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Add annotation descriptive image

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  1. README.md +6 -3
README.md CHANGED
@@ -77,7 +77,7 @@ README.md
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  ### Data Fields
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- **images_metadata.csv**:
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  - `individualImageFilePath`: Path to the individually cropped beetle image, e.g., `individual_specimens/IMG_<id>_specimen_<number>_<taxonID>_<individualID>.png`, where `<id>` matches the group image and `<number>` indicates the beetle's position within that group image. Ex: `individual_specimens/IMG_0093_specimen_1_MECKON_NEON.BET.D20.000001.png`.
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  - `groupImageFilePath`: Path to grouped beetle images. e.g., `group_images/IMG_<id>.png` where `IMG_<id>` is the image name assigned by the camera roll. Ex: `group_images/IMG_0093.png`.
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  - `individualID`: Unique identification number assigned by NEON to each individual beetle. This begins with NEON.BET.D20 to show that the unique ID corresponds to a beetle from the National Ecological Observatory Network's Domain 20, followed by six digits. Ex: `NEON.BET.D20.000001`.
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  <br>
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- **trait_annotations.csv**:
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  - `groupImageFilePath`: File path to grouped beetle specimen images. Format: `group_images/IMG_<id>.png`, where `IMG_<id>` corresponds to the unique image identifier assigned by the camera system.
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  - `BeetlePosition`: Ordinal position of the individual beetle specimen within the group image (dorsal view). Specimens are numbered sequentially from top to bottom: topmost specimen = 1, subsequent specimens = 2, 3, 4, etc.
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  - `individualID`: Unique identifier assigned by NEON to each individual beetle specimen. This begins with NEON.BET.D20 to show that the unique ID corresponds to a beetle from the National Ecological Observatory Network's Domain 20, followed by six digits. Ex: `NEON.BET.D20.000001`. This allows for linking to the `images_metadata.csv` and additional metadata provided through the [NEON data portal](https://www.neonscience.org/data).
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  <a name="footnote2">2</a>: The measurement is up to 3 decimal places. To get measurements with more numerical precision (i.e. additional decimal places), use this equation: `cm_<measurement>` = `px_<measurement>`/`px_scalebar`.
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-
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  ## Dataset Creation
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  This dataset was compiled as part of the field component of the Experiential Introduction to AI and Ecology Course run by the Imageomics Institute and the AI and Biodiversity Change (ABC) Global Center. This field work was done on the island of Hawai'i January 15-29, 2025.
@@ -143,6 +142,10 @@ This dataset is a collection of images taken of the ground beetle collection at
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  After imaging all the specimens, the data curation team segmented the individuals and measured the elytra length and width for each.
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  #### Annotation process
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  Trait annotations were produced using **TORAS** (Trait Observation and Recording Annotation System), a high-precision tool designed for detailed morphological measurements on high-resolution images of pinned beetle specimens. Annotators manually placed coordinate pairs marking the endpoints of key anatomical landmarks: the 1 cm reference scalebar (`coords_scalebar`), maximum elytral length (`coords_elytra_max_length`), basal pronotal width at the elytro-pronotal junction (`coords_basal_pronotum_width`), and maximum elytral width (`coords_elytra_max_width`). From these coordinates, Euclidean distances were computed in pixels (`px_scalebar`, `px_elytra_max_length`, `px_basal_pronotum_width`, `px_elytra_max_width`) and converted to centimeters using the *scalebar calibration factor* (cm_scalebar = 1.0 cm). Annotations were performed exclusively on dorsal-view images to maximize visibility of diagnostic morphological traits. Rigorous quality control ensured that each image met predefined standards for focus, illumination, and label legibility.
 
