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joule: [example] Image Segmentation using K-means Clustering

Authors: Pavel Zaichenkov;

joule: [example] Image Segmentation using K-means Clustering

Abstract

This is an image segmentation based on k-means clustering algorithm described as a Kahn Process Network. The example demonstrates interface specification capabilities of the Message Definition Language (MDL). It is used to test an algorithm that solves a CSP with constraints formulated in the MDL. It provides all files to test a full stack of developed tools that in order perform: Transform the source files of components stored in .cpp files. The transformed sources represent an original code extended with macro variables, so the components can be configured specifically for the context after the CSP is solved; Derive the interfaces for every component from the source files; Construct constraints using the derived interfaces and a net list, which declares the connections between the components; Run the algorithm that solves the CSP and SAT to find a solution that satisfies the constraints from the previous step; Configure the components by generating the code for macro variables; For each component generate API functions that receive and send messages, and are used mostly by run-time system. As a result, we get a set of modified source files that are tuned specifically for the context and are ready for use with any coordination layer that can handle communication between component. The tools are executed (after they are built) using run.sh script from the repository root directory using the command: sh run.sh build tests/image-processing/image-processing.netlist Below we briefly overview files used in the example: image-processing.netlist file specifies the connections between components including channel names. In the example the names of components are read, denoise, init and kMeans; *.cpp files are the original implementations of the components; cal.h is a header file that must be included in every component. It contains declarations specific to the format of the interfaces; environment.terms represents an interface of the environment. The output interface declares the format of the messages provided to the input of the network and the input interface specifies the expected output of the network. All terms in the interface of the environment must be ground. *.shell files overwrite information in components about channel routing, as well as provide facilities for renaming term labels. The shell facilitates separation of concerns between components, because the interfaces of incompatible components can be tuned in the shell in order to achieve precise match. The tools generate the following files that we keep in 'build' directory: *.transformed.cpp are modified source files that are generated after step 1 described above; *.terms store the interface of the components; *.json store auxiliary information that is required during code generation; example.constraints is an input for the CSP-KPN algorithm that contains the constraints for the components; example.solution is a solution of the CSP-KPN algorithm; *_CAL_FI_variables.h are files that contain generated macros definitions. They are generated based on the solution of the CSP-KPN and fully configure the components for the specific context.

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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