Speaker
Description
Area Detector is widely used in accelerator and observatory control systems to build data processing pipelines for images and waveforms, but adding new processing stages normally requires specialized C++ development. This slows prototyping and limits access to modern analysis tools that are predominantly available in Python. We present a new Area Detector plugin that executes user-defined Python algorithms directly on acquired images and their metadata. The plugin integrates advanced scientific libraries and machine learning toolkits, supports GPU acceleration, and enables parallel execution through multi-stage pipelines or Python multiprocessing. Algorithms can be updated without recompiling the IOC, allowing rapid iteration during operations. An automatically generated GUI exposes configurable parameters to operators. The approach is being evaluated on ESA’s NEOSTED telescope system, where Python-based routines are used for telescope autofocusing.
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Funding Agency
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| Paper status | Resubmitted proceeding files received and assigned to an editor. Accepted by Submitter. |
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