This article present a video on how to use a technique called "Transfer learning" to quickly train a deep learning model in order to classify images.
This video teaches you how to use ST ecosystem to build a computer vision application from the ground up. It describes how the FP-AI-VISION1 allows easy image collection with an STM32 Discovery kit, how to use transfer learning with Tensorflow to quickly train an image classification model, and eventually how to use STM32Cube.AI to convert this model into optimized code for ST microcontrollers.
The Jupyter notebook used in this video is available on Github. It can be opened with Colab.
For a complete example on how to use your own models with the FP-AI-VISION1, refer to check out this article. In addition, this series of videos gives a good overview of the Vision Function Pack.