| # Scripts for training Layout Detection Models using Detectron2 | |
| ## Usage | |
| - In `tools/`, we provide a series of handy scripts for converting data formats and training the models. | |
| - In `scripts/`, it lists specific command for running the code for processing the given dataset. | |
| - The `configs/` contains the configuration for different deep learning models, and is organized by datasets. | |
| ## Supported Datasets | |
| - Prima Layout Analysis Dataset [`scripts/train_prima.sh`](https://github.com/Layout-Parser/layout-model-training/blob/master/scripts/train_prima.sh) | |
| - You will need to download the dataset from the [official website](https://www.primaresearch.org/dataset/) and put it in the `data/prima` folder. | |
| - As the original dataset is stored in the [PAGE format](https://www.primaresearch.org/tools/PAGEViewer), the script will use [`tools/convert_prima_to_coco.py`](https://github.com/Layout-Parser/layout-model-training/blob/master/tools/convert_prima_to_coco.py) to convert it to COCO format. | |
| - The final dataset folder structure should look like: | |
| ```bash | |
| data/ | |
| └── prima/ | |
| ├── Images/ | |
| ├── XML/ | |
| ├── License.txt | |
| └── annotations*.json | |
| ``` | |
| ## Reference | |
| - **[cocosplit](https://github.com/akarazniewicz/cocosplit)** A script that splits the coco annotations into train and test sets. | |
| - **[Detectron2](https://github.com/facebookresearch/detectron2)** Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. |