Uploaded August 2024 | Updated September 2026, 2 weeks ago
I started this project with high expectations but I failed. Please use this as a reference and I hope your project will be successful.
*When connecting the drone via WiFi from the mobile, the password is 12345678
[ESP-Drone]
docs.espressif.com/projects/espressif-esp-drone/en/latest/index.html
[ESP-Drone Sensor Calibration]
docs.espressif.com/projects/espressif-esp-drone/en/latest/system.html#sensor-calibration
#ESP32 #Drone #Crazyflie
I started this project with high expectations but I failed. Please use this as a reference and I hope your project will be successful.
*When connecting the drone via WiFi from the mobile, the password is 12345678
[ESP-Drone]
docs.espressif.com/projects/espressif-esp-drone/en/latest/index.html
[ESP-Drone Sensor Calibration]
docs.espressif.com/projects/espressif-esp-drone/en/latest/system.html#sensor-calibration
#ESP32 #Drone #Crazyflie
![[AMB82-Mini IoT AI Camera] *On-Device* object detector powered by Tiny Yolo v7! #standalone](https://i.ytimg.com/vi/TGqOUVhQQY8/mqdefault.jpg "[AMB82-Mini IoT AI Camera] *On-Device* object detector powered by Tiny Yolo v7! #standalone
Tiny YOLO version 7 is a simplified version of YOLO version 7, which has a much smaller number of convolution layers than YOLO version 7, which means that Tiny YOLO version 7 does not need to have a large amount of memory and hardware performance but lose some of the detection accuracy.
Lets make one thing clear.
The object detector we are trying to build in a low-power MCU environment is a very simple one. For example, it triggers an action when it detects a person, or acts as a kind of switch to take a certain action. For better performance, it is recommended to run the latest full version of YOLO on a device such as Nano Jetson.
[AMB82-Mini Camera module]
https://amzn.to/4bYOuNk
[Project GitHub]
https://github.com/0015/AMB82-Mini-Board")
