README.md

---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- image-classification
task_ids:
- multi-class-image-classification
pretty_name: domarks16k
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': aec
          '1': ael
          '2': cli
          '3': cra
          '4': fse
          '5': fsf
          '6': fsg
          '7': fss
          '8': mix
          '9': rid
          '10': rou
          '11': sfe
          '12': sfx
          '13': smo
          '14': tex
---

# domarks16k

A Mars image classification dataset for planetary science research.

## Dataset Metadata

* **License:** CC-BY-4.0 (Creative Commons Attribution 4.0 International)
* **Version:** 1.0
* **Date Published:** 2025-05-09
* **Cite As:** TBD

## Classes

This dataset contains the following classes:

- 0: aec
- 1: ael
- 2: cli
- 3: cra
- 4: fse
- 5: fsf
- 6: fsg
- 7: fss
- 8: mix
- 9: rid
- 10: rou
- 11: sfe
- 12: sfx
- 13: smo
- 14: tex

## Statistics

- **train**: 11305 images
- **test**: 1614 images
- **val**: 3231 images
- **few_shot_train_5_shot**: 75 images
- **partition_train_0.02x**: 225 images

## Few-shot Splits

This dataset includes the following few-shot training splits:

- **few_shot_train_5_shot**: 75 images

Few-shot configurations:

- **5_shot.json**
## Partition Splits

This dataset includes the following training data partitions:

- **partition_train_0.02x**: 225 images

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("gremlin97/domarks16k")
```

## Format

Each example in the dataset has the following format:

```
{
  'image': Image(...),  # PIL image
  'label': int,         # Class label
}
```