OpenVINO vs Aquarium: What are the differences?

Developers describe OpenVINO as "A free toolkit facilitating the optimization of a Deep Learning model". It is a comprehensive toolkit for quickly developing applications and solutions that emulate human vision. Based on Convolutional Neural Networks (CNNs), the toolkit extends CV workloads across Intel® hardware, maximizing performance. On the other hand, Aquarium is detailed as "*Improve Your ML Dataset Quality *". Machine learning models are only as good as the datasets they're trained on It helps ML teams make better models by improving their dataset quality..

OpenVINO and Aquarium can be primarily classified as "Machine Learning" tools.

Some of the features offered by OpenVINO are:

• Optimize and deploy deep learning solutions across multiple Intel® platforms
• Accelerate and optimize low-level, image-processing capabilities using the OpenCV library
• Maximize the performance of your application for any type of processor

On the other hand, Aquarium provides the following key features:

• Upload your dataset to get a health check of its quality, quantity, and diversity. Zoom in and out of your dataset. Uncover distribution biases before you train. Find and fix labeling errors quickly
• Upload model inferences against your labeled datasets and deep dive into its performance. Find where your model is performing well and badly so you can take the best actions to improve it
• With knowledge of your dataset diversity and model performance, it automatically samples the best data to sample to label and retrain on. Your model performance just gets better