AnimalClue YOLO Datasets: Images of Animal Traces for Object Detection

A collection of images for training object detection models to recognize wild animals from indirect clues. The dataset is part of the AnimalClue project presented at ICCV 2025 and is authored by risashinoda. It was last updated on May 13, 2026.

Use Cases

• Train YOLO models to detect animal footprints based on image annotations.
• Develop systems for wildlife identification from feathers mentioned in the description.
• Build classifiers for animal feces or bones as indirect clues for species recognition.
• Create educational tools for recognizing animals by their traces like eggs.

Strengths

• Dataset is associated with a research project presented at ICCV 2025, a top-tier computer vision conference.
• Images are annotated for object detection in YOLO format, a standard for the task.
• Each image filename is linked to an observation ID, which suggests traceable data organization.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

huggingface

Collection Method

Likely gathered for the AnimalClue research project exploring animal recognition from traces.

Freshness

Last updated 2026-05-13 05:23:18; freshness should be verified.