What is a Computer Vision Platform?

There is a combination of factors that are preventing CV from becoming mainstream. Let’s have a look at them too:

• Time shortages – This challenge can simply be attributed to the time shortage that the companies have to build or to even generate a proof of concept for the implementation of CV. Studying and preparing a proper plan will require months if not years. Hence, most companies despite the will won’t invest a lot of time in CV.
• Limited expertise in CV – Even if a company decides to go forward, plans, and creates a POC for the implementation, there will always be a higher chance of them not knowing the steps forward. As building CV systems is highly technical and requires setting up a proper team of expensive engineers to get started, most companies would dare not go forward.
• Difficulties in setting up a proper system for deployment – If a company overcomes the challenge of building a good CV solution for their business use case, deploying and interacting with it will again require setting up a proper system with an easy-to-use UI so that anyone can use it. Failure to do so will create a solution just accessible to certain technical people and hence will not be adopted properly.
• Limited monitoring of CV models – After building and deploying a proper CV solution, the models must be monitored for their performances regularly. Failure to do so will lead to a CV solution that works at the beginning of the deployment but becomes useless as time passes by. A proper retraining pipeline will also be required to keep the model well-functioning.