metadata

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
      num_examples: 272
    - name: valid
      num_bytes: 210925170
      num_examples: 360
  download_size: 365017887
  dataset_size: 365062301

XAMI: XMM-Newton optical Artefact Mapping for astronomical Instance segmentation

The Dataset

Check the XAMI model and the XAMI dataset on Github.

Downloading the dataset

using a python script

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:

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.