SurfTrack
This repository contains scripts for tracking and analyzing versatile images from in-situ optical microscopy (OM) experiment or Blood Clotting experiments.
Overview
The project aims to develop a package for tracking and analyzing any images from a movie. It involves two main MATLAB scripts: trracking_master_code.m and Tracked_surface_compare.m.
Requirements
- MATLAB R2022a or later
- MATLAB Computer Vision Toolbox
- Python 3.x
Setup
Installation
-
Download the Package:
- Download the zip file containing the SurfTrack package.
- Extract the zip file to a directory of your choice.
-
Install the Package:
- Open a command prompt or terminal.
- Navigate to the directory where you extracted the package.
- Install the package by running the command:
git clone https://github.com/MusannaGalib/SurfTrack.git
cd SurfTrack
pip install .
This command installs the package along with its dependencies.
SurfTrack can also be installed from PyPI:
pip install SurfTrack
Using the Package
To use this package, give your matlab executable path in run.py. Then just copy your movie.mp4 file in the scirpts folder and run the following command
process = subprocess.Popen(['C:/Program Files/MATLAB/R2022a/bin/matlab', '-nosplash', '-nodesktop', '-r', f"run('{script_path}');exit;"], stdout=subprocess.PIPE, stderr=subprocess.PIPE)
python3 wrapper.py
If you want to change the number of images that needed to be generated from the movie change the following file in the run.py file:
# Define how many images you want from the video
npics = 3
Example Usage
An example movie is given in 'scripts' folder. You can use the following commands to play with that.
# execute the python wrapper
python3 wrapper.py
Authors
This Software is developed by Matteo Ferraresso & Musanna Galib
Citing This Work
If you use this software in your research, please cite the following paper:
BibTeX entry:
@misc{galib2025dendritesuppressionznbatteries,
title={Dendrite Suppression in Zn Batteries Through Hetero-Epitaxial Residual Stresses Shield},
author={Musanna Galib and Amardeep Amardeep and Jian Liu and Mauricio Ponga},
year={2025},
eprint={2502.03841},
archivePrefix={arXiv},
primaryClass={cond-mat.mtrl-sci},
url={https://arxiv.org/abs/2502.03841},
}
Contact, questions, and contributing
If you have questions, please don't hesitate to reach out to galibubc[at]student[dot]ubc[dot]ca and matfe[at]mail[dot]ubc[dot]ca
If you find a bug or have a proposal for a feature, please post it in the Issues. If you have a question, topic, or issue that isn't obviously one of those, try our GitHub Disucssions.
If your post is related to the framework/package, please post in the issues/discussion on that repository.
Metadata
Release files for SurfTrack 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| surftrack-0.0.1.tar.gz | 4.1 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| SurfTrack-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 7.8 kB
Release files / surftrack-0.0.1.tar.gz
| Download URL | surftrack-0.0.1.tar.gz |
|---|---|
| Size | 4.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.10.12
|
Release files / SurfTrack-0.0.1-py3-none-any.whl
| Download URL | SurfTrack-0.0.1-py3-none-any.whl |
|---|---|
| Size | 3.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.10.12
|
Security for SurfTrack 0.0.1
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