---
license: unknown
library_name: ultralytics
---

# DocLayout-YOLO — Model Checkpoints

Official checkpoints for **DocLayout-YOLO**, a document-specialized real-time detector built on YOLOv12 with Page-Axis Layout Attention (PALA) and mesh-guided synthetic pretraining.

## Checkpoints

**Pretrained models** (for fine-tuning on your own layout datasets), trained on large-scale synthetic document pretraining data:

- [DocLayout-YOLO-pretrain-N.pt](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/DocLayout-YOLO-pretrain-N.pt)
- [DocLayout-YOLO-pretrain-S.pt](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/DocLayout-YOLO-pretrain-S.pt)
- [DocLayout-YOLO-pretrain-M.pt](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/DocLayout-YOLO-pretrain-M.pt)
- [DocLayout-YOLO-pretrain-L.pt](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/DocLayout-YOLO-pretrain-L.pt)
- [DocLayout-YOLO-pretrain-X.pt](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/DocLayout-YOLO-pretrain-X.pt)

**Downstream models** (fine-tuned on four public document-layout benchmarks, five model sizes each), under [`downstream/`](./tree/main/downstream):

- [`downstream/D4LA/`](./tree/main/downstream/D4LA) · [`downstream/M6Doc/`](./tree/main/downstream/M6Doc) · [`downstream/HJDataset/`](./tree/main/downstream/HJDataset) · [`downstream/PRIMA-LAD/`](./tree/main/downstream/PRIMA-LAD)

**General-purpose model** (22 fine-grained layout categories, drop-in front-end for document parsing pipelines):

- [DocLayout-YOLO-universal.pt](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/universal/DocLayout-YOLO-universal.pt)

Quick inference:

```python
from ultralytics import YOLO

model = YOLO("DocLayout-YOLO-universal.pt")  # download from the link above
results = model.predict("page.png", imgsz=1024, conf=0.25, iou=0.5, verbose=False)
results[0].save(filename="result.jpg")
```

Or try it online without any setup: [Online Demo (ModelScope)](https://www.modelscope.cn/studios/JulioZhao97/DocLayout-YOLO-demo).

## Main Results (mAP50-95)

| Model | D4LA | M6Doc | HJDataset | PRIMA-LAD |
| :-- | :-: | :-: | :-: | :-: |
| n | [67.2](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/D4LA/n_DocLayout-YOLO.pt) | [66.2](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/M6Doc/n_DocLayout-YOLO.pt) | [93.6](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/HJDataset/n_DocLayout-YOLO.pt) | [67.7](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/PRIMA-LAD/n_DocLayout-YOLO.pt) |
| s | [70.6](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/D4LA/s_DocLayout-YOLO.pt) | [71.1](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/M6Doc/s_DocLayout-YOLO.pt) | [94.8](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/HJDataset/s_DocLayout-YOLO.pt) | [70.3](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/PRIMA-LAD/s_DocLayout-YOLO.pt) |
| m | [70.7](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/D4LA/m_DocLayout-YOLO.pt) | [73.3](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/M6Doc/m_DocLayout-YOLO.pt) | [95.3](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/HJDataset/m_DocLayout-YOLO.pt) | [71.3](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/PRIMA-LAD/m_DocLayout-YOLO.pt) |
| l | [72.4](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/D4LA/l_DocLayout-YOLO.pt) | [75.1](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/M6Doc/l_DocLayout-YOLO.pt) | [95.7](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/HJDataset/l_DocLayout-YOLO.pt) | [73.4](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/PRIMA-LAD/l_DocLayout-YOLO.pt) |
| x | [72.4](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/D4LA/x_DocLayout-YOLO.pt) | [75.5](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/M6Doc/x_DocLayout-YOLO.pt) | [96.0](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/HJDataset/x_DocLayout-YOLO.pt) | [73.1](https://huggingface.co/juliozhao/DocLayout-YOLO/resolve/main/downstream/PRIMA-LAD/x_DocLayout-YOLO.pt) |

Click a score to download the corresponding checkpoint.

## Datasets

The four downstream benchmarks are released as separate dataset repositories, each a YOLO-layout dataset directory (`images/`, `labels/`, split lists `train.txt` / `val.txt` / `test.txt`):

| dataset | repository | pages |
|:--|:--|:--|
| D4LA | [juliozhao/D4LA](https://huggingface.co/datasets/juliozhao/D4LA) | 22,184 |
| M6Doc | [juliozhao/M6Doc](https://huggingface.co/datasets/juliozhao/M6Doc) | 17,252 |
| HJDataset | [juliozhao/HJDataset](https://huggingface.co/datasets/juliozhao/HJDataset) | 4,012 |
| PRIMA-LAD | [juliozhao/PRIMA-LAD](https://huggingface.co/datasets/juliozhao/PRIMA-LAD) | 956 |

### Download

```python
# pip install huggingface_hub
from huggingface_hub import snapshot_download

for repo, local in [
    ("juliozhao/D4LA",      "D4LA"),        # keep these exact directory names
    ("juliozhao/M6Doc",     "m6doc"),       # (the val/train scripts depend on them)
    ("juliozhao/HJDataset", "HJDataset"),
    ("juliozhao/PRIMA-LAD", "prima-lad"),
]:
    snapshot_download(repo, repo_type="dataset", local_dir=local)
```

Each repository is ready to use as-is: the split lists point to the actual file locations, so no post-processing is needed after download.

