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WISDAM (Wildlife Imagery Survey – Detection and Mapping) is a software package used for the digitisation of objects within images and to enrich objects with meta-data.

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WISDAM

Python Version 3.10,3.11 License: GPLv3 Contributor Covenant

WISDAM (Wildlife Imagery Survey – Detection and Mapping) is a free-and-open-source (FOSS) software package used for the digitisation of objects within images and to enrich objects with metadata.

Information about the WISDAM Project and its history can be found at www.wisdamapp.org

The software uses the power of georeferenced images to map objects and to use the mapped location to perform actions, such as grouping or statistics.

WISDAM handle images from different sources (such as piloted aircraft and drones) and allow you to import them with their georeference information. Alternatively you can import orthophotos.

With this georeference information, image footprints and geometries of objects can be mapped to real world coordinates. For mapping in WISDAM either a raster model (e.g. DTM, DSM) or a simple plain (e.g. sea level) can be used.

WISDAM also allows you to run an AI background process on images, to extract objects that my not have been detected through manual review process. WISDAM helps to visualise and enrich these objects with meta-data.

WISDAM has been designed to optimise the workflow of environmental observation and is focused on the fast and easy handling of images and digitisation of objects.

Important

WISDAM is under development and did undergo a major refactoring, if you encounter any bugs (crashes, error, wrong calculations). Please submit a bug issue as described under contribution. You can save the information from the logfile within WIASDAM and error message was printed.

Table of Contents

Features

For a more detailed outline of features please look at https://www.wisdamapp.org/about/

Map your aerial images and objects

When you import your images and select the appropriate ‘data loader’ according to the aerial platform you’ve used (e.g. select your drone model), your images are immediately georeferenced to real-world coordinates. Image metadata can then be exported as csv or GIS file types.

GIS Page

Customise the metadata

Customise the metadata you attribute to your images and animal sightings You can design your own project metadata attributes according to your unique survey needs. Create your own environmental categories to classify your images, and set up your own variables to describe each animal sighting.

Project Creation

Detect resights of animals in overlapping images to avoid double-counting

You can easily detect and assign resights of the same individual animal using WISDAM’s projection feature, which displays the location of the bounding box of animals already labelled as they should appear in overlapping images. Assign multiple sightings of a single animal to a resight set to ensure the animal is only counted once.

Animal Resight

View all of your animal sightings in one page

You can view all of your sighting using WISDAM’s gallery page, which allows you to filter and sort the sightings according type, detection method, resight set and more. Click on each sighting to review and edit it’s attributes, or to go to the full image.

Gallery Page

Verify AI (deep learning) detections of animals

You can visualise, verify and manage the output from an automated (AI) detection model by importing them via WISDAM’s AI page. Scroll through the detections and highlight the true positives before importing these detections into your project dataset. The detections can be filtered according to the probability assigned by your AI model, as well as classifications (e.g. animal type) or AI run number.

AI Page

Installing and using WISDAM

Note

WISDAM does not require installation and is a standalone executable.

WISDAM is provided currently as archive in "zip" file format. And is available at the release page. Download the file called Wisdam.zip

WISDAM is currently only available and tested for Microsoft Windows.

The building guide can be used to get started with building WISDAM from source.

Documentation

Currently, for WISDAM a manual is available which is available within WISDAM or can be found in the subdirectory of the distribution "_internal" called "wisdam_manual.pdf".

Also, the current documentation is available at http://wisdamapp.github.io/wisdam/

As well, you will find video Tutorials at https://www.wisdamapp.org/resources/

Get involved

All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome.

WISDAM relies on community support to further extend and maintaining the software. Feel free to get in contact with us, if you are using WISDAM in you projects and research studies.

Check our project homepage for more information.

Discussion

The main source of discussion should be the discussion page for future developments, questions or to get help.

Here you will also find News, for example about new releases or upcoming user conferences.

For developers

Contribution guidelines for this project

Dependency Notes

WISDAM is using QT6 and PySide6/Shiboken6 under GPLv3 and LibRAW under LGPLv2.1. Find the license statements under licenses as well within the software under the about section.

Source codes used for libraries under the GPL can be found at dependency source codes

Licence

WISDAM is licensed under the GPLv3.

Copyright (C) 2024 Martin Wieser

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or(at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see https://www.gnu.org/licenses/.

See LICENSE for more details.

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