It reduces the required processing power on the CPU and GPU. With OpenVINO, you can run your normal algorithms and normal software on CPU, but don't require a huge amount of processor power. It is faster, and you have plenty of more resources for other jobs.
It is easy to manage the software with OpenVINO. You can change the number of models or quotes. I can use five quotes for a model, or I can write a particular model with a quote. Management is easy without touching the software.
OpenVINO toolkit quickly deploys applications and solutions that emulate human vision. Based on Convolutional Neural Networks (CNNs), the toolkit extends computer vision (CV) workloads across Intel hardware, maximizing performance. The OpenVINO toolkit includes the Deep Learning Deployment Toolkit (DLDT).
The initial setup is quite simple.
The inferencing and processing capabilities are quite beneficial for our requirements.
It reduces the required processing power on the CPU and GPU. With OpenVINO, you can run your normal algorithms and normal software on CPU, but don't require a huge amount of processor power. It is faster, and you have plenty of more resources for other jobs.
It is easy to manage the software with OpenVINO. You can change the number of models or quotes. I can use five quotes for a model, or I can write a particular model with a quote. Management is easy without touching the software.
The features for model comparison, the feature for model testing, evaluation, and deployment are very nice. It can work almost with all the models.