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Overview

  • What is Lightly?

Getting Started

  • Install Lightly
  • Set Up Your First Dataset
  • Run Your First Selection
  • Analyze the Selection Results
  • Export Filenames

Advanced

  • Videos as Input
  • Customize a Selection
    • Selection Strategy Combination
    • Active Learning Scorers
  • Train a Self-Supervised Model
  • Relevant Filenames
  • Datapool
  • Corruptness Check
  • Sequence Selection
  • Custom Embeddings
  • Configuration Options
  • Outputs
    • Report
    • Dataset Metrics
    • Embeddings
    • Corruptness Check Information
    • Other Outputs
  • Automation
    • Automation with Python
    • Metaflow
    • Dagster

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

Providing Data to Lightly

  • Cloud Storage
    • AWS S3
    • Azure
    • Google Cloud Storage
  • Work with Metadata
  • Work with Predictions
    • Prediction Format
    • Lightly Pretagging

The Lightly Platform

  • Overview
  • Core Concepts
    • Datasets
    • Tags
    • Samples
    • Runs
    • Collaboration
    • Crop Datasets
  • Analyze and Filter
    • Metadata
    • Correlation
    • Embeddings
  • Export
    • Filenames and ReadURLs
    • Labelbox
    • Label Studio
  • Metadata Configuration

Other Bits

  • Security
  • Hardware Recommendations
  • Known Issues & FAQ
  • Debugging
  • Contact Us
  • Assign Scheduled Runs to Specific Workers
  • Migration guides
    • Migrating to Worker v2.4
    • Migrating to Worker v2.5
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Migration guides

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Migrating to Worker v2.4
Migrating to Worker v2.5

Updated 26 days ago