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YOLO-World Model

Version v1

Run YOLO-World, a zero-shot object detection model, on an image.

YOLO-World accepts one or more text classes you want to identify in an image. The model returns the location of objects that meet the specified class, if YOLO-World is able to identify objects of that class.

We recommend experimenting with YOLO-World to evaluate the model on your use case before using this block in production. For example on how to effectively prompt YOLO-World, refer to the Roboflow YOLO-World prompting guide.

Type identifier

Use the following identifier in step "type" field: roboflow_core/yolo_world_model@v1to add the block as as step in your workflow.

Properties

Name Type Description Refs
name str The unique name of this step.. ❌
class_names List[str] One or more classes that you want YOLO-World to detect. The model accepts any string as an input, though does best with short descriptions of common objects.. ✅
version str Variant of YoloWorld model. ✅
confidence float Confidence threshold for detections. ✅

The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.

Available Connections

Check what blocks you can connect to YOLO-World Model in version v1.

The available connections depend on its binding kinds. Check what binding kinds YOLO-World Model in version v1 has.

Bindings

  • input

    • images (image): The image to infer on.
    • class_names (list_of_values): One or more classes that you want YOLO-World to detect. The model accepts any string as an input, though does best with short descriptions of common objects..
    • version (string): Variant of YoloWorld model.
    • confidence (float_zero_to_one): Confidence threshold for detections.

  • output

Example JSON definition of step YOLO-World Model in version v1 
{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/yolo_world_model@v1",
    "images": "$inputs.image",
    "class_names": [
        "person",
        "car",
        "license plate"
    ],
    "version": "v2-s",
    "confidence": 0.005
}