Amazon Rekognition vs. National Instruments Vision Builder AI

Amazon Rekognition is well suited for all image and videos analysis. Also, deep learning projects for image and video can easily be done using this. It is very easy to use so a beginner can also use it.

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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.

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• Image tagging is very good.
• Object detection is precise.
• Video tagging has become very easy using Rekognition.

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• The cost is bit more for small scale companies.
• For text processing, OCR is not available in amazon rekognition.
• Only facial search is available in image search.

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Very much suitable for many applications where the image processing features are secondary and independent of any domain. This makes it a general solution and the recognition features are returned in a JSON object in response to the API called made which is a very simple process.

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Support of Amazon is great. So far we are having a great experience using it.

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It's easy to implement and its documentation is great compared to CNTK.

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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.

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• The best thing it made our work fast.
• It reduces the chance of failure of a project which is based on image or video processing.
• We can assign anyone in our team to work on this as it very easy to use.

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