Metadata-Version: 2.1
Name: Multi-Template-Matching
Version: 1.6.0.post1
Summary: Object-recognition in images using multiple templates
Home-page: https://github.com/multi-template-matching/MultiTemplateMatching-Python
Author: Laurent Thomas
Author-email: laurent132.thomas@laposte.net
License: UNKNOWN
Description: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/multi-template-matching/MultiTemplateMatching-Python/master?filepath=tutorials)
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        # 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.
        
        # 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.
        
        # 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
        
        # Releases
        Previous github releases were archived to Zenodo.  
        [![DOI](https://zenodo.org/badge/197186256.svg)](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 Unionâ€™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>
        
Keywords: object-recognition object-localization
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Intended Audience :: Science/Research
Description-Content-Type: text/markdown
