
This SDK has been patched by Embedded Artists for the iMXRT1064 Developer's Kit.
The SDK was released on 2021-12-01 and is based on NXP's 2.10.0 SDK (SDK_2_10_0_MIMXRT1064xxxxA.zip).

This is what has been patched:
* Set CPU speed according to Commercial/Industrial CPU
* Correction of the VDD_SOC_IN voltage.
* LWIP projects - added reading of the MAC address from the onboard I2C EEPROM
* Wi-Fi and Bluetooth projects
* Added an I2C driver for the gpio expander (PCA6416) and code to use it
* Added an I2C driver for the PWM gpio expander (PCA9530) and code to use it
* Modified pin muxing
* SEMC projects - changed algorithm for memory test and now test entire 32MB instead of only 4KB
* Examples using a disaplay have been updated to use PCA6416/PCA9530 for
  RST/PWR/BL signals
* BOARD_USER_BUTTON has been redirected to SW5/WAKEUP button on the uCOM Carrier Board
* USER_LED has been changed to the blue RGB LED using PCA6416
* Adjusted the USB interface number (it is different for host and device examples)
* Added support for Embedded Artists 2DS M.2 Module (EAR00386) in the NXP Wi-Fi examples
* Added support for Embedded Artists 1ZM M.2 Module (EAR00364) in the NXP Wi-Fi examples
* Added support for Embedded Artists 1XK M.2 Module (EAR00385) in the NXP Wi-Fi examples
* Changed reset pin for SD card examples

This has been added:
* LWIP projects - option to use 100/10Mbps Ethernet-PHY Adapter
* AWS projects - option to use 100/10Mbps Ethernet-PHY Adapter
* AzureRTOS projects - option to use 100/10Mbps Ethernet-PHY Adapter
* I2C probe example
* Wi-Fi (serial) examples for the CMWC1ZZABR-107-EVB (a.k.a ABR Module)

This has been removed:
* All projects for the expansion board AGM01

Important things to note:
* Read section "8 - Known Issues" in docs/MCUXpresso SDK Release Notes for EVK-MIMXRT1064.pdf
  to see known issues with the current version of the SDK.
* For Iperf examples, set compiler optimization to -O3 or similar to improve performance.
* If the hardware seems unresponsive and the debugger cannot connect/flash/erase the current program
  then the most likely cause is the running program preventing the access. To stop the currently
  running program and regain control:
  1) Press and hold down the ISP_ENABLE button (SW1)
  2) Press and hold down the RESET button (SW3)
  3) Let go of the RESET button
  4) Wait an extra second or two
  5) Release the ISP_ENABLE button
  6) The hardware is now in a mode where programming/erasing it should work



Connectors:
* J29 (micro USB) is the default UART and unless specified otherwise it is setup for 115200 8/N/1


!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
THIS PROJECT IS NOT DIRECTLY COMPATIBLE WITH THE HARDWARE AND WILL NOT WORK.

The CSI interface needed for camera support is not available on the iMXRT1064 uCOM connector
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!



Everything below this line is the original content of the readme file.
=======================================================================



Overview
========
Demonstrates inference for models compiled using the GLOW AOT tool and uses
a camera to generate data for inferencing.

This example project provides an inference example using the Lenet model
compiled with the Glow AOT software tools. The model is capable to perform
hand-written digit classification. The model is using 28 x 28 grayscale
input images and provides the confidence scores for the 10 output classes:
digits "0" to "9". The application will run the inference on data captured by 
a connected camera and display the top1 classification results and the inference time. 
The Glow bundle is the same as the "glow_lenet_mnist" MCUXpresso SDK example in the RT1060 SDK.

A PDF with example numbers for the camera to look at is included in the /doc folder.

 If you want a step-by-step example of running the Glow AOT tool for a given model 
 take a look at the LeNet MNIST Glow MCUXpresso SDK example and the Glow Getting Started Lab:
 https://community.nxp.com/t5/eIQ-Machine-Learning-Software/eIQ-Glow-Lab-for-i-MX-RT/ta-p/1123119


Toolchains supported
====================
- MCUXpresso IDE
- IAR Embedded Workbench for ARM
- Keil uVision MDK
- ArmGCC - GNU Tools ARM Embedded


Running the demo
================
Use the LCD screen to point the camera at handwritten digits. Some images will work better than others, and a few example
digits have been provided in the PDF in the /doc folder. Thicker font works better than thin font and the demo expects 
black ink/marker on a white background.  For best results, the selection rectangle should be centered on the image 
and nearly (but not completely) fill up the whole rectangle. The camera should be stabilized with your finger or by some other means to prevent 
shaking. Also ensure the camera lens has been focused as described in the instructions when connecting the camera and LCD 
(https://community.nxp.com/t5/i-MX-RT-Knowledge-Base/Connecting-camera-and-LCD-to-i-MX-RT-EVKs/tac-p/1122184). 

You will see the result of the inference on the LCD screen as well as the serial terminal. The result printed
on the LCD screen has a minimum threshold applied to it. 
  Top1 class = 4 (4)
  Confidence = 0.999
  Inference time = 10 (ms)

Your own handwritten digits can also be used. It's recommended to use a thick black marker with white paper for best results. 
