The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider removing the loading script and relying on automated data support (you can use convert_to_parquet from the datasets library). If this is not possible, please open a discussion for direct help.

Motivation

My goal is to build a dataset using Wild Sage Node captured images to help score LLMs that will be used with SAGE.

Origin

This dataset was forked from sagecontinuum/smokedataset

Data Instances

A data point comprises an image, its classification label, a prompt, and mulitple choices.

{
  'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=224x224 at 0x1215D0C50>,
  'label': 2,
  'prompt': 'What is shown in the image?',
  'choice': ['cloud', 'other', 'smoke']
}

Data Fields

  • image: A PIL.JpegImagePlugin.JpegImageFile object containing the image.
  • label: the expected class label of the image.
  • prompt: the prompt that will be sent to the LLM.
  • choice: the choices that the LLM can choose from.

Scoring

The multiple choice portion of the question is scored by overall accuracy (# of correctly answered questions/total questions). The question can also be open-ended by eliminating the choice portion.

Next Steps

More work is needed to figure out a scoring for open ended questions.

Citation

Dewangan A, Pande Y, Braun H-W, Vernon F, Perez I, Altintas I, Cottrell GW, Nguyen MH. FIgLib & SmokeyNet: Dataset and Deep Learning Model for Real-Time Wildland Fire Smoke Detection. Remote Sensing. 2022; 14(4):1007. https://doi.org/10.3390/rs14041007

Downloads last month
44