Replies: 1 comment 1 reply
-
OpenMV has a Tensorflow module. To use that one has to use the OpenMV "distribution" of MicroPython (not the official downloads). See their documentation Otherwise, there is a CNN module in emlearn-micropython, which is distributed as a drop in .mpy module. I have tested it a bit on ESP32. This is based on TinyMaix, which takes a Keras/Tensorflow network or a .tflite file, and converts it to their format. See the examples at https://github.com/emlearn/emlearn-micropython/tree/master/examples/mnist_cnn |
Beta Was this translation helpful? Give feedback.
1 reply
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Uh oh!
There was an error while loading. Please reload this page.
Uh oh!
There was an error while loading. Please reload this page.
-
I am working on a project that involves using MicroPython and a Convolutional Neural Network (CNN) for face recognition. I already have the model saved in a .tflite format. However, I am struggling to find a way to import and use the .tflite file in MicroPython.
I have tried:
Importing TensorFlow (import tensorflow as tf), but TensorFlow isn't supported in MicroPython.
Searching online for solutions or libraries that might work with MicroPython, but I haven't found a clear answer.
Are there any alternatives or lightweight libraries available for MicroPython that can run a .tflite model? If not, are there other approaches I can consider for deploying face recognition in MicroPython?
Any advice or suggestions would be greatly appreciated!
Also, I have the possibilte of change the .tflite to an .h5
Imi using an ESP32 PSRAM Timer Camera X from M5
Beta Was this translation helpful? Give feedback.
All reactions