Title: ClassifyMe: A Field-Scouting Software for the Identification of Wildlife in Camera Trap Images
Authors: Greg Falzon, Christopher Lawson, Ka-Wai Cheung, Karl Vernes, Guy A. Ballard, Peter J. S. Fleming, Alistair S. Glen, Heath Milne, Atalya Mather-Zardain and Paul D. Meek
Journal: MDPI (Multidisciplinary Digital Publishing Institute)
Citation: Falzon G, Lawson C, Cheung K-W, Vernes K, Ballard GA, Fleming PJS, Glen AS, Milne H, Mather-Zardain A, Meek PD. ClassifyMe: A Field-Scouting Software for the Identification of Wildlife in Camera Trap Images. Animals. 2020; 10(1):58. https://doi.org/10.3390/ani10010058
Open Access: Yes
We present ClassifyMe a software tool for the automated identification of animal species from camera trap images. ClassifyMe is intended to be used by ecologists both in the field and in the office. Users can download a pre-trained model specific to their location of interest and then upload the images from a camera trap to a laptop or workstation. ClassifyMe will identify animals and other objects (e.g., vehicles) in images, provide a report file with the most likely species detections, and automatically sort the images into sub-folders corresponding to these species categories. False Triggers (no visible object present) will also be filtered and sorted. Importantly, the ClassifyMe software operates on the user’s local machine (own laptop or workstation)—not via internet connection. This allows users access to state-of-the-art camera trap computer vision software in situ, rather than only in the office. The software also incurs minimal cost on the end-user as there is no need for expensive data uploads to cloud services. Furthermore, processing the images locally on the users’ end-device allows them data control and resolves privacy issues surrounding transfer and third-party access to users’ datasets.
Keywords: Camera traps, camera trap data management, deep learning, ecological software, species recognition, wildlife monitoring