PerceptiLabs
v0.13
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  • Welcome
  • ⚡Getting Started
    • Quickstart Guide
      • Requirements
      • Installation
      • Video Tutorials
    • Load and Pre-process Data
    • Build Models
    • Train Models
    • Evaluate Models
    • Export and Deploy Models
    • Manage, Version, and Track Models
  • 🙏How to Contribute
    • Datasets
    • Models
    • Components
  • 👨‍🍳Tutorials
    • Basic Image Recognition
    • Basic Image Segmentation
  • 🛠️Advanced
    • Common Testing Issues
    • Common Training Issues
    • Components
      • Input and Target
      • Processing
      • Deep Learning
      • Operations
      • Custom
    • CSV File Format
    • Debugging and Diagnostic Features
    • How PerceptiLabs Works With TensorFlow
    • Included Packages
    • Types of Tests
    • UI Overview
      • Data Wizard
      • Overview Screen
      • Model Training Settings
      • Modeling Tool
      • Training View
      • Evaluate View
      • Deploy View
    • Using the Exported/Deployed Model
  • 💡Use Cases
    • General
      • A Guide to Using U-Nets for Image Segmentation
      • A Voice Recognition model using Image Recognition
    • Environmental
      • Automated Weather Analysis Using Image Recognition
      • Wildfire Detection
    • Healthcare & Medical
      • Brain Tumor Detection
      • Breast Cancer Detection
      • Classifying Chest X-Rays to Detect Pneumonia
      • Classifying Ways to Wear a Face Mask
      • Detecting Defective Pills
      • Highlighting Blood Cells in Dark-field Microscopy Using Image Segmentation
      • Ocular Disease Recognition
      • Retinal OCT
      • Skin Cancer Classification
    • Industrial IoT & Manufacturing
      • Air Conditioner Piston Check
      • Classifying Fruit
      • Classifying Wood Veneers Into Dry and Wet
      • Defect Detection in Metal Surfaces
      • Fabric Stain Classification
  • 📖Support
    • FAQs
    • Changelog
  • Code of Conduct
  • Marketing Site
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On this page
  • Key Elements of the Perceptilabs UI
  • Zooming and Scrolling in the Modeling Tool

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UI Overview

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Last updated 3 years ago

PerceptiLabs is a visual modeling tool for machine learning with a rich user interface to edit, manage, and monitor your machine learning models while designing and training them.

Note: After logging in to PerceptiLabs you will be redirected to the Model Hub where you can create and manage your models.

Tip: Also be sure to check out our UI Overview video on the video tutorials page.

Key Elements of the Perceptilabs UI

The following are the main elements of the Perceptilabs UI:

  1. Model Hub (Overview): lists existing models that have been created in PerceptiLabs and allows you to view and manage those models.

  2. Modeling Tool (Model): the main workspace area where you build your models.

  3. Training : displays the training statistics for the currently-running, or recently-trained model.

  4. Evaluate: displays statistics about your trained model after it has been tested against test data. You can also create new tests here.

  5. Deploy: provides options to deploy your trained model.

  6. Components: provides Components which you can drag and drop onto your model.

  7. Save: saves the changes that you've made to the current model.

  8. Color Scheme and Quick Links: provides the following links:

    • Color Scheme: allows you to toggle between light and dark color schemes

    • Chat: opens a chat window so you can ask us questions.

    • Report a Bug: opens the forums where you can report bugs or find solutions.

    • Help: provides links to documentation and other resources.

  9. Data Settings: displays the data settings that are used by the model. These were initially set when you first created the model using the Data Wizard.

  10. Login/Logout: allows you to sign in and out of PerceptiLabs.

  11. Run: starts training the current model.

  12. Weights: load and use your most recent checkpoint.

  13. Preview: toggles weather PerceptiLabs displays previews in the model's components.

  14. Settings: toggles display of the settings and components panes down the right.

  15. Open Code: opens the Code Editor for the currently selected component.

  16. Zoom Controls: allows you to zoom in and out of the model (see Zooming and Scrolling in the Modeling Tool below for more information).

  17. Map: displays a small view of the model which can be useful for quickly scrolling across models with large topologies.

  18. Grid: displays a grid in the background to help you visually align your model's Components.

  19. Problems List: displays a list of errors detected in the model.

  20. Console: displays notifications related to the model.

Zooming and Scrolling in the Modeling Tool

You can zoom and scroll the model using the controls at the bottom of the Modeling Tool:

Use the Zoom controls (2) to zoom in and out.

You can optionally enable the background grid by selecting Grid (4).

To scroll a model when zoomed in, you can:

  • Enable the Map (3) and then drag the red view rectangle (1); or

  • Hold down Ctrl + Left Mouse button or the middle mouse button and drag the view (5).