LuxFilter Technical Documentation
Overview
LuxFilter is a modular filtering system designed for processing and scoring digital assets efficiently. It integrates with the Luxoria ecosystem and provides a pipeline-based approach to apply filtering algorithms to image data.
Features
Modular filtering pipeline with weighted algorithms
Event-driven architecture for processing notifications
Parallelized execution for optimized performance
Error handling for robust processing
Architecture
Core Components
LuxFilter
Module
LuxFilter
ModuleImplements
IModule
Handles initialization, execution, and shutdown
Provides logging for module actions
PipelineService
PipelineService
Manages the execution of filtering algorithms
Tracks progress and scores
Uses concurrency for efficiency
IFilterAlgorithm
IFilterAlgorithm
Defines a standard interface for filtering algorithms
Implements a scoring method based on image analysis
Implemented Filtering Algorithms
Image Quality Algorithms
ResolutionAlgo: Evaluates the resolution of an image.
SharpnessAlgo: Measures the sharpness level in an image.
Perceptual Metrics Algorithms
BrisqueAlgo: Uses the BRISQUE metric to assess perceptual quality.
How to Use
Prerequisites
Ensure that the Luxoria ecosystem is installed and configured properly.
Your project should reference the necessary LuxFilter libraries.
Implement and register
IEventBus
for event-driven interactions.
Installation
Clone or download the LuxFilter module.
Add the project reference in your Luxoria-based application.
Implement
IModule
interface in your module system.
Running the Module
Initialize the module using
Initialize()
.Configure the filtering pipeline using
AddAlgorithm()
.Pass image data through the
Compute()
function.
Example Usage
Initialization
Subscribes to filtering events
Initializes logger and context
Filtering Process
1. Pipeline Configuration
Uses
AddAlgorithm(IFilterAlgorithm algorithm, double weight)
to add algorithmsEnsures the total weight of all algorithms does not exceed 1.0
2. Image Processing
Processes images using
Compute(IEnumerable<(Guid, SKBitmap)> bitmaps)
Applies each algorithm in the workflow to every image
3. Score Computation
Each image receives a final score based on weighted algorithm outputs
Results are returned as
(Guid, double)
tuples
Event Handling
Score Computation Event
Notifies when an image has been processed and scored
Pipeline Completion Event
Notifies when the pipeline has finished executing
Error Handling & Logging
Uses
ILoggerService
for structured logsException handling ensures robust error reporting
Logs execution times for performance analysis
Performance Optimizations
Uses parallel processing for scoring
Implements concurrent data structures for thread safety
Optimized event-driven execution to reduce overhead
Future Enhancements
Dynamic algorithm tuning for real-time adjustments
Support for additional image formats
Graphical visualization of scores
Conclusion
LuxFilter provides a scalable and efficient filtering pipeline for processing images in the Luxoria ecosystem. Its modular design, event-driven execution, and parallel processing capabilities make it an ideal choice for large-scale image scoring and analysis.
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