Top 6 Computer Vision Data Management Tools

Google recently released a virtual try-on computer vision (CV) model that lets users see how clothing items will look on different models in various poses. This is just one example of how CV is revolutionizing the retail industry and changing human interaction with AI systems. However, creating advanced CV applications requires training CV models on high-quality data, which can be challenging due to increasing data volume and variety. Proper data management involves ingesting, storing, and curating data to ensure users have access to high-quality datasets for model training and validation. Key challenges include maintaining data security, managing complex data ecosystems, and dealing with large data volumes and varieties. To address these issues, consider factors such as user experience, integration capabilities, searchability, metadata management, and security when selecting a computer vision data management tool. Some top tools include Encord, Scenebox, Picsellia, DataLoop, Tenyks, and Nucleus by Scale.