ClassifyMe

ClassifyMe identifies animal species and other objects in camera trap images to enable automated wildlife monitoring and biodiversity data extraction.

Key Features:

• Automated identification: Uses computer vision algorithms to detect and classify animals and objects, including vehicles, in camera trap images.
• Pre-trained models: Employs models pre-trained for specific geographic locations to improve species identification accuracy relevant to study areas.
• Local processing: Processes images on local laptops or workstations without requiring an internet connection.
• Data management and reporting: Generates report files with the most likely species detections per image and organizes images into sub-folders by identified species categories.
• False trigger filtering: Identifies and separates false triggers (images with no visible object) for dataset curation.

Scientific Applications:

• Wildlife monitoring: Automated extraction of species detections from camera trap datasets to support ecological studies.
• Biodiversity studies: Facilitates systematic collection of occurrence data for biodiversity assessment.
• Large-scale ecological surveys: Enables processing of extensive image datasets to reduce manual annotation workload in broad-scale surveys.

Methodology:

Applies computer vision algorithms and machine learning techniques using pre-trained, location-specific models to classify objects in camera trap images.