YOLO-World

YOLO-World is a zero-shot object detection model that allows you to perform object detection without any training, just by describing the items you want to detect.

You can also run YOLO-World locally using Inference, our open-source inference server.

API Reference

The base URL for our hosted API is at https://infer.roboflow.com.

More information on using YOLO-World with Inference, through the Python SDK or the self-hosted API, see the YOLO-World Inference docs page.

YOLO-World inference.

post

Run the YOLO-World zero-shot object detection model.

Query parameters

api_keyany ofOptional

Roboflow API Key that will be passed to the model during initialization for artifact retrieval

stringOptional

or

nullOptional

countinferenceany ofOptional

booleanOptional

or

nullOptional

service_secretany ofOptional

stringOptional

or

nullOptional

Body

application/json

Request for Grounding DINO zero-shot predictions.

Attributes: text (List[str]): A list of strings.

idstringRequired

api_keyany ofOptional

Roboflow API Key that will be passed to the model during initialization for artifact retrieval

stringOptional

or

nullOptional

usage_billablebooleanOptionalDefault: true

startany ofOptional

numberOptional

or

nullOptional

sourceany ofOptional

stringOptional

or

nullOptional

source_infoany ofOptional

stringOptional

or

nullOptional

disable_model_monitoringany ofOptional

If true, disables model monitoring for this request

Default: false

booleanOptional

or

nullOptional

model_idany ofOptional

stringOptional

or

nullOptional

model_typeany ofOptional

The type of the model, usually referring to what task the model performs

Example: object-detection

stringOptional

or

nullOptional

imageany ofRequired

or

disable_preproc_auto_orientany ofOptional

If true, the auto orient preprocessing step is disabled for this call.

Default: false

booleanOptional

or

nullOptional

disable_preproc_contrastany ofOptional

If true, the auto contrast preprocessing step is disabled for this call.

Default: false

booleanOptional

or

nullOptional

disable_preproc_grayscaleany ofOptional

If true, the grayscale preprocessing step is disabled for this call.

Default: false

booleanOptional

or

nullOptional

disable_preproc_static_cropany ofOptional

If true, the static crop preprocessing step is disabled for this call.

Default: false

booleanOptional

or

nullOptional

textstring[]Required

A list of strings

Example: ["person","dog","cat"]

yolo_world_version_idany ofOptionalDefault: l

stringOptional

or

nullOptional

confidenceany ofOptionalDefault: 0.4

numberOptional

or

nullOptional

Responses

200

Successful Response

application/json

Object Detection inference response.

Attributes: predictions (List[inference.core.entities.responses.inference.ObjectDetectionPrediction]): List of object detection predictions.

visualizationany ofOptional

Base64 encoded string containing prediction visualization image data

stringOptional

or

nullOptional

inference_idany ofOptional

Unique identifier of inference

stringOptional

or

nullOptional

frame_idany ofOptional

The frame id of the image used in inference if the input was a video

integerOptional

or

nullOptional

timeany ofOptional

The time in seconds it took to produce the predictions including image preprocessing

numberOptional

or

nullOptional

imageany ofRequired

or

422

Validation Error

application/json

post

/yolo_world/infer

HTTPcURLJavaScriptPython

POST /yolo_world/infer HTTP/1.1
Content-Type: application/json
Accept: */*
Content-Length: 464

{
  "id": "text",
  "api_key": "text",
  "usage_billable": true,
  "start": 1,
  "source": "text",
  "source_info": "text",
  "disable_model_monitoring": false,
  "model_id": "text",
  "model_type": "object-detection",
  "image": [
    {
      "type": "url",
      "value": "http://www.example-image-url.com"
    }
  ],
  "disable_preproc_auto_orient": false,
  "disable_preproc_contrast": false,
  "disable_preproc_grayscale": false,
  "disable_preproc_static_crop": false,
  "text": [
    "person",
    "dog",
    "cat"
  ],
  "yolo_world_version_id": "l",
  "confidence": 0.4
}

{
  "visualization": "text",
  "inference_id": "text",
  "frame_id": 1,
  "time": 1,
  "image": [
    {
      "width": 1,
      "height": 1
    }
  ],
  "predictions": [
    {
      "x": 1,
      "y": 1,
      "width": 1,
      "height": 1,
      "confidence": 1,
      "class": "text",
      "class_confidence": 1,
      "class_id": 1,
      "tracker_id": 1,
      "detection_id": "text",
      "parent_id": "text"
    }
  ]
}