Eden AI Deepfake Detection API

The Deepfake Detection API from Eden AI — 1 operation(s) for deepfake detection.

Operations 1

POST /image/deepfake_detection/ Deepfake Detection #

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OpenAPI Specification

eden-ai-deepfake-detection-api-openapi.yml Raw ↑
openapi: 3.2.0
info:
  title: Image Features Deepfake Detection API
  version: '2.0'
  description: Your project description
servers:
- url: https://api.edenai.run/v2
tags:
- name: Deepfake Detection
paths:
  /image/deepfake_detection/:
    post:
      operationId: image_deepfake_detection_create
      description: 'Available Providers


        |Provider|Version|Price|Billing unit|

        |----|-------|-----|------------|

        |**sightengine**|`v1beta`|0.0145 (per 1 image)|1 image

        |**resemble**|`v2`|0.04 (per 1 image)|1 image'
      summary: Deepfake Detection
      tags:
      - Deepfake Detection
      requestBody:
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/imageanonymizationimagelandmark_detectionimageexplicit_contentimagedeepfake_detectionImageRequest'
            examples:
              RequestExample:
                value:
                  providers: sightengine,resemble
                  file_url: http://edenai-resource-example.jpg
                summary: Request Example
          multipart/form-data:
            schema:
              $ref: '#/components/schemas/imageanonymizationimagelandmark_detectionimageexplicit_contentimagedeepfake_detectionImageRequest'
            examples:
              RequestExample:
                value:
                  providers: sightengine,resemble
                  file: /edenai/edenai/features/image/samples/data/face.jpeg
                summary: Request Example
        required: true
      security:
      - FeatureApiAuth: []
      responses:
        '200':
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/imagedeepfake_detectionResponseModel'
              examples:
                ResponseExample:
                  value:
                    sightengine:
                      deepfake_score: 0.01
                      prediction: original
                      cost: 0.0
                    resemble:
                      deepfake_score: 0.04
                      prediction: original
                      cost: 0.0
                  summary: Response Example
          description: ''
        '400':
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/BadRequest'
          description: ''
        '500':
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Error'
          description: ''
        '403':
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Error'
          description: ''
        '404':
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/NotFoundResponse'
          description: ''
components:
  schemas:
    BadRequest:
      type: object
      properties:
        error:
          $ref: '#/components/schemas/NestedBadRequest'
      required:
      - error
    StatusEnum:
      enum:
      - sucess
      - fail
      type: string
    NotFoundResponse:
      type: object
      properties:
        details:
          type: string
          default: Not Found
    FieldError:
      type: object
      properties:
        <parameter_name>:
          type: array
          items:
            type: string
      required:
      - <parameter_name>
    Error:
      type: object
      properties:
        error:
          $ref: '#/components/schemas/NestedError'
      required:
      - error
    imageanonymizationimagelandmark_detectionimageexplicit_contentimagedeepfake_detectionImageRequest:
      type: object
      properties:
        settings:
          type: string
          default: {}
          description: "A dictionnary or a json object to specify specific models to use for some providers. <br>                     It can be in the following format: {\"google\" : \"google_model\", \"ibm\": \"ibm_model\"...}.\n                     "
        providers:
          type: array
          items:
            type: string
            minLength: 1
          description: 'It can be one (ex: **''amazon''** or **''google''**) or multiple provider(s) (ex: **''amazon,microsoft,google''**)             that the data will be redirected to in order to get the processed results.<br>             Providers can also be invoked with specific models (ex: providers: **''amazon/model1, amazon/model2, google/model3''**)'
        fallback_providers:
          type: array
          items:
            type: string
          default: []
          description: "Providers in this list will be used as fallback if the call to provider in `providers` parameter fails.\n    To use this feature, you must input **only one** provider in the `providers` parameter. but you can put up to 5 fallbacks.\n\nThey will be tried in the same order they are input, and it will stop to the first provider who doesn't fail.\n\n\n*Doesn't work with async subfeatures.*\n    "
          maxItems: 5
        response_as_dict:
          type: boolean
          default: true
          description: "Optional : When set to **true** (default), the response is an object of responses with providers names as keys : <br> \n                  ``` {\"google\" : { \"status\": \"success\", ... }, } ``` <br>\n                When set to **false** the response structure is a list of response objects : <br> \n                   ``` [{\"status\": \"success\", \"provider\": \"google\" ... }, ] ```. <br>\n                  "
        attributes_as_list:
          type: boolean
          default: false
          description: "Optional : When set to **false** (default) the structure of the extracted items is list of objects having different attributes : <br>\n     ```{'items': [{\"attribute_1\": \"x1\",\"attribute_2\": \"y2\"}, ... ]}``` <br>\n     When it is set to **true**, the response contains an object with each attribute as a list : <br>\n     ```{ \"attribute_1\": [\"x1\",\"x2\", ...], \"attribute_2\": [y1, y2, ...]}``` "
        show_base_64:
          type: boolean
          default: true
        show_original_response:
          type: boolean
          default: false
          description: "Optional : Shows the original response of the provider.<br>\n        When set to **true**, a new attribute *original_response* will appear in the response object."
        file:
          type: string
          format: binary
          description: 'File to analyse in binary format to be used with *content-type*: **multipart/form-data** <br> **Does not work with application/json !**'
          pattern: (?:jpg|jpeg|png|tiff)$
        file_url:
          type:
          - string
          - 'null'
          format: uri
          description: 'File **URL** to analyse to be used with with *content-type*: **application/json**.'
      required:
      - providers
    ImagedeepfakeDetectionDeepfakeDetectionDataClassPredictionEnum:
      enum:
      - deepfake
      - original
      type: string
    imagedeepfake_detectionDeepfakeDetectionDataClass:
      properties:
        deepfake_score:
          maximum: 1
          minimum: 0
          title: Deepfake Score
          type: integer
        prediction:
          allOf:
          - $ref: '#/components/schemas/ImagedeepfakeDetectionDeepfakeDetectionDataClassPredictionEnum'
          title: Prediction
        original_response:
          default: null
          description: original response sent by the provider, hidden by default, show it by passing the `show_original_response` field to `true` in your request
          title: Original Response
        status:
          allOf:
          - $ref: '#/components/schemas/StatusEnum'
          title: Status
      required:
      - deepfake_score
      - prediction
      - status
      title: imagedeepfake_detectionDeepfakeDetectionDataClass
      type: object
    imagedeepfake_detectionResponseModel:
      properties:
        resemble:
          $ref: '#/components/schemas/imagedeepfake_detectionDeepfakeDetectionDataClass'
          default: null
        sightengine:
          $ref: '#/components/schemas/imagedeepfake_detectionDeepfakeDetectionDataClass'
          default: null
      title: imagedeepfake_detectionResponseModel
      type: object
    NestedError:
      type: object
      properties:
        type:
          type: string
        message:
          type: string
      required:
      - message
      - type
    NestedBadRequest:
      type: object
      properties:
        type:
          type: string
        message:
          $ref: '#/components/schemas/FieldError'
      required:
      - message
      - type
  securitySchemes:
    FeatureApiAuth:
      type: http
      scheme: bearer
      bearerFormat: JWT