Introduction

Welcome to the Visual Layer documentation! This guide will help you understand what Visual Layer is, how it can benefit you, and how to get started. Whether you're managing visual data at scale or exploring new ways to organize and analyze datasets, this is your go-to resource.

What is Visual Layer?

Visual data is often disorganized, scattered, and often contains poor-quality data, making it difficult to manage, maintain, and extract value from in its raw form.

Manual processes for handling and sorting large volumes of data are inefficient, expensive, error-prone, and outdated. Using such methods impacts businesses in time-to-market, service quality, maintaining competitive edge and costs.

Visual Layer is a platform designed to empower users to curate, manage, and analyze visual data at scale.

By combining advanced filtering, visualization tools, and organizational features, Visual Layer transforms how teams work with complex datasets. It seamlessly integrates with your workflows to offer a centralized hub for exploring visual data and gaining actionable insights.

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: Find the data you're looking for quickly by using natural language 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

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:

Technology and software: Prepare and refine datasets for training models by identifying and removing duplicates or outliers, ensuring data quality and representativeness
Manufacturing and logistics: Optimize workflows and empower manufacturers to harness the full potential of your visual data for a competitive edge
Defense and security: Manage and analyze video feeds for event detection and categorization
Media and entertainment: Organize large media libraries and quickly locate specific assets using powerful filtering tools
Retail and E-commerce: Analyze product imagery for consistency, quality control, and trend identification
Healthcare and research: Explore medical imaging datasets to uncover patterns or anomalies efficiently

Benefits

Visual Layer offers numerous advantages that make it indispensable for working with visual data:

Time efficiency: Enhance your teams' productivity by reducing the time spent on data preparation and analysis, finding data quicker and automating data quality and annotation workflows
Better models: Better data leads to better models. Improve the reliability of your datasets to train high-performing models
Cost efficiency: Save money by reduces the labor and time required for data selection and preparation, and decrease storage costs by cleaning and streamlining your data
Scalability: Handle datasets of any size, from small collections to millions of images or videos
Collaboration: Share saved views and insights with team members to align efforts

Getting started

Ready to dive in? Follow these steps to get started with Visual Layer:

Sign up or log in: Create an account or log in to access the platform
Create a Dataset: Import your images or videos into the platform
Explore your data: Use filters, visualizations, and saved views to analyze and organize your dataset
Organize data: Customize Tag and Views and save your configurations for quick access later
Collaborate: Share your saved views or insights with team members to streamline teamwork

For more detailed instructions, check out our Getting Started Guide.