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  ### Data Fields
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+ **images_metadata.csv**: Individual specimen identification information with collection location and date information from NEON.
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  - `individualImageFilePath`: Path to the individually cropped beetle image, e.g., `individual_specimens/IMG_<id>_specimen_<number>_<taxonID>_<individualID>.png`, where `<id>` matches the group image and `<number>` indicates the beetle's position within that group image. Ex: `individual_specimens/IMG_0093_specimen_1_MECKON_NEON.BET.D20.000001.png`.
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  - `groupImageFilePath`: Path to grouped beetle images. e.g., `group_images/IMG_<id>.png` where `IMG_<id>` is the image name assigned by the camera roll. Ex: `group_images/IMG_0093.png`.
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  - `individualID`: Unique identification number assigned by NEON to each individual beetle. This begins with NEON.BET.D20 to show that the unique ID corresponds to a beetle from the National Ecological Observatory Network's Domain 20, followed by six digits. Ex: `NEON.BET.D20.000001`.
 
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  <br>
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+ **trait_annotations.csv**: Individual specimen annotation/measurement information. See Figure 1 in [Annotations](#annotations) for a visual representation of the annotation and measurement process.
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  - `groupImageFilePath`: File path to grouped beetle specimen images. Format: `group_images/IMG_<id>.png`, where `IMG_<id>` corresponds to the unique image identifier assigned by the camera system.
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  - `BeetlePosition`: Ordinal position of the individual beetle specimen within the group image (dorsal view). Specimens are numbered sequentially from top to bottom: topmost specimen = 1, subsequent specimens = 2, 3, 4, etc.
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  - `individualID`: Unique identifier assigned by NEON to each individual beetle specimen. This begins with NEON.BET.D20 to show that the unique ID corresponds to a beetle from the National Ecological Observatory Network's Domain 20, followed by six digits. Ex: `NEON.BET.D20.000001`. This allows for linking to the `images_metadata.csv` and additional metadata provided through the [NEON data portal](https://www.neonscience.org/data).
 
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  <a name="footnote2">2</a>: The measurement is up to 3 decimal places. To get measurements with more numerical precision (i.e. additional decimal places), use this equation: `cm_<measurement>` = `px_<measurement>`/`px_scalebar`.
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  ## Dataset Creation
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  This dataset was compiled as part of the field component of the Experiential Introduction to AI and Ecology Course run by the Imageomics Institute and the AI and Biodiversity Change (ABC) Global Center. This field work was done on the island of Hawai'i January 15-29, 2025.
 
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  After imaging all the specimens, the data curation team segmented the individuals and measured the elytra length and width for each.
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+ |![Fig4-Traits-Recipe-Fictional CoPilot generated depiction of the trait annotation pipeline, starting with the pinned specimens, and moving to an individual with lines on the body to illustrate the location of the morphological measurements (elytral length in red, basal pronotum width in blue, and maximum elytral width in green)](https://cdn-uploads.huggingface.co/production/uploads/642dbba7c3a53b9e1d6e8726/Mpsh-YL8Byt3iIiiWsaxZ.png)|
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+ |:--|
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+ |**Figure 1.** Artificial depiction of trait measurement “recipe” for pinned specimens. Left: Fictional group image of pinned beetles with scalebar, middle: one individual specimen with three traits measured (elytral length in red, basal pronotum width in blue, and maximum elytral width in green), right: measurement of the centimeter scalebar. Images shown in this figure were generated using Microsoft CoPilot.|
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+
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  #### Annotation process
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  Trait annotations were produced using **TORAS** (Trait Observation and Recording Annotation System), a high-precision tool designed for detailed morphological measurements on high-resolution images of pinned beetle specimens. Annotators manually placed coordinate pairs marking the endpoints of key anatomical landmarks: the 1 cm reference scalebar (`coords_scalebar`), maximum elytral length (`coords_elytra_max_length`), basal pronotal width at the elytro-pronotal junction (`coords_basal_pronotum_width`), and maximum elytral width (`coords_elytra_max_width`). From these coordinates, Euclidean distances were computed in pixels (`px_scalebar`, `px_elytra_max_length`, `px_basal_pronotum_width`, `px_elytra_max_width`) and converted to centimeters using the *scalebar calibration factor* (cm_scalebar = 1.0 cm). Annotations were performed exclusively on dorsal-view images to maximize visibility of diagnostic morphological traits. Rigorous quality control ensured that each image met predefined standards for focus, illumination, and label legibility.