runwayml_micropython_m5stack

using http requests with m5stack to communicate with

example using http get with RunwayML classification models

this example uses the big gan classification model to identify items and stream the text descriptions to the screen of the M5Stack using http get and json. the M5Stack responds by graphically representing the identified object as well as changing the color of the leds to a color matching the identified object. this example can be customized to use the identification value from RunwayML to trigger and control various hardwares such as motors, LEDs, and sound on the M5Stack. RunwayML is fantastic since it is made to network. this makes it easy to communicate and experiment with ML. the M5Stack makes IOT and ML and great match.

example using http post with RunwayML to explore latent space

this example sends vectors to RunwayML and allows you to interact and select different categories from which to draw