Machine learning enthusiast living in Tokyo. Prev Gengo & Lionbridge AI
The term ‘curation’ is commonly associated with museums or libraries, not data science. However, much like the work that’s done on rare paintings or books, data curation tools make the most important data easily accessible to engineers as they build complex machine learning models.
Without curation, data is difficult to find, analyze, and interpret. Data curation tools provide meaningful insights and enduring access to all your data in one place. In this article, we’ll dive into the importance of data curation for computer vision specifically, as well as review the top data curation tools on the market today.
Data curation is the act of organizing, enhancing, and preserving data for future use. In machine learning, data curation describes the management of data throughout its lifecycle: from its collection and initially storage, to the time it is archived for future re-use.
This process is all the more important for computer vision engineers, who deal with massive amounts of visual data on a daily basis. Instead of using manual methods such as writing ETL jobs to extract insights, data curation tools provide a streamlined way to access the right data whenever you need to.
Under the hood, data curation tools directly influence computer vision model performance. Using data curation tools, engineers can get a better understanding of the data they’ve collected, identify the most important subsets and edge cases, and curate custom training datasets to feed back into their models.
The best data curation tools enable you to:
With an overwhelming amount of AI products and platforms popping up year after year, how do you know which will provide the most value? Read on below to find out which data curation tool is the best fit for your computer vision project.
Aquarium is a data management platform that aims to make it easy to identify labeling errors and model failures. With Aquarium, users can version and combine model predictions with their ground truth.
Aquarium is especially focused on curating and maintaining training datasets, catering less to raw data management use cases. This is because data exploration in Aquarium is predominantly tied to model predictions and ground truth labels.
Users can access Aquarium via their cloud platform or API. However, they currently do not offer on-premise or VPC deployments, and there are no external integrations.
Developed by Voxel51, FiftyOne is an open-source tool to visualize and interpret computer vision datasets. The tool is made up of three components: the Python library, the web app (GUI), and the Brain.
FiftyOne does not contain any auto-tagging capabilities, and therefore works best with datasets that have previously been annotated. Furthermore, the tool only supports image and video data, and does not work for multimodal sensor datasets at this time.
Unlike other tools, FiftyOne is designed to be used by individual developers rather than teams, functioning like a programming IDE. Today, the platform lacks collaborative features; for example, a single instance cannot host multiple user accounts.
Launched in late 2020 by Scale, Nucleus is one of the newest data curation tools to hit the market. The Nucleus platform allows users to collaboratively search through image data for model failures. As of now, Nucleus only supports image data, with no support for 3D sensor fusion, video, or text data.
Users can access Nucleus via their cloud platform, API or Python SDK. Currently, Nucleus does not support on-premise deployability.
Clarifai is an end-to-end solution for labeling, searching & modeling unstructured data. One of the first AI startups, they provide a platform for modeling image, video, and text data. While Clarifai’s original focus was enabling users to build custom models, they’ve recently added several data curation features including auto-tagging, visual search, and annotations.
Ultimately, Clarifai is more of a modelling platform and less of a developer tool. They are best suited for relatively inexperienced teams getting started with ML use cases.
SiaSearch is a data management platform for computer vision data. Consisting of a scalable metadata catalog and query engine, SiaSearch enables developers to easily search through visual data, add metadata to frames and sequences, as well as assemble custom subsets of data for training or testing.
With deep roots in autonomous driving, the SiaSearch platform is used by many OEMs, Tier 1s and tech companies. Aside from autonomous driving, SiaSearch also has solutions for robotics, retail, and more.
The right data curation tool can dramatically reduce the time spent on manual processes, allowing engineers to focus on what really matters - building great models.
Lead image via Tobias Fischer on Unsplash
Originally published by Clemens Viernickel on: https://www.siasearch.io/blog/best-data-curation-tools-for-computer-vision and has been reposted with permission.
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