README.md

---
#license: ??
language:
- en
pretty_name: Beetlepalooza Dataset
task_categories:
- image-classification 
- image-segmentation
tags:
- biology
- image
- animals
- CV
- beetles
- elytra
- elytra width
- elytra length
- size
size_categories: 
- n<1K
- 10K<n<100K
configs:
- config_name: group_images
  data_files:
  - "BeetleMeasurements.csv"
  - "group_images/*.jpg"
- config_name: individual_images
  data_files:
  - "individual_metadata.csv"
  - "individual_images/*.jpg"
---

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# Dataset Card for Beetlepalooza Dataset

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## Dataset Details

### Dataset Description

- **Curated by:** list curators (authors for _data_ citation, moved up)
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- **Homepage:** 
- **Repository:** [related project repo]
- **Paper:** 


<!-- Provide a longer summary of what this dataset is. -->
[More Information Needed]

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### Supported Tasks and Leaderboards
[More Information Needed]

<!-- Provide benchmarking results -->


## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

In `group_images` we have 577 images of multiple beetles in a reasonably regular pattern (see sample image below). Each of these images contains a centimeter-based scalebar and a barcode representing the sample (collection of beetles in the image). Each row in `BeetleMeasurements.csv` corresponds to a measurement of the elytra (length or width) of an individual beetle.

The `individual_images` directory contains images of each individual segmented from the group images. These connect back to their group image based on the `individualID`.


```
/dataset/
    group_images/
        <pictureID 1>.png
        <pictureID 2>.png
        ...
        <pictureID 577>.png
    individual_images/
        <individualID 1>.png
        <individualID 2>.png
        ...
        <individualID n>.png
    BeetleMeasurements.csv
    individual_metadata.csv
```



### Data Instances
[More Information Needed]

<!--
Describe data files

Ex: All images are named <img_id>.png, each within a folder named for the species. They are 1024 x 1024, and the color has been standardized using <link to color standardization package>.
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### Data Fields
[More Information Needed]

**BeetleMeasurements.csv**:
  - `PictureID`: Name of the image (`<sample-barcode>.jpg`, though sometimes it's `<NEON_sampleID_>`.jpg). Unique identifier for the 577 _group_ images, not for dataset. There are 11,104 individual beetles?
  - `scalebar`: Pixel coordinates of the ruler/scalebar in the image.
  - `scale_dist_pix`: Integer. The length in pixels of the scalebar.
  - `individual`: Integer. The beetle in the image to whom the measurements refer. Awaiting confirmation of how they are counted.
  - `structure`: Whether the measurement applies to the length or width of the elytra (`ElytraLength` or `ElytraWidth`, respectively).
  - `lyingstraight`: Whether or not the beetle is "straight" in the image (`Yes` or `No`). Further guidance on this term's meaning would be helpful.
  - `coords_pix`: Pixel coordinates of the line marking the length or width of the elytra (green or purple --confirm which is which). Note that the lines are more than one pixel wide, which is why these coordinates form a rectangle.
  - `dist_pix`: Float. The length or width of the elytra (indicated by `structure`) as measured in pixels.
  - `dist_cm`: Float. The length or width of the elytra (indicated by `structure`) as measured in centimeters using the scalebar (the red line in the reference image denotes the pixel count for 1cm).
  - `scientificName`: Scientific name of the specimen (`<Genus> <species>`). There are 85 different species among 36 genera.
  - `siteID`: String. Identifier for the site from which the specimens were collected. There 30 different site IDs.
  - `field_site_name`: Name of site from which the specimens were collected. There are 43 different field site names.
  - `plotID`: Identifier for the plot from which the specimens were collected (`<siteID>_<plot number>`). There are 144 different plots from which specimens were collected.
  - `user_name`: Name of person inputting the information? (`<first><Last>`) or just their username in the system? Only 3 of them. --looks like username
  - `workflow_id`: Integer identifier for the workflow used...?? There are 5.
  - `genus`: Genus of the individual (generated by taking the first word in the `scientificName`).
  - `individualID`: Unique identifier for the beetles (based on the assumed uniqueness of the `PictureID`, generated from `PictureID` (minus the `.jpg`) plus `_<individual>`.
  - `file_name`: Relative path to image from the root of the directory (`<group_images>/<pictureID>.jpg`); allows for image to be displayed in the dataset viewer alongside its associated metadata.


