hugging-mac/yolov8-pose-coreml

YOLOv8 Pose — Core ML

Ready-to-use Core ML conversions of Ultralytics YOLOv8 Pose for human pose estimation on Apple Silicon. The n, s, and m variants are provided as .mlpackage models for use with the CPU, GPU, and Apple Neural Engine.

These models power pose-driven apps and games in Hugging Mac, an open-source platform for building local AI experiences on macOS.

Models

Variant	Package size	Best for
yolov8n-pose	6.8 MB	Lowest latency and resource usage
yolov8s-pose	23.5 MB	Balanced speed and accuracy
yolov8m-pose	53.2 MB	Higher accuracy

Provenance and conversion

• Source: Ultralytics assets v8.2.0
• Task: person detection and COCO 17-keypoint pose estimation
• Input size: fixed 640 × 640, batch size 1
• Precision: FP16 conversion
• NMS: not embedded; apply confidence filtering and NMS after inference

Input and output

Name	Type	Shape	Description
image	RGB image	640 × 640	Letterboxed model input
predictions	FP32 multi-array	1 × 56 × 8400	Boxes, person scores, and 17 keypoints (x, y, visibility)

Core ML example

from pathlib import Path

import coremltools as ct
from huggingface_hub import snapshot_download
from PIL import Image, ImageOps

root = Path(snapshot_download(
    repo_id="hugging-mac/yolov8-pose-coreml",
    allow_patterns=["yolov8n-pose.mlpackage/**"],
))
model = ct.models.MLModel(
    root / "yolov8n-pose.mlpackage",
    compute_units=ct.ComputeUnit.ALL,
)
image = ImageOps.pad(
    Image.open("person.jpg").convert("RGB"),
    (640, 640),
    color=(114, 114, 114),
)
predictions = model.predict({"image": image})["predictions"]
print(predictions.shape)  # (1, 56, 8400)

The output is raw. See the Hugging Mac YOLOv8 Pose SDK for complete preprocessing, NMS, keypoint decoding, and coordinate restoration.

Integrity

Package	Directory SHA-256
yolov8n-pose.mlpackage	84d3154a02c99307ec9e5bab023551eaa4cd16660d61b61fc361ac3c760eb863
yolov8s-pose.mlpackage	660389b72cf309e66af18fdafe80d1c719809921b77ea2d417b76686cf44801c
yolov8m-pose.mlpackage	da9a330d271eac5b1b740b2b78b2fbcc3a3406a5e5d25cb459afd122d091092a

License

The converted models retain the upstream Ultralytics licensing terms and are published under AGPL-3.0. Review Ultralytics licensing requirements before commercial or closed-source use. Hugging Mac is not affiliated with or endorsed by Ultralytics.