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Overview & Quick Start
What is LightlyOne?
Quick Start
Getting Started
Install LightlyOne
Set Up Your First Dataset
Run Your First Selection
Analyze the Selection Results
Export Filenames
Selection
Selection
Examples and Use Cases
Input and Strategy Combinations
Selection Input
Selection Strategies
Selection Algorithm
Active Learning Scorers
Providing Data to LightlyOne
Cloud Storage
AWS S3
Azure
Google Cloud Storage
Local Storage
Mount Permissions
Work with Metadata
Work with Predictions
Prediction Format
Lightly Pretagging
Tutorials
Active Learning Using YOLOv7 and Comma10k
Active Learning Using YOLOv7 for Waste Sorting
Active Learning for Driveable Area Segmentation Using Cityscapes
Active Learning for Transactions of Images
Improving YOLOv8 using Active Learning on Videos
Assertion-based Active Learning with YOLOv8
Active Learning for Sports Applications using Keypoint Detections
Use Similarity Search to Find Similar Samples
Advanced
Videos as Input
Train a Self-Supervised Model
Relevant Filenames
Datapool
Corruption Check
Crop Selection
Sequence Selection
Custom Embeddings
Configuration Options
Outputs
Report
Report - Embedding Analysis
Report - Selection Results Dashboard
Embeddings
Corruptness Check Information
Other Outputs
Automation
Multiple Workers
Automation with Python
Metaflow
Dagster
AWS Batch
The LightlyOne Platform
Overview
Core Concepts
Datasets
Tags
Samples
Runs
Collaboration
Crop Datasets
Analyze and Filter
Metadata
Correlation
Embeddings
Export
Filenames and ReadURLs
Labelbox
Label Studio
Teams
Other Bits
Security
Hardware Recommendations
Known Issues & FAQ
Common Errors That Abort the LightlyOne Worker
Debugging
LightlyOne Worker Installation Guide
Migration guides
Migrating to Worker v2.11
Migrating to Worker v2.10
Migrating to Worker v2.9.5
Migrating to Worker v2.9
Migrating to Worker v2.8
Migrating to Worker v2.7
Migrating to Worker v2.6
Migrating to Worker v2.5
Migrating to Worker v2.4
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Work with Predictions
Updated 3 days ago
Work with Metadata
Prediction Format