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.
Camera trapping has advanced significantly in Australia over the last two decades. These devices have become more versatile and the associated computer technology has also progressed dramatically since 2011. In the USA, the hunting industry drives most changes to camera traps; however the scientific fraternity has been instrumental in incorporating computational engineering, statistics and technology into camera trap use for wildlife research. New survey methods, analytical tools (including software for image processing and storage) and complex algorithms to analyse images have been developed. For example, pattern and texture analysis and species and individual facial recognition are now possible. In the next few decades, as technology evolves and ecological and computational sciences intertwine, new tools and devices will emerge into the market. Here we outline several projects that are underway to incorporate camera traps and associated technologies into existing and new tools for wildlife management. These also have significant implications for broader wildlife management and research.
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.
Context Wildlife and pest managers and stakeholders should constantly aim to improve animal-welfare outcomes when foot-hold trapping pest animals. To minimise stress and trauma to trapped animals, traps should be checked at least once every 24h, normally as soon after sunrise as possible. If distance, time, environmental or geographical constraints prevent this, toxins such as strychnine can be fitted to trap jaws to induce euthanasia. However, strychnine is considered to have undesirable animal-welfare outcomes because animals are conscious while clinical signs of intoxication are present. A toxin considered more humane, para-aminopropiophenone (PAPP), is available to induce euthanasia in trapped animals but is untested for presentation and efficacy. Aim We tested the efficacy of two types of lethal trap device (LTD’s), each using a paste formulation of PAPP as the active toxin to replace the use of strychnine on foot-hold jaw traps. Methods Elastomer LTDs and PAPP-cloths were fitted to jaw traps set to capture wild dogs (Canis familiaris). Camera-trap data was used to record animal behaviours after capture and to determine the efficacy of both modalities. Key results Every trapped wild dog (n=117) gnawed at the elastomer LTD’s or PAPP-cloth attached to the trap jaws that restrained them; one dog failed to liberate the toxin. From the dogs caught in the main trial (n=56), a mortality rate of 84% and 87% was reported respectively. The mean time from trap-to-death for elastomer LTDs was 64min and 68min for PAPP-cloths. Conclusions Elastomer LTDs and PAPP cloths combined caused the mortality of 85% of captured dogs. This efficacy could be improved by adopting the recommendations discussed in the present study for deploying PAPP-based LTDs during trap deployment. Implications PAPP-based LTDs offer an alternative option to the use of strychnine and improve the welfare outcomes for trapped predators, especially where traps are not checked within the recommended 24-h period.
ContextImproving the welfare outcomes for captured animals is critically important and should underpin ‘best-practice’ trapping. Most Australian States and Territories have regulations and guidelines that form a legal framework for the maximum number of hours an animal can be restrained in a trap. Because servicing all traps within preferred time frames (less than 24h) can be logistically difficult or is considered undesirable for efficacy reasons, some jurisdictions have adopted relatively long trap-checking intervals (up to 72 h). AimsWe developed and tested the signal transmission and alert efficacy of a foot hold-trap alert system, based on Celium technology, so as to advise trappers of the activation of individual foot-hold traps, even in remote locations. MethodsWe refined the Celium trap-alert system and designed a below-ground wireless node that transmits a message via satellite or by using the cellular system when a foot-hold trap is sprung. We tested signal transmission and alert efficacy in three locations, with a focus in Australia. Key resultsTransmission of signals from nodes to hubs and to a smart-phone application were used to resolve interference problems and to identify signal limitations and strengths. During the capture of 34 dingoes, 91% of captures resulted in an alert being received. False negatives were attributed to technical issues with nearby transmitters swamping signals, and software problems that have since been resolved. In 40 captures of dogs and foxes, only one trap-alert transmitter (mole) was uncovered by a target animal and no devices were damaged by animals post-capture. ConclusionsThis cable-less trap-alert system successfully uses both cellular and satellite networks to transmit messages from desert and coastal locations to trappers, in Australia. We confirmed that this trap-alert system is not detected by target predators in the areas tested and can be effectively used to alert trappers when traps have been sprung. ImplicationsThis trap-alert system provides a tool to improve welfare outcomes for trapped target and non-target animals through Australia and New Zealand and wherever trapping occurs. It, furthermore, provides a solution to checking traps daily when the distance to and between traps cannot be covered within an appropriate time frame. Although trap alerts can never replace the value of daily trap checking by the trapper, they provide a solution to a management problem, namely, one of accessibility to sites.
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