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---
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
```angular2html
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 <br/>(official) | [yolov8x-p2](https://huggingface.co/soyeollee/yolov8x-p2-coco) | [yolov8x-p26](https://huggingface.co/soyeollee/yolov8x-p26-coco) | yolov11x <br/>(official) | yolo11x-p2<br/>(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 |
|