The aim of the workshop is to familiarize students with basic image processing, feature detection, and feature extraction methods applied to EUSO-SPB1 data. As a part of the practical activity, students will implement their simple feature extraction method, which they will then utilize to process a dataset of EUSO-SPB1 data (simulations and noise).
The Air Shower Pattern Recognition summer school consists of the following five workshops:
- Introduction to the JEM-EUSO and running air shower event simulations
- Reading the detector data
- Implementation of a feature extraction method
- Classification of the data through the extracted features
- Classification of the data using a convolutional neural network
Slides
Practical activity
- Review of image filtration methods applied to EUSO-SPB1 simulations (jupyter)
- Review of thresholding methods applied to EUSO-SPB1 simulations (jupyter)
- Implementation of a simple feature extraction method (py)
- Running the feature extraction procedure.
#3 Implementation of a simple feature extraction method (py)
Feature extraction code in the workshop
Modules/Files of the project
- process_acquisitions.py – Batch processing of acquisition/simulation files
- feature_extraction.py – Processing of a single numpy or ROOT file
- Depends on event reader (AcqL1EventReader, NpyL1EventReader, NpyconvEventReader)
- event_processing_workshop.py
- Implementation of the feature extraction procedure for this workshop
- Class EventProcessingWorkshop (base_classes.BaseEventProcessing)
- Method process_event() returns event of class EventAnalysisRecordWorkshop
- event_analysis_record_workshop.py
- Class EventAnalysisRecordWorkshop(EventAnalysisRecordV3Base)
- tsv_event_storage.py
- Management of output into tsv files
- processing_functions.pyx – various algorithms, Cython
Feature extraction procedure skeleton
- Classes
- EventProcessingWorkshop – main class
- EventProcessingParamsWorkshop – parameters of the procedure
- VisualizationOptions – interactive visualization options
- SavefigOptions – plotting related options
- get_attr_numbering_dict() – information about generated features for event storage (mainly for SQL CREATE)
- process_event() – feature extraction procedure wrapper
- Parsing of the arguments
- Construction of the frames sequence(s)
- process_pdm() loop
- process_pdm() – handling of the feature extraction per PDM
- Calibration map
- Background subtraction
- Projection images construction
- process_single_projection() loop
- process_single_projection()
- Filtration, Thresholding, …
- Hough transform
- Line orientation
- Output