parameter coincides with the name of the multipart/form-data parameter.

Add an Example of a Subject, Base64

Full description here.

curl -X POST "http://localhost:8000/api/v1/recognition/faces?subject=<subject>&det_prob_threshold=<det_prob_threshold>" \
-H "Content-Type: application/json" \
-H "x-api-key: <service_api_key>" \
-d {"file": "<base64_value>"}

Recognize Faces from a Given Image, Base64

Full description here.

curl  -X POST "http://localhost:8000/api/v1/recognition/recognize?limit=<limit>&prediction_count=<prediction_count>&det_prob_threshold=<det_prob_threshold>&face_plugins=<face_plugins>&status=<status>" \
-H "Content-Type: application/json" \
-H "x-api-key: <service_api_key>" \
-d {"file": "<base64_value>"}

Verify Faces from a Given Image, Base64

Full description here.

curl -X POST "http://localhost:8000/api/v1/recognition/faces/<image_id>/verify?
limit=<limit>&det_prob_threshold=<det_prob_threshold>&face_plugins=<face_plugins>&status=<status>" \
-H "Content-Type: application/json" \
-H "x-api-key: <service_api_key>" \
-d {"file": "<base64_value>"}

Face Detection Service, Base64

Full description here.

curl  -X POST "http://localhost:8000/api/v1/detection/detect?limit=<limit>&det_prob_threshold=<det_prob_threshold>&face_plugins=<face_plugins>&status=<status>" \
-H "Content-Type: application/json" \
-H "x-api-key: <service_api_key>" \
-d {"file": "<base64_value>"}

Face Verification Service, Base64

Full description here.

curl -X POST "http://localhost:8000/api/v1/verification/verify?limit=<limit>&prediction_count=<prediction_count>&det_prob_threshold=<det_prob_threshold>&face_plugins=<face_plugins>&status=<status>" \
-H "Content-Type: application/json" \
-H "x-api-key: <service_api_key>" \
-d {"source_image": "<source_image_base64_value>", "target_image": "<target_image_base64_value>"}
更新于 2023-12-31 
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