README.md

---
size_categories:
- 1K<N<10K
source_datasets:
- original
task_categories:
- image-segmentation
task_ids:
- instance-segmentation
pretty_name: XAMI-dataset
tags:
- COCO format
- Astronomy
- XMM-Newton
- CC BY-NC 3.0 IGO
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: valid
    path: data/valid-*
dataset_info:
  features:
  - name: observation id
    dtype: string
  - name: segmentation
    dtype: image
  - name: bbox
    dtype: image
  - name: label
    dtype: string
  - name: area
    dtype: string
  - name: image shape
    dtype: string
  splits:
  - name: train
    num_bytes: 154137131.0
    num_examples: 272
  - name: valid
    num_bytes: 210925170.0
    num_examples: 360
  download_size: 365017887
  dataset_size: 365062301.0
---

<div align="center">
<h1> XAMI: XMM-Newton optical Artefact Mapping for astronomical Instance segmentation </h1>
<i> The Dataset </i>
</div>

Check the **[XAMI model](https://github.com/ESA-Datalabs/XAMI-model)** and the **[XAMI dataset](https://github.com/ESA-Datalabs/XAMI-dataset)** on Github. 

# Downloading the dataset

- using a python script

```python
from huggingface_hub import hf_hub_download

dataset_name = 'xami_dataset' # the dataset name of Huggingface
images_dir = '.' # the output directory of the dataset images

hf_hub_download(
    repo_id="iulia-elisa/XAMI-dataset", # the Huggingface repo ID
    repo_type='dataset', 
    filename=dataset_name+'.zip', 
    local_dir=images_dir
);

# Unzip file
!unzip -q "xami_dataset.zip" -d 'path/to/dest'
```

Or you can simply download only the dataset zip file from HuggingFace using a CLI command:

```bash
DEST_DIR='/path/to/local/dataset/dir'

huggingface-cli download iulia-elisa/XAMI-dataset xami_dataset.zip --repo-type dataset --local-dir "$DEST_DIR" && unzip "$DEST_DIR/xami_dataset.zip" -d "$DEST_DIR" && rm "$DEST_DIR/xami_dataset.zip"
```

## Licence 
**[CC BY-NC 3.0 IGO](https://creativecommons.org/licenses/by-nc/3.0/igo/deed.en).**