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Add documentation for prima training
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# 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/
β”œβ”€β”€ Images/
β”œβ”€β”€ XML/
β”œβ”€β”€ 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.