ReefNet 1.0: Annotated Coral Reef Images for Global Classification

A curated collection of annotated coral reef images sourced from the CoralNet platform. The dataset is designed for training and evaluating machine learning models for coral classification on a global scale. It was created by ReefNet and last updated on 2025-05-16.

Use Cases

• Train coral classification models based on the annotated images.
• Evaluate model performance on a global scale using the consolidated label set.
• Extract custom datasets for specific geographic regions based on the provided metadata.

Strengths

• Dataset is curated and annotated for machine learning tasks.
• Consolidated label set facilitates standardized classification.
• Rich metadata supports extraction of region-specific datasets.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file size are unknown, which may limit suitability assessment.
• Data may reflect geographic bias inherent to the source platform.

Provenance

Source

CoralNet platform

Collection Method

Sourced and curated from an existing platform.

Freshness

Last updated 2025-05-16 02:16:48; freshness should be verified.

Geography

Global scale