Datasets:

imageomics
/

Curated_GoldStandard_Hoyal_Cuthill

	---
	license: cc0-1.0
	task_categories:
	- image-classification
	tags:
	- butterfly
	- heliconius erato
	- heliconius melpomene
	- full body
	- dorsal
	- RGB
	- bird view
	- butterfly view
	- bird acuity
	- butterfly acuity
	- imbalanced
	- mimicry
	- cv
	pretty_name: Curated Gold Standard Cuthill Dataset
	size_categories:
	- n<1K
	---
	# Dataset Card for Curated Gold Standard Cuthill Dataset

	Test change.

	## Dataset Description
	Dorsal full body images of subspecies of Heliconius Erato and Heliconius Melpomene (18 subspecies total).
	960 images with 320 specimens, each photographed in RGB with bird and butterfly acuity included (3 images of each specimen).
	Subset of images processed from Cuthill, et. al. dataset available at [doi:10.5061/dryad.2hp1978](https://doi.org/10.5061/dryad.2hp1978).

	Note: `dorsal_images_cuthill` contains processed dorsal images from the original Cuthill dataset (all 1,234 specimens).

	- Homepage:
	- Repository: [Butterfly-mimicry](https://github.com/Imageomics/Butterfly-mimicry) contains research done using this dataset.
	- Paper:
	- Leaderboard:
	- Point of Contact:

	### Dataset Summary

	![Distribution Summary](https://huggingface.co/datasets/imageomics/Curated_GoldStandard_Hoyal_Cuthill/resolve/main/Curated_GS_Cuthill_Distribution_Snapshot.png)

	<!---
	This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
	--->

	### Supported Tasks and Leaderboards

	[More Information Needed]

	### Languages

	English

	## Dataset Structure

	```
	\|-- dorsal_images_cuthill
	\| \|
	\| \|-- 10427965_D_lowres.tif
	\| \|
	\| \|-- 10427966_D_lowres.tif
	\| \|
	\| \| ...
	\|
	\|-- Acuities
	\| \|
	\| \|-- train_bird
	\| \| \|
	\| \| \|-- erato_cyrbia
	\| \| \|
	\| \| \|-- erato_etylus
	\| \| \|
	\| \| \| ...
	\| \|
	\| \|-- test_bird
	\| \| \|
	\| \| \|-- erato_cyrbia
	\| \| \|
	\| \| \|-- erato_etylus
	\| \| \|
	\| \| \| ...
	\| \|
	\| \|-- train_butterfly
	\| \| \|
	\| \| \|-- erato_cyrbia
	\| \| \|
	\| \| \|-- erato_etylus
	\| \| \|
	\| \| \| ...
	\| \|
	\| \|-- test_butterfly
	\| \|
	\| \|-- erato_cyrbia
	\| \|
	\| \|-- erato_etylus
	\| \|
	\| \| ...
	\|
	\|-- train
	\| \|
	\| \|-- erato_cyrbia
	\| \|
	\| \|-- erato_etylus
	\| \|
	\| \| ...
	\|
	\|-- test
	\|
	\|-- erato_cyrbia
	\|
	\|-- erato_etylus
	\|
	\| ...
	```

	### Data Instances

	* Type: PNG
	* Size: 128px x 128px
	* Background: [210, 210, 210] (gray)
	* Fit in frame: Most padding is above and below the image, some on the left and right.
	* Ruler or Scale: None
	* Color (ColorChecker, white-balance, None): None


	### Data Fields

	In `Hoyal_Cuthill_GoldStandard_metadata_cleaned.csv`:

	* `NHM_Specimen`: Natural History Museum Specimen number
	* `Image_filename`: filename of image of specimen
	* `View`: whether ventral or dorsal view of specimen (all dorsal)
	* `Species`: species of specimen (melpomene or erato)
	* `Subspecies`: subspecies of the specimen
	* `Sex`: sex of the specimen (male or female)
	* `addit_taxa_info`: additional taxonomic information (subspecies)
	* `type_stat`: [More Information Needed] 'ST', 'PT', or 'HT', but mostly null
	* `hybrid_stat`: hybrid status ('valid subspecies', 'subspecies synonym' or 'unknown' (only 1))
	* `in_reduced`: [More Information Needed] 0 or 1 to indicate yes or no
	* `locality`: where specimen was collected
	* `lat`: latitude where specimen was collected
	* `lon`: longitude where specimen was collected
	* `speciesdesig`: species designation, first initial of species '.' subspecies (eg., 'm. rosina')

