PyTorch
ultralytics

YOLOv8 Detection Model

Datasets

Face

Hand

Person

deepfashion2

id label
0 short_sleeved_shirt
1 long_sleeved_shirt
2 short_sleeved_outwear
3 long_sleeved_outwear
4 vest
5 sling
6 shorts
7 trousers
8 skirt
9 short_sleeved_dress
10 long_sleeved_dress
11 vest_dress
12 sling_dress

Info

Model Target mAP 50 mAP 50-95
face_yolov8n.pt 2D / realistic face 0.660 0.366
face_yolov8n_v2.pt 2D / realistic face 0.669 0.372
face_yolov8s.pt 2D / realistic face 0.713 0.404
face_yolov8m.pt 2D / realistic face 0.737 0.424
face_yolov9c.pt 2D / realistic face 0.748 0.433
hand_yolov8n.pt 2D / realistic hand 0.767 0.505
hand_yolov8s.pt 2D / realistic hand 0.794 0.527
hand_yolov9c.pt 2D / realistic hand 0.810 0.550
person_yolov8n-seg.pt 2D / realistic person 0.782 (bbox)
0.761 (mask)
0.555 (bbox)
0.460 (mask)
person_yolov8s-seg.pt 2D / realistic person 0.824 (bbox)
0.809 (mask)
0.605 (bbox)
0.508 (mask)
person_yolov8m-seg.pt 2D / realistic person 0.849 (bbox)
0.831 (mask)
0.636 (bbox)
0.533 (mask)
deepfashion2_yolov8s-seg.pt realistic clothes 0.849 (bbox)
0.840 (mask)
0.763 (bbox)
0.675 (mask)

Usage

from huggingface_hub import hf_hub_download
from ultralytics import YOLO

path = hf_hub_download("Bingsu/adetailer", "face_yolov8n.pt")
model = YOLO(path)
import cv2
from PIL import Image

img = "https://farm5.staticflickr.com/4139/4887614566_6b57ec4422_z.jpg"
output = model(img)
pred = output[0].plot()
pred = cv2.cvtColor(pred, cv2.COLOR_BGR2RGB)
pred = Image.fromarray(pred)
pred

image

Unsafe files

image

Since getattr is classified as a dangerous pickle function, any segmentation model that uses it is classified as unsafe.

All models were created and saved using the official ultralytics library, so it's okay to use files downloaded from a trusted source.

See also: https://huggingface.co./docs/hub/security-pickle

Downloads last month

-

Downloads are not tracked for this model. How to track
Inference API
Unable to determine this model’s pipeline type. Check the docs .

Datasets used to train Bingsu/adetailer

Spaces using Bingsu/adetailer 5