---
library_name: YOLOv11
license: mit
tags:
- YOLO
- PyTorch
- object-detection
- dla
- generic
metrics:
- IoU
- F1
- AP@.5
- AP@.75
- AP@[.5,.95]
pipeline_tag: image-segmentation
version:
- YOLOv11
---

# YOLOv11 - Generic page detection

The generic page detection model predicts single pages from document images.

## Model description

The model has been trained using the YOLOv11 library on multiple datasets.
It has been trained on images with their dimensions equal to 640 pixels, starting from the YOLOv11l checkpoint.

## Evaluation results

The model achieves the following results:

| Set   | Images | Instances | Box-P | Box-R | Box-mAP@50 | Box-mAP@[50-95] | Mask-P | Mask-R | Mask-mAP@50 | Mask-mAP@[50-95] |
| ----- | ------ | --------- | ----- | ----- | ---------- | --------------- | ------ | ------ | ----------- | ---------------- |
| train | 1579   | 2210      | 0.999 | 0.996 | 0.995      | 0.994           | 0.999  | 0.996  | 0.995       | 0.993            |
| val   | 146    | 208       | 0.986 | 0.995 | 0.989      | 0.985           | 0.986  | 0.995  | 0.989       | 0.985            |
| test  | 144    | 215       | 0.995 | 1.00  | 0.995      | 0.994           | 0.995  | 1.00   | 0.995       | 0.991            |


## How to use?

- Download the [weights of this model](https://huggingface.co/Teklia/yolov11-generic-page/resolve/main/model.pt?download=true);
- Refer to the [Ultralytics documentation](https://docs.ultralytics.com/modes/predict/) to use this model.