## Usage

The `val.py` / `train.py` scripts referenced below ship in the release package. Typical flows:

**Validation** (dataset root = the parent directory holding the four dataset folders):

```bash
python val.py --model downstream/PRIMA-LAD/s_DocLayout-YOLO.pt \
  --data prima-lad --dataset-root /absolute/path/to/datasets
```

`--data` accepts one of the dataset aliases `d4la` | `m6doc` | `hjdataset` | `prima-lad`.

**Fine-tuning** from a pretrained checkpoint:

```bash
python train.py --data ultralytics/cfg/datasets/D4LA.yaml \
  --pretrain DocLayout-YOLO-pretrain-X.pt \
  --epoch 500 --image-size 1600 --batch-size 64 --project runs
```

**Prediction**:

```python
from ultralytics import YOLO

model = YOLO("downstream/M6Doc/m_DocLayout-YOLO.pt")
results = model.predict("page.png", imgsz=1600, conf=0.25, device="cuda:0")
results[0].save(filename="result.jpg")
```

## SHA256 (first 16 hex chars)

| repo path | sha256 (16) | size (MB) |
|---|---|---|
| `DocLayout-YOLO-pretrain-N.pt` | `178a9ff51e3cd848` | 9.6 |
| `DocLayout-YOLO-pretrain-S.pt` | `f203c9d02740a549` | 35.8 |
| `DocLayout-YOLO-pretrain-M.pt` | `bfbec6286ef2f659` | 79.3 |
| `DocLayout-YOLO-pretrain-L.pt` | `da336fad052f7ff2` | 107.0 |
| `DocLayout-YOLO-pretrain-X.pt` | `fe0d4daef3d14c8a` | 238.6 |
| `downstream/D4LA/n_DocLayout-YOLO.pt` | `ddc1189beed91e27` | 5.0 |
| `downstream/D4LA/s_DocLayout-YOLO.pt` | `a1d0f8efe22580f3` | 18.2 |
| `downstream/D4LA/m_DocLayout-YOLO.pt` | `ecff5e042e03626b` | 39.9 |
| `downstream/D4LA/l_DocLayout-YOLO.pt` | `826ec4281d1064a2` | 53.9 |
| `downstream/D4LA/x_DocLayout-YOLO.pt` | `fa1d38605ee26115` | 119.8 |
| `downstream/M6Doc/n_DocLayout-YOLO.pt` | `62e3c9352a050769` | 5.0 |
| `downstream/M6Doc/s_DocLayout-YOLO.pt` | `7ce579090a2a0d51` | 18.1 |
| `downstream/M6Doc/m_DocLayout-YOLO.pt` | `e0b3f0356ed4bb6e` | 40.0 |
| `downstream/M6Doc/l_DocLayout-YOLO.pt` | `f4cf7b8e56978ade` | 53.9 |
| `downstream/M6Doc/x_DocLayout-YOLO.pt` | `bddd9e3ebb10a412` | 119.8 |
| `downstream/HJDataset/n_DocLayout-YOLO.pt` | `1099870f0b82c01f` | 5.0 |
| `downstream/HJDataset/s_DocLayout-YOLO.pt` | `6044020c8f13d5de` | 18.2 |
| `downstream/HJDataset/m_DocLayout-YOLO.pt` | `65cf6375760cb08b` | 39.9 |
| `downstream/HJDataset/l_DocLayout-YOLO.pt` | `5878bc467353c810` | 53.9 |
| `downstream/HJDataset/x_DocLayout-YOLO.pt` | `7dd575f4115537ea` | 119.7 |
| `downstream/PRIMA-LAD/n_DocLayout-YOLO.pt` | `f21f9a798a021374` | 5.0 |
| `downstream/PRIMA-LAD/s_DocLayout-YOLO.pt` | `4e9177b75a3c825c` | 18.2 |
| `downstream/PRIMA-LAD/m_DocLayout-YOLO.pt` | `1fcccb0f9273d83a` | 39.9 |
| `downstream/PRIMA-LAD/l_DocLayout-YOLO.pt` | `38fb188c3567d033` | 53.9 |
| `downstream/PRIMA-LAD/x_DocLayout-YOLO.pt` | `d79b8c6f9af4e47a` | 119.7 |
| `universal/DocLayout-YOLO-universal.pt` | `5c733afe7481aea1` | 119.6 |

## License

The source code is distributed under the GNU Affero General Public License v3.0 (AGPL-3.0).

## Citation

```BibTeX
@misc{zhao2024doclayoutyoloenhancingdocumentlayout,
      title={DocLayout-YOLO: Enhancing Document Layout Analysis through Diverse Synthetic Data and Global-to-Local Adaptive Perception},
      author={Zhiyuan Zhao and Hengrui Kang and Bin Wang and Conghui He},
      year={2024},
      eprint={2410.12628},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2410.12628},
}
```