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README.md

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----
-license: cc-by-nc-4.0
----
+---
+task_categories:
+- image-classification
+- multi-label-image-classification
+- semantic-segmentation
+tags:
+- fish
+- traits
+- processed
+- RGB
+pretty_name: Fish-Vista
+size_categories:
+- 10K<n<100K
+language:
+- en
+configs:
+- config_name: classification_fv_419
+  data_files:
+  - split: train
+    path: classification_train.csv
+  - split: test
+    path: classification_test.csv
+  - split: val
+    path: classification_val.csv
+- config_name: identification_fv_682
+  data_files:
+  - split: train
+    path: identification_train.csv
+  - split: test_insp
+    path: identification_test_insp.csv
+  - split: test_lvsp
+    path: identification_test_lvsp.csv
+  - split: val
+    path: identification_val.csv
+- config_name: segmentation_fv_1200
+  data_files:
+  - split: all
+    path: segmentation_data.csv
+---
+# Dataset Card for Heliconius Collection (Cambridge Butterfly)
+
+## Dataset Description
+
+<!--
+- **Homepage:** 
+- **Repository:** 
+- **Paper:** 
+- **Leaderboard:** 
+- **Point of Contact:** 
+-->
+
+### Dataset Summary
+
+the Fish-Visual Trait Analysis (Fish-Vista) dataset—a large, annotated collection of 60K fish images spanning 1900 different species,  supporting several challenging and biologically relevant tasks including species classification, trait identification, and trait segmentation. These images have been curated through a sophisticated data processing pipeline applied to a cumulative set of images obtained from various museum collections. Fish-Vista provides fine-grained labels of various visual traits present in each image. It also offers pixel-level annotations of 9 different traits for 2427 fish images, facilitating additional trait segmentation and localization tasks.
+
+The Fish Vista dataset consists of museum fish images from (GLIN), IDigBio, Morphbank databases. We acquired these images, along with associated metadata including the scientific species names, the taxonomical family the species belong to, and licensing information, from the FishAIR repository. 
+
+
+<!---
+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
+
+* **classification_train.csv:** Information for the approximately x image files.
+
+* **classification_test.csv:** Information for the approximately x image files.
+
+* **classification_val.csv:** Information for the approximately x image files.
+
+* **identification_train.csv:** Information for the approximately x image files.
+
+* **identification_test_insp.csv:** Information for the approximately x image files.
+
+* **identification_test_lvsp.csv:** Information for the approximately x image files.
+
+* **identification_val.csv:** Information for the approximately x image files.
+
+* **segmentation_data.csv:** Information for the approximately x image files.
+
+
+**Notes:**
+
+
+### Data Instances
+
+* **Type:** JPG
+* **Size (x pixels by y pixels):** Variable
+* **Background (color or none):** Uniform (White)
+
+
+#### Preprocessing steps:
+
+### Data Fields
+
+CSV Columns are as follows:
+
+- `filename`: Unique filename for our processed images.
+- `source_filename`: Filename of the source image. Non-unique, since one source filename can result in multiple crops in our processed dataset.
+- `original_format`: Original format, all jpg/jpeg.
+- `arkid`: ARKID from FishAIR for the original images. Non-unique, since one source file can result in multiple crops in our processed dataset.
+- `verbatim_species`: Verbatim species label from FishAIR. This is not the name-resolved species name.
+- `species`: Scientific species name from FishAIR. This is not the name-resolved species name.
+- `family`: Taxonomic family
+- `source`: Source museum collection. GLIN, Idigbio or Morphbank
+- `owner`: Owner institution within the source collection.
+- `standardized_species`: Open-tree-taxonomy-resolved species name. This is the species name that we provide for Fish-Vista
+- `original_url`: URL to download the original, unprocessed image
+- `license`: License information for the original image
+- `adipose_fin`: Presence/absence of the adipose fin trait. 1 indicates presence and 0 indicates absence. This is used for trait identification.
+- `pelvic_fin`: Presence/absence of the pelvic trait. 1 indicates presence and 0 indicates absence. This is used for trait identification.
+- `barbel`: Presence/absence of the barbel trait. 1 indicates presence and 0 indicates absence. This is used for trait identification.
+- `multiple_dorsal_fin`: Presence/absence of the barbel trait. 1 indicates presence, 0 indicates absence and -1 indicates unknown. This is used for trait identification.
+
+**Note:**
+
+<!--
+### Data Splits
+
+[More Information Needed]
+-->
+      
+## Dataset Creation
+
+### Curation Rationale
+
+### Source Data
+
+
+#### Initial Data Collection and Annotation
+
+
+### Personal and Sensitive Information
+
+None
+
+## Considerations for Using the Data
+
+### Discussion of Biases and Other Known Limitations
+
+- This dataset is imbalanced.  
+- There are multiple images of the same specimen for many specimens; sometimes this is due to different views (eg., dorsal or ventral side)
+  - The master files contain only images that were determined to be unique (at the pixel level) through MD5 checksum.
+
+
+
+## Additional Information
+
+### Dataset Curators
+
+**Original Images:**
+
+**This Collection:**
+
+
+### Licensing Information
+
+
+### Citation Information
+
+
+### Contributions
+
+The [Imageomics Institute](https://imageomics.org) is funded by the US National Science Foundation's Harnessing the Data Revolution (HDR) 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). 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.