Petoi AI Vision Module is based on the Arm Cortex-M55, and Ethos-U55 embedded vision module. The Ethos-U55 has 64 to 512 GOP/s of arithmetic power to meet the growing demand for downloading machine learning.
Hardware setup
BiBoard V0
Bittle X
BiBoard V1
Bittle X
Bittle X+Arm
Fix the end connected to the camera to the robot's head (included in Bittle's / Bittle X's mouth or attached to Bittle X+Arm's robotic arm).
If you use the version of Petoi Desktop App <= V1.2.5, you need to connect the Petoi AI vision module to the following Grove socket:
Please select the correct Product type, Board version, and Serial port according to your actual use.
The mode should be Standard, so press the Upgrade the Firmware button.
For example, Bittle, BiBoard_V0_2, COM5 as follows:
Create a mobile app command called "Deactivate camera" and use the code: X99
Web debug GUI
Combined with the empowerment of the web debug GUI (SenseCraft AI Model Assistant), you can easily upload a wide variety of co-created models and directly observe the results.
The camera is already plugged in. After opening the web debug GUI, simply connect Petoi AI Vision to your computer using a Type-C cable and then click the Connect button.
For how to use this web debug GUI, please refer to:
If the camera mode can't be activated, as follows:
You can use the web debug GUI to upgrade the camera firmware and upload the Face Detection model.
To run the example code (inference.ino) in the library Seeed_Arduino_SSCMA, you should add the library to your Arduino IDE by selecting Sketch > Include Library > Add .ZIP Library and choosing the downloaded file.
Or you can install the library in the Library Manager of the Arduino IDE as follows:
More Application
The Petoi AI vision module also supports taking photos and transmitting images via Wi-Fi, but it needs to be installed on a MCU with more powerful computing power (such as ESP32S3, ESP32C3, etc.). For the specific development process, please refer to the wiki technical documentation:
