We are releasing as much of our data as possible for the benefit of researchers interested in marine AI applications. If there’s anything you’re looking for but can’t find then get in contact.
ImageCLEFcoral
The data for this task originates from a growing, large-scale collection of images taken from coral reefs around the world as part of a coral reef monitoring project with the Marine Technology Research Unit at the University of Essex.
Substrates of the same type can have very different morphologies, color variation and patterns. Some of the images contain a white line (scientific measurement tape) that may occlude part of the entity. The quality of the images is variable, some are blurry, and some have poor color balance. This is representative of the Marine Technology Research Unit dataset and all images are useful for data analysis. The images contain annotations of the following 13 types of substrates:
- Hard Coral – Branching
- Hard Coral – Submassive
- Hard Coral – Boulder
- Hard Coral – Encrusting
- Hard Coral – Table
- Hard Coral – Foliose
- Hard Coral – Mushroom
- Soft Coral
- Soft Coral – Gorgonian
- Sponge
- Sponge – Barrel
- Fire Coral – Millepora
- Algae – Macro or Leaves
The test data contains images from four different locations:
- same location as training set
- similar location to training set
- geographically similar to training set
- geographically distinct from training set
Data is available on request.
2x2m quadrat
A dataset of 182 images used to demonstrate the photogrammetry process. The images are from a 2x2m quadrat area of coral reef flat in Indonesia. All sides are marked with a tape measure but no GCPs are used. Images were taken on a SJCAM5000X on 3 second timelapse with natural light following a lawnmower pattern as described in Young et al (2017). We released this dataset as a small example of what can be reconstructed for those starting out with photogrammetry.
