JCTN
/

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
hand_yolov8n.pt 2D / realistic hand 0.767 0.505
hand_yolov8s.pt 2D / realistic hand 0.794 0.527
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

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Datasets used to train JCTN/adetailer