yoloev8s-seg-torch

Compact model producing outlines for objects described in words on edge devices.

Details

• Model name: yoloev8s-seg-torch

• Model source: https://docs.ultralytics.com/models/yoloe

• Model author: Glenn Jocher, et al.

• Model license: AGPL-3.0

• Model size: 29.69 MB

• Exposes embeddings? no

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

Requirements

• Packages: torch>=1.7.0, torchvision>=0.8.1, ultralytics>=8.3.99

• CPU support

  • yes

• GPU support

  • yes

Example usage

import fiftyone as fo
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset(
    "coco-2017",
    split="validation",
    dataset_name=fo.get_default_dataset_name(),
    max_samples=50,
    shuffle=True,
)

model = foz.load_zoo_model("yoloev8s-seg-torch")

dataset.apply_model(model, label_field="predictions")

session = fo.launch_app(dataset)

#
# Make zero-shot predictions with custom classes
#

model = foz.load_zoo_model(
    "yoloev8s-seg-torch",
    classes=["person", "dog", "cat", "bird", "car", "tree", "chair"],
)

dataset.apply_model(model, label_field="predictions")
session.refresh()