Azure AI Vision vs. National Instruments Vision Builder AI

It offers a great option for IoT and simple repetitive tasks with simple configuration but it requires having previous knowledge of Microsoft tools to get familiar with how to use it. I also think it is excellent for classification especially if your requirements about specific tools could need a lot of studies.

Incentivized

The perfect scenario is a production environment where items are passing in front of a camera on some type of conveyor system. Vision Builder AI can be set up to inspect those items and make decisions that can be handled down the line (rejection, sorting, etc.). It's great if you have an isolated vision system as part of a larger system that needs to just pass on results. It's not as well suited if you need that code tightly coupled with other code, such as vision-guided robotics.

Incentivized

• Out of the box capabilities.
• Options of analysis.

Incentivized

• Material to learn.

Incentivized

It all comes down to tradeoffs. Do you want something that is extremely flexible and full-featured or do you want something that is easy and fast to use? Sure there are things that you can't do in Vision Builder AI that you can implement in LabVIEW, however, the vast majority of the applications that we work on do not need that extra functionality so Vision Builder AI is the best choice for us. If we find out along the way that Vision Builder AI is not going to work for us at least we have all of the steps and parameters figured out that we can use when moving to LabVIEW.

Incentivized

• It provided easy configuration for project requirements.
• Allow me to execute simple tests.
• Great manage of resources.

Incentivized