Systems and methods for automatically creating an image processing pipeline

A system for automatically creating an image processing pipeline, the system comprising one or more data storage devices operatively coupled to one or more hardware processors and configured to store instructions configured for execution by the one or more hardware processors to:

• receive an input data comprising an input goal and one or more images to be processed for achieving the input goal, the input data being characterized by a plurality of input properties corresponding to the input goal and the one or more images;
• create a context model in the form of an instance of a context meta model, wherein the context meta model is configured to capture context of a domain having a property goalDescription corresponding to the input goal, and wherein the context meta model is characterized by a plurality of types of contexts including (i) a DomainContext representing domain related information, (ii) an InputContext representing information pertaining to the one or more images and (iii) a ProcessingContext representing information pertaining to the one or more hardware processors;
• create a potential image processing pipeline, based on a solution meta model, wherein the solution meta model is characterized by one or more algorithms associated with the DomainContext for performing a plurality of tasks corresponding to the input goal, and wherein each of the plurality of tasks are associated with (i) a TaskType from a plurality of TaskTypes (ii) a TaskTemplate representing a reusable task sequence for the input data using a taskOrder and (iii) the one or more algorithms for performing an associated task;
• create a rule model based on a rule meta model, wherein the rule meta model is configured to capture knowledge pertaining to the DomainContext and wherein the rule model is characterized by a plurality of rules of types including (i) TemplateRule representing rules for selecting the TaskTemplate from a list of TaskTemplate, for each of the plurality of tasks, (ii) AlgoRule representing rules for selecting an algorithm from the one or more algorithms for performing an associated task in the TaskTemplate based on the context model and (iii) PropRule representing rules for updating properties of the one or more images based on execution of a selected algorithm;
• obtain the taskOrder representing an order of execution of the plurality of tasks by performing execution of the TemplateRule for selection of the TaskTemplate pertaining to the goalDescription;
• and
• execute one or more rules from the plurality of rules, comprised in AlgoRule, corresponding to each of the plurality of tasks based on the obtained order of execution of the plurality of tasks to obtain a recommended algorithm for each of the plurality of tasks;
• execute the recommended algorithm for each of the plurality of tasks;
• and
• validate the potential image processing pipeline to obtain a validated image processing pipeline corresponding to the input goal using a continually updated model based Knowledge Repository comprised in the one or more data storage devices, the Knowledge Repository comprising the context meta model, the solution meta model, the rule meta model and algorithmic services corresponding to the one or more algorithms, by dynamically performing:
• on execution of the recommended algorithm, validating an outcome associated thereof for each of the plurality of tasks for input and output consistency;
• and
• on execution of the one or more rules, validating the one or more rules corresponding to each of the plurality of tasks based on dynamic updation of the InputContext of the context model.

A computer program product comprising a non-transitory computer readable medium having a computer readable program embodied therein, wherein the computer readable program, when executed on a computing device, causes the computing device to:

• receive, via one or more processors, an input data comprising an input goal and one or more images to be processed for achieving the input goal, the input data being characterized by a plurality of input properties corresponding to the input goal and the one or more images;
• create a context model in the form of an instance of a context meta model, wherein the context meta model is configured to capture context of a domain having a property goalDescription corresponding to the input goal, and wherein the context meta model is characterized by a plurality of types of contexts including (i) a DomainContext representing domain related information, (ii) an InputContext representing information pertaining to the one or more images and (iii) a ProcessingContext representing information pertaining to the one or more hardware processors;
• create a potential image processing pipeline, based on a solution meta model, wherein the solution meta model is characterized by one or more algorithms associated with the DomainContext for performing a plurality of tasks corresponding to the input goal, and wherein each of the plurality of tasks are associated with (i) a TaskType from a plurality of TaskTypes (ii) a TaskTemplate representing a reusable task sequence for the input data using a taskOrder and (iii) the one or more algorithms for performing an associated task;
• create a rule model based on a rule meta model, wherein the rule meta model is configured to capture knowledge pertaining to the DomainContext and wherein the rule model is characterized by a plurality of rules of types including (i) TemplateRule representing rules for selecting the TaskTemplate from a list of TaskTemplate, for each of the plurality of tasks, (ii) AlgoRule representing rules for selecting an algorithm from the one or more algorithms for performing an associated task in the TaskTemplate based on the context model and (iii) PropRule representing rules for updating properties of the one or more images based on execution of a selected algorithm;
• obtain the taskOrder representing an order of execution of the plurality of tasks by performing execution of the TemplateRule for selection of the TaskTemplate pertaining to the goalDescription;
• and
• execute one or more rules from the plurality of rules, comprised in AlgoRule, corresponding to each of the plurality of tasks based on the obtained order of execution of the plurality of tasks to obtain a recommended algorithm for each of the plurality of tasks;
• execute the recommended algorithm for each of the plurality of tasks;
• and
• validate the potential image processing pipeline to obtain a validated image processing pipeline corresponding to the input goal using a continually updated model based Knowledge Repository comprised in the one or more data storage devices, the Knowledge Repository comprising the context meta model, the solution meta model, the rule meta model and algorithmic services corresponding to the one or more algorithms, by dynamically performing:
• on execution of the recommended algorithm, validating an outcome associated thereof for each of the plurality of tasks for input and output consistency;
• and
• on execution of the one or more rules, validating the one or more rules corresponding to each of the plurality of tasks based on dynamic updation of the InputContext of the context model.