{
  "opencollection": "1.0.0",
  "info": {
    "name": "Unitary content classification API Authentication Items & Characteristics API",
    "version": "1.0.0"
  },
  "items": [
    {
      "info": {
        "name": "Items & Characteristics",
        "type": "folder"
      },
      "items": [
        {
          "info": {
            "name": "Queue an image for Items & Characteristics classification",
            "type": "http"
          },
          "http": {
            "method": "POST",
            "url": "{{baseUrl}}/classify/items-characteristics/image",
            "body": {
              "type": "multipart-form",
              "data": []
            },
            "auth": {
              "type": "bearer",
              "token": "{{bearerToken}}"
            }
          },
          "docs": "This endpoint queues a job that predicts the Items & Characteristics categories of a single image.\n\nThe request must contain either a file (a multi-part form encoded image file) or a `url` form field (a string containing a URL to download the image file from).\n\nExample CURL:\n```\ncurl --location --request POST https://api.unitary.ai/v1/classify/items-characteristics/image --header \"Authorization: Bearer {API_TOKEN}\" --header \"Content-Type: multipart/form-data\" --form \"url={RESOURCE_URL}\"\n```\n\nA j"
        },
        {
          "info": {
            "name": "Retrieve the results of a queued Items & Characteristics classification",
            "type": "http"
          },
          "http": {
            "method": "GET",
            "url": "{{baseUrl}}/classify/items-characteristics/image/:job_id",
            "params": [
              {
                "name": "job_id",
                "value": "",
                "type": "path"
              }
            ],
            "auth": {
              "type": "bearer",
              "token": "{{bearerToken}}"
            }
          },
          "docs": "This endpoint returns the results of a previously queued classify job.\n\nThe response for each item is a prevalence score between 0 and 1 that represents how present it is in the content. 1 is highest prevalence and 0 is lowest prevalence.\n\nYou can use these scores in mappings or models to implement safety policies, for example setting a numerical threshold for automated flagging of content or in a linear regression model.\n\nNote that the score meaning and distribution is different for each item: "
        },
        {
          "info": {
            "name": "Queue a video for Items & Characteristics classification",
            "type": "http"
          },
          "http": {
            "method": "POST",
            "url": "{{baseUrl}}/classify/items-characteristics/video",
            "body": {
              "type": "multipart-form",
              "data": []
            },
            "auth": {
              "type": "bearer",
              "token": "{{bearerToken}}"
            }
          },
          "docs": "This endpoint queues a job that predicts the Items & Characteristics categories of a single video.\n\nThe request must contain either a file (a multi-part form encoded video file) or a `url` form field (a string containing a URL to download the video file from).\n\nExample CURL:\n```\ncurl --location --request POST https://api.unitary.ai/v1/classify/items-characteristics/video --header \"Authorization: Bearer {API_TOKEN}\" --header \"Content-Type: multipart/form-data\" --form \"url={RESOURCE_URL}\"\n```\n\nA j"
        },
        {
          "info": {
            "name": "Retrieve the results of a queued Items & Characteristics classification",
            "type": "http"
          },
          "http": {
            "method": "GET",
            "url": "{{baseUrl}}/classify/items-characteristics/video/:job_id",
            "params": [
              {
                "name": "job_id",
                "value": "",
                "type": "path"
              }
            ],
            "auth": {
              "type": "bearer",
              "token": "{{bearerToken}}"
            }
          },
          "docs": "This endpoint returns the results of a previously queued classify job.\n\nThe response for each item is a prevalence score between 0 and 1 that represents how present it is in the content. 1 is highest prevalence and 0 is lowest prevalence.\n\nYou can use these scores in mappings or models to implement safety policies, for example setting a numerical threshold for automated flagging of content or in a linear regression model.\n\nNote that the score meaning and distribution is different for each item: "
        }
      ]
    }
  ],
  "bundled": true
}