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.

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

post

/yolo_world/infer

Query parameters

api_keyany of

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

Body

idstringrequired

api_keyany of

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

usage_billableboolean · default: true

startany of

sourceany of

source_infoany of

model_idany of

model_typeany of

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

Example: object-detection

imageany ofrequired

Image data for inference request.

Attributes: type (str): The type of image data provided, one of 'url', 'base64', or 'numpy'. value (Optional[Any]): Image data corresponding to the image type.

Image data for inference request.

Attributes: type (str): The type of image data provided, one of 'url', 'base64', or 'numpy'. value (Optional[Any]): Image data corresponding to the image type.

disable_preproc_auto_orientany of · default: false

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

disable_preproc_contrastany of · default: false

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

disable_preproc_grayscaleany of · default: false

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

disable_preproc_static_cropany of · default: false

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

textstring[]required

A list of strings

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

yolo_world_version_idany of · default: l

confidenceany of · default: 0.4

Responses

application/json

application/json

cURL

JavaScript

Python

HTTP

cURL

curl -L \
  --request POST \
  --url '/yolo_world/infer' \
  --header 'Content-Type: application/json' \
  --data '{
    "id": "text",
    "api_key": "text",
    "usage_billable": true,
    "start": 1,
    "source": "text",
    "source_info": "text",
    "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
  }'

200

422

200

{
  "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"
    }
  ]
}

Successful Response