arrow_back WildCount Dataset

30 Jun 2025 Restricted Image data

General information

Contributor: Andrea Letizia

Other contributors: Christophe Cérin, Didier Donsez

Institution: Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP, LIG

Description: This dataset was collected using automatic camera traps installed in the Écrins National Park, as part of a wildlife monitoring program. It contains images of wild animals categorized into 10 distinct species classes, and an empty class. each representing a different animal observed in its natural environment. It contain day and night images from all the seasons Animal Classes: Badger, Chamois, Roe deer, Dog, Squirrel, Hare, Wolf, Mustelid, Fox, Wild boar, Empty The dataset is divided into training and testing sets. Data augmentation techniques have been applied to certain classes within the training set to enhance model training.

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inventory_2  WildCount_Dataset.zip

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Details

External identifier:
doi:10.18709/perscido.2025.06.ds422

Subjects:
Geography, Environmental science and ecology, Computer science, Engineering

Keywords:
Wild boar, Squirrel, Badger, Day and Night Images, Mustelid, , Empty, Camera Trap Images, Biodiversity Dataset, Animal Species Classification, Ecological Data, Animal, Wildlife Monitoring, Roe deer, Écrins National Park, Fox, Chamois, Wolf, Hare

Encoding format:
JPG

Tasks:

zoom_in zoom_in prediction

Citation

Andrea Letizia, Christophe Cerin, Didier Donsez , "WildCount Dataset", 2025 Published via PerSCiDO.

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