**TODO:* Make metadata file for viewer once we have segmented images too:
**individual_metadata.csv**:
  - `individualID`: ID of beetle in the individual image (matches `individualID` in `BeetleMeasurements.csv`). This is a unique identifier for this CSV.
  - `pictureID`: Name of the group image (`<sample-barcode>.jpg`, though sometimes it's `<NEON_sampleID_>`.jpg). Unique identifier for the 577 _group_ images, not for dataset. (Matches `pictureID` in `BeetleMeasurements.csv`.)
  - `scientificName`: Scientific name of the specimen (`<Genus> <species>`). There are 85 different species among 36 genera.
  - `elytraLength`: Length of the elytra in centimeters.
  - `elytraWidth`: Width of the elytra in centimeters.
  - `file_name`: Relative path to image from the root of the directory (`<individual_images>/<individualID>.jpg`); allows for image to be displayed in the dataset viewer alongside its associated metadata.


### Data Splits
[More Information Needed]
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## Dataset Creation

### Curation Rationale
[More Information Needed]
<!-- Motivation for the creation of this dataset. For instance, what you intended to study and why that required curation of a new dataset (or if it's newly collected data and why the data was collected (intended use)), etc. -->

This dataset was curated for use at [BeetlePalooza 2024](https://github.com/Imageomics/BeetlePalooza-2024/wiki) to help drive scientific discovery through machine learning and computer vision.


### Source Data

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The specimens come from [NEON sites](https://www.neonscience.org/), as indicated in the `BeetleMeasurements` CSV.

#### Data Collection and Processing
[More Information Needed]
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-->

#### Who are the source data producers?
[More Information Needed]
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Ex: This dataset is a collection of images taken of the butterfly collection housed at the Ohio State University Museum of Biological Diversity. The associated labels and metadata are the information provided with the collection from biologists that study butterflies and supplied the specimens to the museum.
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### Annotations
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Annotations were completed by 3 individuals (indicated by their NEON system usernames in the `BeetleMeasurements` CSV).

#### Annotation process
[More Information Needed]
<!-- This section describes the annotation process such as annotation tools used, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->

#### Who are the annotators?
[More Information Needed]
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### Personal and Sensitive Information
[More Information Needed]
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## Considerations for Using the Data
[More Information Needed]
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Things to consider while working with the dataset. For instance, maybe there are hybrids and they are labeled in the `hybrid_stat` column, so to get a subset without hybrids, subset to all instances in the metadata file such that `hybrid_stat` is _not_ "hybrid".
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### Bias, Risks, and Limitations
[More Information Needed]
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### Recommendations
[More Information Needed]
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## Licensing Information
[More Information Needed]

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Be sure to note different licensing of images if they have a different license from the compilation.
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The data (images and text) contain a variety of licensing restrictions mostly within the CC family. Each image and text in this dataset is provided under the least restrictive terms allowed by its licensing requirements as provided to us (i.e, we impose no additional restrictions past those specified by licenses in the license file).

EOL images contain a variety of licenses ranging from [CC0](https://creativecommons.org/publicdomain/zero/1.0/) to [CC BY-NC-SA](https://creativecommons.org/licenses/by-nc-sa/4.0/).
For license and citation information by image, see our [license file](https://huggingface.co/datasets/imageomics/treeoflife-10m/blob/main/metadata/licenses.csv).

This dataset (the compilation) has been marked as dedicated to the public domain by applying the [CC0 Public Domain Waiver](https://creativecommons.org/publicdomain/zero/1.0/). However, images may be licensed under different terms (as noted above).
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## Citation
[More Information Needed]

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## Acknowledgements

The National Ecological Observatory Network is a program sponsored by the National Science Foundation and operated under cooperative agreement by Battelle. This material uses specimens and/or samples collected as part of the NEON Program. Additionally, this material is based upon work supported by the National Science Foundation under [Award No. 2118240](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2118240) ([Imageomics](https://imageomics.org): A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning), and under Award Numbers [2301322](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2301322&HistoricalAwards=false) and [2242803]() and the USDA National Institute of Food and Agriculture, Hatch Project [Number ME0-22425]() through the Maine Agricultural and Forest Experiment Station. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.


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