PerceptiLabs
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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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  1. How to Contribute

Models

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Last updated 3 years ago

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At PerceptiLabs, we strongly believe in building a rich and diverse community of ML practitioners who can share and benefit from each other's contributions.

To share a model that you've created in PerceptiLabs, make a new thread on the PerceptiLabs forums and post the following:

  • The name of the model

  • Its application area

  • A preview of the model on the workspace

  • (Optional) A description of what it is and how it works

  • Required input types

  • Required target types

  • Dataset it was built for

  • The model.json file and (optionally) the checkpoint files

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