Use these saved recognitions to control devices connected to the ESP32īefore following this tutorial make sure your camera works by following this tutorial Ai-Thinker ESP32-CAM in the Arduino IDE Persistent Storage Partition SchemeĪ new partition scheme with persistent storage on the on-board flash is needed.Modify the CameraWebServer example sketch to save face data to the new partition.Create a new partition scheme to enable persistent storage.This tutorial will explain how to save enrolled images in the on-board flash so they survive the ESP32 powering off and use these saved recognitions to control devices connected to the ESP32. We will use a state machine approach as in JeVois + Arduino: blink for X, just now it has a few more states because we have a total of 6 tokens to decode for each message.įor the sake of developing a non-trivial example, let's say we want to turn on the LED of the Arduino when we detect a dog at least 200 units wide (i.e., the bounding box around the dog should be at least as wide as 1/10th of the field of view, and the full field of view is 2000 standardized units wide as explained above).Using face recognition to open a door or control other home automation devices ![]() For the code below, we will assume floating point values which could be integers as well. If you change that using the parameter serprec described in Standardized serial messages formatting, you can get more precise floating-point values (e.g., try setpar serprec 3 in the Console of JeVois Inventor).
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