Datasets:
Tasks:
Image Segmentation
Formats:
parquet
Sub-tasks:
semantic-segmentation
Languages:
English
Size:
1K - 10K
License:
metadata
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
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
}