README.md

metadata

annotations_creators:
  - human-curator
language:
  - en
license:
  - mit
pretty_name: RockGlacier
size_categories:
  - 1K<n<10K
source_datasets:
  - original
task_categories:
  - image-classification
task_ids:
  - multi-class-image-classification

Dataset Card for Rock Glacier Detection

Table of Contents

• Table of Contents
• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: RockGlacier Homepage
• Repository: alcazar90/rock-glacier-detection
• Paper: N/A
• Leaderboard: N/A
• Point of Contact: N/A

Dataset Summary

Rock Glacier Detection dataset with satelital images of rock glaciers in the Chilean Andes.

Supported Tasks and Leaderboards

• image-classification: Based on a satelitel images (from sentinel2), the goal of this task is to predict a rock glacier in the geographic area, if there any.
• image-segmentation: ...

Languages

Spanish

Dataset Structure

Data Instances

A sample from the image-classification training set is provided below:

df = load_dataset("alkzar90/rock-glacier-dataset", name="image-classification")

df["train"][666]

> {'image': <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=128x128 at 0x7FB2EC58C6D0>,
 'labels': 0,
 'path': 'train/cordillera/1512.png'
}

A sample from the image-segmentation training set is provided below:

df = load_dataset("alkzar90/rock-glacier-dataset", name="image-segmentation")

df["train"][666]

> {'image': <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=128x128 at 0x7FB2EB7C1160>,
 'masks': <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=128x128 at 0x7FB2EC5A08E0>,
 'path': 'train/cordillera/1512.png'}

Data Fields

The data instances have the following fields:

• image: A PIL.Image.Image object containing the image. Note that when accessing the image column: dataset[0]["image"] the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. dataset[0]["image"] should always be preferred over dataset["image"][0].
• labels: an int classification label.

Class Label Mappings:

{
  "cordillera": 0
  "glaciar": 1,
}

Data Splits

	train	validation	test
# of examples	7875	1125	2700

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

@ONLINE {rock-glacier-dataset,
    author="CMM - Glaciares (UChile)",
    title="Rock Glacier Dataset",
    month="October",
    year="2022",
    url="https://github.com/alcazar90/rock-glacier-detection"
}

Contributions

Thanks to...