	`Train_Test_Curated_GoldStandard_Hoyal_Cuthill.csv` has three additional columns:
	* `Image_filename_png`: filename of (png) image of specimen, `dorsal_images_cuthill/` + `<Image_filename_png>` is the filepath for the processed dorsal image
	* `subset`: whether this is part of the training or test set (`train` or `test`)
	* `filepath`: the filepath for the train or test image

	`Acuity_Curated_GoldStandard_Hoyal_Cuthill.csv` also has `Image_filename_png` and `subset`, but `subset` references the bird and butterfly acuity training and test sets. Additionally, it has columns:
	* `bird_filepath`: the filepath for the bird acuity version of the image
	* `butterfly_filepath`: the filepath for the butterfly acuity version of the image


	### Data Splits

	There are 250 images in each training set and 70 in each test set.

	RGB training images are in `train` folder and testing are in `test`.

	For bird and butterfly acuities, their respective training and test images are in the `train_bird` (`train_butterfly`) and `test_bird` (`test_butterfly`) folders.

	All of these folders are further subdivided by the subspecies. Filepaths to access these images are provided in `Train_Test_Curated_GoldStandard_Hoyal_Cuthill.csv` and `Acuity_Curated_GoldStandard_Hoyal_Cuthill.csv`, respectively.


	## Dataset Creation

	Processing steps included:
	1. Hybrid Separation
	2. Label Correction
	3. Removal of subspecies with no mimic pairs
	4. Make background uniform across all images
	5. Make image square via padding

	### Curation Rationale

	[More Information Needed]
	This dataset was curated for training a model to classify different species of Heliconius Butterflies and to take into account mimicry between species.
	The original data (Cuthill et al 2019) had misclassified species/subspecies and some locality/ collection sites were outside the known range of the butterflies. It also contained hybrid and aberrant samples, that had the potential to muddle classification results. To prevent this, the data was further refined by several Heliconius experts to remove hybrid and aberrant samples. Lastly, bird and butterfly acuities were added to provide another level of analysis.

	### Source Data

	Cuthill, et. al. [doi:10.5061/dryad.2hp1978](https://doi.org/10.5061/dryad.2hp1978).

	#### Initial Data Collection and Normalization

	[More Information Needed]
	Photographers: Robyn Crowther and Sophie Ledger, Natural History Museum, London.

	#### 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

	None

	## Considerations for Using the Data

	### Social Impact of Dataset

	[More Information Needed]

	### Discussion of Biases

	[More Information Needed]

	### Other Known Limitations

	* No genetic data available.

	* Non-uniform distribution of subspecies (imbalanced).


	## Additional Information

	### Dataset Curators

	* Krzysztof Kozak (University of California Berkeley) - ORCID: 0000-0001-8980-3173

	* Christopher Lawrence (Princeton University) - ORCID: 0000-0002-3846-5968

	* James Mallet (Harvard University) - ORCID: 0000-0002-3370-0367

	* Owen McMillan (Smithsonian Tropical Research Institute) - ORCID: 0000-0003-2805-2745

	* David Carlyn (The Ohio State University) - ORCID: 0000-0002-8323-0359

	* Mohannad Elhamod (Virginia Tech) - ORCID: 0000-0002-2383-947X


	### Licensing Information

	[More Information Needed]

	### Citation Information

	Krzysztof Kozak, Christopher Lawrence, James Mallet, Owen McMillan, David Carlyn, Mohannad Elhamod. (2023), "Curated_GoldStandard_Hoyal_Cuthill", https://huggingface.co/datasets/imageomics/Curated_GoldStandard_Hoyal_Cuthill.

	Please also cite the original dataset from which this was adapted and its accompanying paper:
	* Hoyal Cuthill, Jennifer F. et al. (2019), Data from: Deep learning on butterfly phenotypes tests evolution’s oldest mathematical model, Dryad, Dataset, https://doi.org/10.5061/dryad.2hp1978.
	* Hoyal Cuthill, Jennifer F. et al. (2019), Deep learning on butterfly phenotypes tests evolution’s oldest mathematical model, Science Advances, Article-journal, https://doi.org/10.1126/sciadv.aaw4967

	### Contributions

	The [Imageomics Institute](https://imageomics.org) is funded by the US National Science Foundation's Harnessing the Data Revolution (HDR) Institute program under [Award #2118240](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2118240) (Imageomics: A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning).