HOOPS AI 1.0-b2 release on: February 2nd, 2026

see what is new here: https://docs.techsoft3d.com/hoops/ai/resources/release_notes/index.html

Documentation

visit our documentation here: https://docs.techsoft3d.com/hoops/ai/

HOOPS-AI-tutorials

Tech Soft 3D tutorials of python CAD framework for machine learning development - HOOPS AI

Recording of the webinar hold on November 6th. Presenting HOOPS AI, check it out!:

This repository provides a collection of tutorial materials designed to help users learn and apply the HOOPS AI library.

Developed in Python, it features Jupyter notebooks that guide users through practical use cases and workflows.

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Dependency

🪪 1. Get Access first!

Requirements: Python > 3.9 and MiniConda (24.x) Ask your TECH SOFT 3D contact to give you acces to HOOPS AI 1.0 beta-2 preview. Go to: https://www.techsoft3d.com/developers/products/hoops-ai

pip install hoops-ai-installer .........(full code to be received by email)
hoops-ai-installer install --mode cpu
hoops-ai-installer install --mode gpu

Note: You will need to set your HOOPS AI license to execute the notebooks

Running the Notebooks

Download the input data for the notebooks

Fetch test files for the tutorials - Require password to be received by email

Go to: https://transfer.techsoft3d.com/link/dc8ogpj5B7S6U3iZIC6pcG

extract the zip and name this packages.

Activate the development environment

Open a cmd in the location of this repo. If HOOPS AI is installed, then activate the environment of you choice (cpu or gpu):

conda activate hoops_ai_gpu

or

conda activate hoops_ai_cpu

then run inside the environment the jupyter lab command:

jupyter lab

A browser will open with your local folder, in the environment double click the folder notebooks and follow each notebook instructions.

Each notebook contains step-by-step instructions and annotations.

Proceed through each notebook in order, running the cells interactively.

hoops_ai_tutorials/
│
├── notebooks/         # Jupyter notebooks for each tutorial
├── packages/          # Downloaded binary assets (unzipped before accesing them)
└── README.md
|___ ...

If you have never used jupyter notebook for python code, you can learn the basics here: https://justinbois.github.io/bootcamp/2020_fsri/lessons/l01_welcome.html