Welcome to the Visual Layer documentation! This guide introduces you to Visual Layer, a powerful platform designed to revolutionize how you manage and analyze visual data. By addressing challenges like disorganization, scattered storage, and poor data quality, Visual Layer empowers teams to work more efficiently, improve model performance, and reduce costs. Its scalable and collaborative tools make it indispensable for handling datasets of any size, enabling you to streamline workflows and unlock actionable insights. Visual Layer provides a centralized platform to curate, manage, and analyze visual data at scale. By leveraging advanced filtering, visualization tools, and organizational features, it transforms how teams interact with complex datasets. Whether you’re looking to save time, enhance collaboration, or improve the quality of your data, Visual Layer seamlessly integrates into your workflows to drive innovation and success.

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Browser Requirements

Chrome browser is recommended for the best Visual Layer experience. While other browsers like Firefox may work for basic functionality, they are not fully supported and may have compatibility issues with advanced features.

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Key features

At its core, Visual Layer is built to simplify the complexities of working with large-scale datasets. It provides tools for:
  • Dataset exploration: Explore and identify patterns and outliers by going over clusters of similar images, objects, and video frames
  • Semantic & Visual search: Quickly find relevant data using natural language queries or a reference image/object.
  • Data organization: Tag relevant data or save filtering queries as Views for future use
  • Data quality improvement: Identify, review and address critical issues like duplicates, annotation errors and outliers
  • Data enrichment: Enhance your data by generating metadata using advanced, cutting-edge models

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Use cases for using Visual Layer

Visual Layer is versatile and can be applied across various industries and scenarios. Here are some common use cases:
  • AI models development: Prepare and refine datasets for training models by identifying and removing duplicates or outliers, ensuring data quality and representativeness
  • Manufacturing & logistics: Optimize workflows and manufacturers to harness the full potential of your visual data for a competitive edge
  • Defense & security: Manage and analyze video feeds for event detection and categorization
  • Media & entertainment: Organize large media libraries and quickly locate specific assets using powerful filtering tools
  • Retail & E-commerce: Analyze product imagery for consistency, quality control, and trend identification
  • Healthcare & research: Explore medical imaging datasets to uncover patterns or anomalies efficiently

Ready to dive in?

Check out our Quick Start guide to unlock the full potential of your visual data.