Welcome to the Photographic Observation Study (POS)- Canadian Wildlife Service (CWS) GitHub page. This is the home for a number of tools that were developed for the POS. General notes about each tool are found in this file, and more detailed ones are available in the corresponding repository.
POS-CWS is a team of researchers working to improve marine traffic monitoring, especially as it relates to marine mammal behaviour. For more information, see https://www.poscanada.org/
Tools on this page can be downloaded either by either cloning them with Git or by downloading them as a zip. The first method takes a bit more setup as you'll need to install Git, but it makes it very easy to update the tools. The second method is an easy way to access the smaller tools (such as the file management ones), but it does mean that tools must be redownloaded if they are updated in the future.
This section provides a brief overview of the tools that are provided on github.
Most of our completed tools are publicly available, and can be downloaded without logging in. If you are part of our team and need access to any of the private tools, please contact Patrick or Gregory to get your github account linked to our team.
This tool overlays AIS information on images taken looking out over water, and provides ways to mark and record vessel traffic.
This tool copies images between locations, organizing them into daily folders as it does so.
This is a collection of small tools that don't fit into any other repository. More information on each can be found there. Currently, this list includes:
- file counter: a PyQt program that lists the number of files in each folder. Useful in searching for anomalies in a repetitive file structure, such as when data is organized into daily folders, each of which should have a comparable amount of data files.
- file list/copy tool: saves a specific folder and file structure, then recreates that structure from an unorganized dataset. Our typical use case for this is when returning data that has been organized on a remote workstation to the original central server, without needed to transfer an entire dataset.
- image sampler: specific to our standard image file structure, this tool copies 4 images at specific times each day to a new folder. This is useful when assessing weather conditions or camera status.
- metadata copier: This tool supports one of our auto-detection tools by searching for duplicate images with metadata missing, then searching for an original image for each duplicate to mirror the metadata over from.
This is a collection of scripts that have been used in the past for a variety of purposes, such as processing AIS data. Many of them are ad-hoc and not intended for re-use, but they may be useful as references for future processing scripts.
Most of these tools are written in Python 3. Some require additional libraries, the main two of which are:
- PyQt5 is required for any tool that has a visual interface. It can be installed using pip: "pip install PyQt5"
- this package is licenced under the GNU General Public Licence. For more details, see the licencing information below.
- Pillow is used to get image metadata in a number of the correction tools. It can also be installed using pip: "pip install Pillow" Python 3.8 or newer is recommended for any tools that copy files, as these tools will run several times faster than on older versions of Python.
All of these projects are licenced under the GNU GPLv3 copy-left licence. Details on the permissions of this licence can be found at https://www.gnu.org/licenses/.