metadata
license: agpl-3.0
library: ultralytics
tags:
- object-detection
- pytorch
- coco
- p2-layer
- yolo11
- yolov11
- yolox11-p2
- yolovx11-p2
YOLO11-p2 COCO Pretrained Model
This model is a YOLO11-p2 model trained on the COCO dataset, with P2-P5 output layers.
Example Usage
from huggingface_hub import hf_hub_download
from ultralytics import YOLO
from PIL import Image
model_path = hf_hub_download("soyeollee/yolo11x-p2-coco", "model.pt")
model = YOLO(model_path)
image_path = "/path/to/image"
output = model(Image.open(image_path))
Performance
| metric (maxDets=100) | yolov8x (official) |
yolov8x-p2 | yolov8x-p26 | yolov11x (official) |
yolo11x-p2 (this repo) |
|---|---|---|---|---|---|
| AP @[ IoU=0.50:0.95 / area= all ] | 0.540 | 0.541 | 0.544 | 0.546 | 0.553 |
| AP @[ IoU=0.50 / area= all ] | 0.710 | 0.712 | 0.713 | 0.716 | 0.722 |
| AP @[ IoU=0.75 / area= all ] | 0.588 | 0.590 | 0.593 | 0.595 | 0.606 |
| AP @[ IoU=0.50:0.95 / area= small ] | 0.360 | 0.386 | 0.381 | 0.377 | 0.386 |
| AP @[ IoU=0.50:0.95 /area=medium ] | 0.594 | 0.586 | 0.586 | 0.597 | 0.595 |
| AP @[ IoU=0.50:0.95 / area= large ] | 0.707 | 0.686 | 0.691 | 0.702 | 0.702 |