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-segmentation
task_ids:
- semantic-segmentation
pretty_name: crater_binary_segmentation
---

# crater_binary_segmentation

A segmentation dataset for planetary science applications.

## Dataset Metadata

* **License:** CC-BY-4.0 (Creative Commons Attribution 4.0 International)
* **Version:** 1.0
* **Date Published:** 2025-05-11
* **Cite As:** TBD

## Classes

This dataset contains the following classes:

- 0: Background
- 1: Crater

## Directory Structure

The dataset follows this structure:

```
dataset/
  ├── train/
  │   ├── images/  # Image files
  │   └── masks/   # Segmentation masks
  ├── val/
  │   ├── images/  # Image files
  │   └── masks/   # Segmentation masks
  ├── test/
  │   ├── images/  # Image files
  │   └── masks/   # Segmentation masks
```

## Statistics

- train: 3600 images
- val: 900 images
- test: 900 images

## Usage

```python
from datasets import load_dataset

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

## Format

Each example in the dataset has the following format:

```
{
  'image': Image(...),      # PIL image
  'mask': Image(...),       # PIL image of the segmentation mask
  'width': int,             # Width of the image
  'height': int,            # Height of the image
  'class_labels': [str,...] # List of class names present in the mask
}
```