|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Vpp||620||5 years ago||4||mit||C++|
|Video++, a C++14 high performance video and image processing library.|
|Pysteps||360||1||3 months ago||20||January 25, 2023||33||bsd-3-clause||Python|
|Python framework for short-term ensemble prediction systems.|
|Clover||333||a month ago||14||mit||C++|
|ROS-based framework and RPi image to control PX4-powered drones 🍀|
|Opticalflowtoolkit||194||4 years ago||1||mit||Python|
|Python-based optical flow toolkit for existing popular dataset|
|Mrflow||99||4 years ago||5||other||Python|
|Code for the paper "Optical Flow in Mostly Rigid Scenes" by Jonas Wulff, Laura Sevilla-Lara, Michael Black, CVPR 2017|
|Torch Warp||56||4 years ago||2||other||C++|
|Fully automatic optical flow based image morphing implemented in Torch|
|Im2flow||44||5 years ago||Lua|
|Im2Flow: Motion Hallucination from Static Images for Action Recognition (CVPR 2018)|
|Optical Flow Gpu Docker||32||5 years ago||1||Python|
|Compute dense optical flow using TV-L1 algorithm with NVIDIA GPU acceleration.|
|Briefmatch||32||6 years ago||1||bsd-3-clause||C++|
|BriefMatch real-time GPU optical flow|
|Motion Estimation Using Speeded Up Robust Features Surf And Oriented Fast Rotated Brief Orb||16||6 years ago||C++|
PyTrx (short for 'Python Tracking') is a Python object-oriented toolbox created for the purpose of calculating real-world measurements from oblique images and time-lapse image series. Its primary purpose is to obtain velocities, surface areas, and distances from imagery of glacial environments.
We are happy for others to use and adapt PyTrx for their own processing needs. If used, please cite the following key publication and Digital Object Identifier:
PyTrx has been used in the following publications. In addition to the publication above, please cite any that are applicable where possible:
PyTrx used for georectification of glacier calving event locations
How et al. (2019) Calving controlled by melt-undercutting: detailed mechanisms revealed through time-lapse observations. Annals of Glaciology 60 (78), 20-31, doi:10.1017/aog.2018.28
PhD thesis by Penelope How, for which PyTrx was developed primarily
How (2018) Dynamical change at tidewater glaciers examined using time-lapse photogrammetry. PhD thesis, University of Edinburgh, UK, https://hdl.handle.net/1842/31103
PyTrx used for detection of supraglacial lakes and meltwater plumes
How et al. (2017) Rapidly changing subglacial hydrological pathways at a tidewater glacier revealed through simultaneous observations of water pressure, supraglacial lakes, meltwater plumes and surface velocities. The Cryosphere 11, 2691-2710, doi:10.5194/tc-11-2691-2017
MSc thesis by Lynne Buie, where PyTrx was created in its earliest form
Addison (2015) PyTrx: feature tracking software for automated production of glacier velocity. MSc thesis, University of Edinburgh, UK, https://hdl.handle.net/1842/11794
The PyTrx installation has been tested on Linux and Windows operating systems (it should also work on Apple operating systems too, it just hasn't been tested). PyTrx is primarily available through pip:
pip install pytrx
Be warned that there are difficulties with the GDAL package on pip, meaning that gdal could not be declared explicitly as a PyTrx dependency in the pip package compiling. Please ensure that gdal is installed separately if installing PyTrx through pip. You should be able to create a new environment, install GDAL and the other dependencies with conda, and then install PyTrx with pip.
conda create --name pytrx3 python=3.7 conda activate pytrx3 conda install gdal opencv pillow scipy matplotlib spyder pip install pytrx
Be aware that the PyTrx example scripts in this repository are not included with the pip distribution of PyTrx, given the size of the example dataset files. Either download these separately, or create a new conda environment (using the .yml environment file provided) and clone the PyTrx GitHub repository:
conda env create --file environment.yml conda activate pytrx3 git clone https://github.com/PennyHow/PyTrx.git
See our readthedocs page on setting up PyTrx for more details.
PyTrx was initially developed and released as part of the CRIOS (Calving Rates and Impact on Sea Level project. PyTrx's continued development and maintenance is funded by an ESA Living Planet Fellowship.
Parts of the georectification functions in the PyTrx toolbox were inspired and translated from ImGRAFT, a photogrammetry toolbox for Matlab (Messerli and Grinsted, 2015). Where possible, ImGRAFT has been credited for in the corresponding PyTrx scripts (primarily some passages in the CamEnv.py script) and cited in relevant PyTrx publications.
See PyTrx's readthedocs for all permissions and acknowledgements.
There are other useful software available for terrestrial photogrammetry in glaciology:
Pointcatcher - Matlab-based GUI toolbox for feature-tracking and georectification
ImGRAFT - Matlab toolbox for feature-tracking and georectification
EMT (Environmental Motion Tracking) - GUI toolbox for feature-tracking and georectification
CIAS - IDL gui for feature-tracking
PRACTISE - Matlab toolbox for georectification
PyTrx is licensed under a MIT License.