Documentation and Support
  • Welcome to Dockship!
  • User Accounts
    • Creating a User Account
    • Creating a Recruiter or Organization Account
    • Completing Your Profile
    • Updating your Dockship Username
    • Completing your KYC
    • Messaging
  • Challenges on Dockship
  • Types of Challenges
  • Participating in a Challenge
  • Downloading a Dataset
  • Making a submission
  • Leaderboard
  • Public - Private Leaderboard
  • Discussion
  • Notebooks
  • Gems
    • About Gems
  • Articles
    • About Articles
    • Using the Editor and Publishing your Article
    • Adding a Youtube Video in your Article
    • Moving, and Deleting a Section
    • Article Settings
    • Monetizing your Article
    • Article FAQs
  • Creating a Challenge
    • About Challenges
    • Creating a New Challenge
    • Automating Submission Grading
    • Creating a Challenge From Scratch
  • Publishing your AI Model
    • Purchasing the Developer Pass
    • Preparing your AI Model
    • Submitting your AI Model
    • Preparing Dockerfile for your model
  • Achievements
    • About Achievements
    • Hall of Fame (HOF)
Powered by GitBook
On this page

Was this helpful?

  1. Publishing your AI Model

Preparing your AI Model

This guide will help you in structuring your AI Model

Your model should have the following structure:

  • Input (Directory)

  • Output (Directory)

  • requirements.txt (File)

  • README.md (File)

  • src (Directory)

  • src / run.py (File)

  • stats (Directory)

Input - 'Input' directory contains sample source images / Videos for inference.

Output - 'Output' directory contains sample outputs which were generated by inference on 'Input' directory.

requirements.txt - 'requirements.txt' should list all the python dependencies with versions. You can use: pip freeze > requirements.txt to generate this file.

README.md - This file tells other people why your project is useful, what they can do with your project, and how they can use it.

src - 'src' directory contains all the source code for I/O, pre-processing and post-processing along with the trained model.

src/run.py - This is the main python file that the user calls. It should be able to take at least 'input' (Input path) and 'output' (Output path) as arguments. Example -

python src/run.py --input Input --output Output

stats - This directory may contain one or more files. Each file stores inference time taken on particular hardware. Example - 'cpu.txt' stores inference time on CPU.

Above mentioned are the necessary files/directories which your model should have. It may contain additional files if your model requires.

Once you have structured your model according to the above template, compress the folder as a zip file.

PreviousPurchasing the Developer PassNextSubmitting your AI Model

Last updated 4 years ago

Was this helpful?