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Let's Sipeed up, Maximize AI's power!

MaixPy, makes AIOT easier!

Maixpy is designed to make AIOT programming easier, based on the Micropython syntax, running on a very powerful embedded AIOT chip K210.

There are many things you can do with MaixPy, please refer to here

K210 brief:

• Image Recognition with hardware AI acceleration
• Dual core with FPU
• 8MB(6MB+2MB) RAM
• 16MB external Flash
• Max 800MHz CPU freq (see the dev board in detail, usually 400MHz)
• Microphone array(8 mics)
• Hardware AES SHA256
• FPIOA (Periphrals can map to any pins)
• Peripherals: I2C, SPI, I2S, WDT, TIMER, RTC, UART, GPIO etc.

Find I2C devices:

from machine import I2C

i2c = I2C(I2C.I2C0, freq=100000, scl=28, sda=29)
devices = i2c.scan()
print(devices)

Take picture:

import sensor
import image
import lcd

lcd.init()
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.run(1)
while True:
    img=sensor.snapshot()
    lcd.display(img)

Use AI model to recognize object:

import KPU as kpu
import sensor

sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_windowing((224, 224))

model = kpu.load("/sd/mobilenet.kmodel")  # load model
while(True):
    img = sensor.snapshot()               # take picture by camera
    out = kpu.forward(task, img)[:]       # inference, get one-hot output
    print(max(out))                       # print max probability object ID

please read doc before run it

See Releases page

Get latest commit firmware: master firmware

Custom your firmware, see build or use online custom tool

Doc refer to maixpy.sipeed.com

MaixPy_scripts

See build doc

The historic version see historic branch (No longer maintained, just keep commit history)

Go to maixhub.com to use online compilation to customize the functions you need

Find more models on Maixhub.com

See LICENSE file

In addition to the source code of the MaixPy project, since MaixPy exists as a component, it can be configured to not participate in compilation, so this repository can also be developed as C SDK. For the usage details, see Building Documentation, which can be started by compiling and downloading projects/hello_world.

The compilation process is briefly as follows:

wget http://dl.cdn.sipeed.com/kendryte-toolchain-ubuntu-amd64-8.2.0-20190409.tar.xz
sudo tar -Jxvf kendryte-toolchain-ubuntu-amd64-8.2.0-20190409.tar.xz -C /opt
cd projects/hello_world
python3 project.py menuconfig
python3 project.py build
python3 project.py flash -B dan -b 1500000 -p /dev/ttyUSB0 -t