Other

项目介绍

sipeed/MaixPy-v1 是一个托管在 GitHub 上的开源项目,主要使用 Python 编写,采用 Other 许可证,目前获得 1.7k 个 Star、453 次 Fork。

仓库全名
sipeed/MaixPy-v1
开源许可证
Other
Star 数
1.7k
Fork 数
453
未关闭 Issue
145

README 摘要

中文 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…

完整内容见 GitHub 原始 README 或本页 。

常见问题

MaixPy-v1 用什么语言开发?

主要使用 Python 编写,采用 Other 许可证,目前有 1.7k 个 Star。

MaixPy-v1 可以免费商用吗?

仓库标注的许可证为 Other,商用前请先阅读仓库 LICENSE 文件确认授权范围。

如何获取 MaixPy-v1 的源码?

可以直接克隆仓库:git clone https://github.com/sipeed/MaixPy-v1.git,默认分支为 master;安装与运行步骤见仓库 README。

MaixPy-v1 最近还在维护吗?

仓库最近一次更新为 2024年6月17日,当前有 145 个未关闭 Issue;Star 数为 1.7k,可作为社区活跃度的参考。

简要分析

热度分
2706
价值分
1162
活跃状态
活跃

语言占比

Assembly
C
C++
CMake
Dockerfile
Makefile
Python
Shell

Release

README




Master branch build status master build firmware Latest release version License
Good first issues Bug issues Enhancement issues

中文



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.
maix bit

Simple code

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

Release

See Releases page

Get latest commit firmware: master firmware

Custom your firmware, see build or use online custom tool

Documentation

Doc refer to maixpy.sipeed.com

Examples

MaixPy_scripts

Build From Source

See build doc

The historic version see historic branch (No longer maintained, just keep commit history)

Use online compilation tools to customize firmware

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

Model hub: Maixhub.com

Find more models on Maixhub.com

License

See LICENSE file

Other: As C SDK for C developers

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

评论

暂无评论