yolov8m-world-torch#

Detector understanding text descriptions to find matching objects in images.

Details

  • Model name: yolov8m-world-torch

  • Model source: https://docs.ultralytics.com/models/yolo-world/

  • Model author: Glenn Jocher, et al.

  • Model license: AGPL-3.0

  • Model size: 55.89 MB

  • Exposes embeddings? no

  • Tags: detection, torch, yolo, zero-shot, official

Requirements

  • Packages: torch>=1.7.0, torchvision>=0.8.1, ultralytics>=8.1.0

  • CPU support

    • yes

  • GPU support

    • yes

Example usage

 1import fiftyone as fo
 2import fiftyone.zoo as foz
 3
 4dataset = foz.load_zoo_dataset(
 5    "coco-2017",
 6    split="validation",
 7    dataset_name=fo.get_default_dataset_name(),
 8    max_samples=50,
 9    shuffle=True,
10)
11
12model = foz.load_zoo_model("yolov8m-world-torch")
13
14dataset.apply_model(model, label_field="predictions")
15
16session = fo.launch_app(dataset)
17
18#
19# Make zero-shot predictions with custom classes
20#
21
22model = foz.load_zoo_model(
23    "yolov8m-world-torch",
24    classes=["person", "dog", "cat", "bird", "car", "tree", "chair"],
25)
26
27dataset.apply_model(model, label_field="predictions")
28session.refresh()