PyNTA: An Open Source Software Application for Live Particle Tracking. Faez, S.; Carattino, A.; and Mosk, A. June, 2019. Publisher: Preprints
PyNTA: An Open Source Software Application for Live Particle Tracking [link]Paper  doi  abstract   bibtex   
We introduce PyNTA, a modular instrumentation software for live particle tracking. By using the multiprocessing library of Python and the distributed messaging library pyZMQ, PyNTA allows users to acquire images from a camera at close to maximum readout bandwidth while simultaneously performing computations on each image on a separate processing unit. This publisher/subscriber pattern generates a small overhead and leverages the multi-core capabilities of modern computers. We demonstrate capabilities of the PyNTA package on the featured application of nanoparticle tracking analysis. Real-time particle tracking on megapixel images at a rate of 50 Hz is presented. Reliable live tracking reduces the required storage capacity for particle tracking measurements by a factor of approximately 103, as compared with raw data storage, allowing for a virtually unlimited duration of measurements
@article{faez_pynta_2019,
	title = {{PyNTA}: {An} {Open} {Source} {Software} {Application} for {Live} {Particle} {Tracking}},
	shorttitle = {{PyNTA}},
	url = {https://www.preprints.org/manuscript/201906.0251/v1},
	doi = {10.20944/preprints201906.0251.v1},
	abstract = {We introduce PyNTA, a modular instrumentation software for live particle tracking. By using the multiprocessing library of Python and the distributed messaging library pyZMQ, PyNTA allows users to acquire images from a camera at close to maximum readout bandwidth while simultaneously performing computations on each image on a separate processing unit. This publisher/subscriber pattern generates a small overhead and leverages the multi-core capabilities of modern computers. We demonstrate capabilities of the PyNTA package on the featured application of nanoparticle tracking analysis. Real-time particle tracking on megapixel images at a rate of 50 Hz is presented. Reliable live tracking reduces the required storage capacity for particle tracking measurements by a factor of approximately 103, as compared with raw data storage, allowing for a virtually unlimited duration of measurements},
	language = {en},
	urldate = {2020-07-25},
	author = {Faez, Sanli and Carattino, Aquiles and Mosk, Allard},
	month = jun,
	year = {2019},
	note = {Publisher: Preprints}
}
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