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Importantly, the ClassifyMe software operates on the users local machine (own laptop or workstation) not via internet connection. False Triggers (no visible object present) will also be filtered and sorted. 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. ClassifyMe will identify animals and other objects (e.g.
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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 is intended to be used by ecologists both in the field and in the office.
We present ClassifyMe a software tool for the automated identification of animal species from camera trap images. The media and reference panes allow the user to view media files, apply helpful filters such as zoom and sharpen filters and to compare media files against “reference” media to determine matches with another individual. Snoopy applies filters to the media file stored in the database. If the object is a media file, the individual media file appears in the media pane. If the object is a capture, all of the media files appear in the media pane as a tab list of media files. For example, clicking on a station object causes it to list all of its captures and recorders. Object selection causes the context-sensitive edit pane to change its content, the action buttons’ states to change, and the object to expand its “child” object list. The navigation pane contains a hierarchical “tree” of entities in the current survey. Figure 3 shows a screen shot of Snoopy Beta and its various content panes. DISCUSSION Snoopy’s design goals were to provide the capture-recapture researcher with a comprehensive and complete software toolset to track field data. The recommended database is MySQL, as it is freely available, fast and a mature technology. This will allow researchers to customize the software where needed.
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Snoopy is written in Java and the source code will be released concurrent with the binaries. It runs efficiently on a laptop although for heavy image processing an optimized machine with plenty of RAM (16 gigabyte) and processing speed (Intel i7) is recommended. It has been tested against large datasets containing tens of thousands of records. The spreadsheets and book information is available at Samples were calculated and checked against the US Naval Observatory Database at RESULTS Snoopy is in Beta test as of December 2014 with 98% of its core features functional. The equations were translated to Java and used unmodified. Equations were taken from the Excel software included with the book Practical Astronomy with Your Spreadsheet and Calculator, Peter Duffet-Smith and Jonathan Zwart. Snoopy also includes calculated values for moon rise, set and phase as well as sun rise and set. The test data came from the Belize Mountain Pine Ridge survey, 2010-2014. The web page includes a map to select the area of interest and will tell you the number of weather stations in that area. The data was downloaded from Texas A&M’s web site at. Snoopy includes the ability to import daily weather data. Visual Paradigm is available for download at their web site (- /shop/vp.jsp) but it is not free. Visual Paradigm® was used for initial development of the object model. Media viewer effects such as zoom, sharpen and scroll position were virtualized to a database table and restored at runtime. Customized components were written for the media viewer subtypes. The primary portions of the GUI were implemented using the native Java Swing components. Netbeans is freely available from the Netbeans web site (). Netbeans was the IDE (Integrated Development Environment) used to write the Java code. The current version of Snoopy (in Beta) was not tested on a Linux machine. Snoopy was tested in the Windows environment on both the Mac’s Bootcamp Windows partition and an ASUS Windows laptop. It includes four years of data and some 60,000 media captures and several dozen animal species. Test data was imported from NSU’s existing CameraBase data for the Mountain Pine Ridge preserve in Belize.
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It is extremely fast and free for the Community edition ( ). Oracle’s MySQL database was used for the development database.
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was developed on an Apple 15” Macbook Pro Retina with 16 gigabytes of memory and a 1 TB solid-state drive.
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