MeqdadDev/teachable-machine-lite
A lightweight Python package optimized for integrating exported models from Google's Teachable Machine Platform into robotics and embedded systems environments. This streamlined version of Teachable Machine Package is specifically designed for resource-constrained devices, making it easier to deploy and use your trained models in embedded apps.
This helps developers deploy trained machine learning models, specifically image classification, from Google's Teachable Machine platform onto small, less powerful devices like those found in robotics or IoT projects. You input a trained model file and image data, and it outputs classification predictions, enabling your embedded system to 'see' and react. It's designed for engineers building smart devices with limited computing resources.
No commits in the last 6 months. Available on PyPI.
Use this if you need to integrate a custom image classification model from Teachable Machine into an embedded system or robot that has limited processing power and memory.
Not ideal if you are working with large-scale cloud-based AI applications or have ample computing resources for model deployment.
Stars
10
Forks
2
Language
Python
License
MIT
Category
Last pushed
Nov 18, 2024
Commits (30d)
0
Dependencies
3
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