logo

SLEAP (v1.2.6)

  • Home
  • Overview
  • Installation
  • Tutorial
    • Creating a project
    • Initial Labeling
    • Training and Inference
    • Prediction-assisted labeling
    • Tracking instances across frames
    • Export Data For Analysis
  • Guides
    • GUI
    • Command line interfaces
    • Troubleshooting workflows
    • Skeleton design
    • Configuring models
    • Importing predictions for labeling
    • Tracking and proofreading
    • Run training and inference on Colab
    • Creating a custom training profile
    • Running SLEAP remotely
  • Notebooks
    • Training and inference on an example dataset
    • Training and inference on your own data using Google Drive
    • Model evaluation
    • Analysis examples
    • Data structures
    • Post-inference tracking
    • Interactive and resumable training
    • Interactive and realtime inference
  • Developer API
  • Datasets
  • GitHub
  • Releases
  • Help
  • repository
  • open issue

Tutorial

Tutorial#

The tutorial will walk you through the entire SLEAP workflow as described in the Overview. You can read through this tutorial and try running SLEAP on one of our sample datasets. Then you will be ready to start using SLEAP on your own data.

  • Creating a project
    • Starting SLEAP
    • Opening a video
    • Creating a Skeleton
  • Initial Labeling
    • Selecting frames to label
    • Labeling the first frame
    • Saving
    • Labeling more frames
  • Training and Inference
    • Training Options
    • Start Training
    • Inference
  • Prediction-assisted labeling
  • Reviewing and fixing predictions
  • Tracking instances across frames
    • Track proofreading
  • Export Data For Analysis
    • MATLAB
    • Python

previous

Installation

next

Creating a project

By SLEAP Developers
© Copyright 2019–2022, Talmo Lab.