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Multi-Template-Matching-1.6.3
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مشاهده بیشترتوضیحات
Object-recognition in images using multiple templates
| ویژگی | مقدار |
|---|---|
| سیستم عامل | OS Independent |
| نام فایل | Multi-Template-Matching-1.6.3 |
| نام | Multi-Template-Matching |
| نسخه کتابخانه | 1.6.3 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Laurent Thomas |
| ایمیل نویسنده | laurent132.thomas@laposte.net |
| آدرس صفحه اصلی | https://github.com/multi-template-matching/MultiTemplateMatching-Python |
| آدرس اینترنتی | https://pypi.org/project/Multi-Template-Matching/ |
| مجوز | - |
[](https://mybinder.org/v2/gh/multi-template-matching/MultiTemplateMatching-Python/master?filepath=tutorials)
[](https://saythanks.io/to/laurent132.thomas@laposte.net)
# Multi-Template-Matching
Multi-Template-Matching is a python package to perform object-recognition in images using one or several smaller template images.
The main function `MTM.matchTemplates` returns the best predicted locations provided either a score_threshold and/or the expected number of objects in the image.
The branch opencl contains some test using the UMat object to run on GPU, but it is actually slow, which can be expected for small dataset as the transfer of the data between the CPU and GPU is slow.
__** News **__ : You might be interested to test the newer python implementation which is more object-oriented and only relying on scikit-image and shapely.*
https://github.com/multi-template-matching/mtm-python-oop
# Installation
Using pip in a python environment, `pip install Multi-Template-Matching`
Once installed, `import MTM`should work.
Example jupyter notebooks can be downloaded from the tutorial folder of the github repository and executed in the newly configured python environement.
# Documentation
The [wiki](https://github.com/multi-template-matching/MultiTemplateMatching-Python/wiki) section of the repo contains a mini API documentation with description of the key functions of the package.
The [website](https://multi-template-matching.github.io/Multi-Template-Matching/) of the project contains some more general documentation.
# Examples
Check out the [jupyter notebook tutorial](https://github.com/multi-template-matching/MultiTemplateMatching-Python/tree/master/tutorials) for some example of how to use the package.
You can run the tutorials online using Binder, no configuration needed ! (click the Binder banner on top of this page).
To run the tutorials locally, install the package using pip as described above, then clone the repository and unzip it.
Finally open a jupyter-notebook session in the unzipped folder to be able to open and execute the notebook.
The [wiki](https://github.com/multi-template-matching/MultiTemplateMatching-Fiji/wiki) section of this related repository also provides some information about the implementation.
# Citation
If you use this implementation for your research, please cite:
Thomas, L.S.V., Gehrig, J. Multi-template matching: a versatile tool for object-localization in microscopy images.
BMC Bioinformatics 21, 44 (2020). https://doi.org/10.1186/s12859-020-3363-7
Download the citation as a .ris file from the journal website, [here](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3363-7.ris).
# Releases
Previous github releases were archived to Zenodo, but the best is to use pip to install specific versions.
[](https://zenodo.org/badge/latestdoi/197186256)
# Related projects
See this [repo](https://github.com/multi-template-matching/MultiTemplateMatching-Fiji) for the implementation as a Fiji plugin.
[Here](https://nodepit.com/workflow/com.nodepit.space%2Flthomas%2Fpublic%2FMulti-Template%20Matching.knwf) for a KNIME workflow using Multi-Template-Matching.
# Origin of the work
This work has been part of the PhD project of **Laurent Thomas** under supervision of **Dr. Jochen Gehrig** at ACQUIFER.
<img src="https://github.com/multi-template-matching/MultiTemplateMatching-Python/blob/master/images/Acquifer_Logo_60k_cmyk_300dpi.png" alt="ACQUIFER" width="400" height="80">
# Funding
This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 721537 ImageInLife.
<p float="left">
<img src="https://github.com/multi-template-matching/MultiTemplateMatching-Python/blob/master/images/ImageInlife.png" alt="ImageInLife" width="130" height="100">
<img src="https://github.com/multi-template-matching/MultiTemplateMatching-Python/blob/master/images/MarieCurie.jpg" alt="MarieCurie" width="130" height="130">
</p>
نیازمندی
| مقدار | نام |
|---|---|
| - | numpy |
| >=4.5.4 | opencv-python-headless |
| - | scikit-image |
| - | scipy |
| - | pandas |
نحوه نصب
نصب پکیج whl Multi-Template-Matching-1.6.3:
pip install Multi-Template-Matching-1.6.3.whl
نصب پکیج tar.gz Multi-Template-Matching-1.6.3:
pip install Multi-Template-Matching-1.6.3.tar.gz