I was trying a python http communication tutorial - https://aiohttp-demos.readthedocs.io/en/latest/tutorial.html#views - when I had to disable the NI Application Web Server to proceed. And then I thought, what the **** am I doing? Maybe I should take the free (well, prepaid) gift of a working web server.
Here's my task. A central HQ computer will have a GUI that monitors five machine stations, each of which has its own computer. Every approx 10 ms (negotiable), each station gives a report consisting of two arrays, the larger being 2048 data points, the other much smaller. Whenever HQ feels like it, HQ can tell a station to start or stop (its computer stays on). A local IP connection is used, with a router at each end. There is also a Raspberry Pi with its own IP address at each station's router, that can send camera frames to HQ. The station-computers use Python and C++ to do their work, not counting whatever needs to be added to communicate with HQ.
Your advice please? Should I use Labview? On both ends or just the HQ? And which if any of these helpful add-ons suggested by Hooovahh should I use?
TDF team is proud to propose for free download the scikit-learn library adapted for LabVIEW in open source.
LabVIEW developer can now use our library for free as simple and efficient tools for predictive data analysis, accessible to everybody, and reusable in various contexts.
It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy from the famous scikit-learn Python library.
Coming soon, our team is working on the « HAIBAL Project », deep learning library written in native LabVIEW, full compatible CUDA and NI FPGA.
But why deprive ourselves of the power of ALL the FPGA boards ? No reason, that's why we are working on our own compilator to make HAIBAL full compatible with all Xilinx and Intel Altera FPGA boards.
HAIBAL will propose more than 100 different layers, 22 initialisators, 15 activation type, 7 optimizors, 17 looses.
As we like AI Facebook and Google products, we will of course make HAIBAL natively full compatible with PyTorch and Keras.
Sources are available now on our GitHub for free : https://www.technologies-france.com/?page_id=487
I would like to build a model using image data and NI-cRIO-9063 and NI 9264 for voltage control.
for image, I made a script in python using OpenCV libraries that detecting some points . For voltage control, I use cRIO-9063 with NI 9264 voltage controller.
My question is, I am new in LabVIEW and I don't have any idea how can I make a loop for voltage control in python. Is there any library available in python that directly connect cRIO and NI 9264 devices? if not then how can I combine my image data(which is in python) with cRIO device? I need argent help.
I recently stumbled upon this issue while debugging an application that didn't handle JSON payload as expected.
As it turns out, Unflatten From JSON breaks on NUL characters, even though Flatten To JSON properly encodes them as ("\u0000").
I have confirmed the behavior in LabVIEW 2017, 2019, and 2020 (all with latest service packs and patches), currently waiting for confirmation by NI.
Workaround: Use JSONtext
I am just starting on trying to be able to use Python code from a LabVIEW application (mostly for some image analysis stuff). This is for a large project where some programmers are more comfortable developing in Python than LabVIEW. I have not done any Python before, and their seem to be a bewildering array of options; many IDE's, Libraries, and Python-LabVIEW connectors.
So I was wondering if people who have been using Python with LabVIEW can give their experiences and describe what set of technologies they use.