Falzon Greg, Lawson Christopher, Cheung Ka-Wai, Vernes Karl, Ballard Guy A, Fleming Peter J S, Glen Alistair S, Milne Heath, Mather-Zardain Atalya, Meek Paul D
School of Science and Technology, University of New England, Armidale, NSW 2351, Australia.
School of Environmental and Rural Science, University of New England, Armidale, NSW 2351, Australia.
Animals (Basel). 2019 Dec 27;10(1):58. doi: 10.3390/ani10010058.
We present a software tool for the automated identification of animal species from camera trap images 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 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 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.
我们展示了一种用于从相机陷阱图像中自动识别动物物种的软件工具，该工具供生态学家在野外和办公室使用。用户可以下载针对其感兴趣地点的预训练模型，然后将相机陷阱拍摄的图像上传到笔记本电脑或工作站，该软件将识别图像中的动物和其他物体（如车辆），提供包含最可能的物种检测结果的报告文件，并自动将图像分类到与这些物种类别相对应的子文件夹中。误触发（无可见物体）也将被过滤和分类。重要的是，该软件在用户的本地机器（自己的笔记本电脑或工作站）上运行，而不是通过互联网连接。这使得用户能够在现场使用最先进的相机陷阱计算机视觉软件，而不仅仅是在办公室。该软件对最终用户的成本也很低，因为无需将昂贵的数据上传到云服务。此外，在用户的终端设备上本地处理图像使他们能够控制数据，并解决围绕数据传输和第三方访问用户数据集的隐私问题。
