MaixPy (v4)

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

MaixPy (v4): Easily create AI projects with Python on edge device

Quick Start | Documentation | API | Hardware

GitHub repo size

English | 中文

MaixCAM

Feature Overview

MaixPy offers simple Python programming combined with powerful edge computing hardware. Integrated hardware peripheral operations, video streaming, AI vision algorithms, and audio algorithms etc. With its plug-and-play design, MaixPy enables you to quickly implement your intelligent projects.

Additionally, MaixPy provides the MaixVision IDE, MaixHub online training platform, detailed documentation, and even a C/C++ SDK with identical APIs, ensuring seamless development and production deployment.

For more features and video demonstrations, please visit the official website: wiki.sipeed.com/maixpy/

If you like this project, please click Star on the top right of the MaixPy Project to encourage us to develop more exciting content!

Concise and Efficient Code (API) Design

With MaixPy you can easily create AI vision project within 10 lines of code:

from maix import camera, display, image, nn

classifier = nn.Classifier(model="/root/models/mobilenetv2.mud")
cam = camera.Camera(classifier.input_width(), classifier.input_height(), classifier.input_format())
disp = display.Display()

while 1:
    img = cam.read()
    res = classifier.classify(img)
    max_idx, max_prob = res[0]
    msg = f"{max_prob:5.2f}: {classifier.labels[max_idx]}"
    img.draw_string(10, 10, msg, image.COLOR_RED)
    disp.show(img)

Result:

Edge(embeded) friendly

Simply use hardware peripheral like serial port:

from maix import uart

devices = uart.list_devices()

serial = uart.UART(devices[0], 115200)
serial.write_str("hello world")
print("received:", serial.read(timeout = 2000))

MaixVision workstation

We also provide a handy MaixVision workstation software to make development easier and faster:

MaixVision

MaixHub online platform

MaixHub provide free online AI train service, one click to train AI model and deploy to MaixCAM even you have no AI knowledge and expensive training equipment.

MaixHub

Hardware platform MaixCAM

And we provide two powerful hardware platform MaixCAM and MaixCAM-Pro, with datasheet register level open.

MaixCAM

CPU	NPU	Memory
- 1GHz RISC-V(Linux) - 700MHz RISCV-V(RTOS) - 25~300MHz 8051(LowPower)	1Tops@INT8 NPU, support BF16 support YOLOv5 YOLOv8 etc.	256MB DDR3

Connecting	Peripheral	MultiMedia	Buy
USB2.0/WiFi6/BLE5.4	IIC/PWM/SPI/UART/WDT/ADC	- 4M Camera - 2.3" 552x368 Touchscreen - H.264/H.265/MJPEG codec	Sipeed Official Store

Who are using MaixPy?

AI Algorithm Engineer who want to deploy your AI model to embedded devices.

MaixPy provide easy-to-use API to access NPU, and docs to help you develop your AI model.

STEM teacher who wants to teach AI and embedded devices to students.

MaixPy provide easy-to-use API, PC tools, online AI train service ... Let you focus on teaching AI, not the hardware and complicated software usage.

Maker who want to make some cool projects but don't want to learn complicated hardware and software.

MaixPy provide Python API, so all you need is learn basic Python syntax, and MaixPy's API is so easy to use, you can make your project even in a few minutes.

Engineer who want to make some projects but want a prototype as soon as possible.

MaixPy is easy to build projects, and provide corresponding C++ SDK, so you can directly use MaixPy to deploy or transfer Python code to C++ in a few minutes.

Students who want to learn AI, embedded development.

We provide many docs and tutorials, and lot of open source code, to help you find learning route, and grow up step by step. From simple Python programming to Vision, AI, Audio, Linux, RTOS etc.

Enterprise who want to develop AI vision products but have no time or engineers to develop complicated embedded system.

Use MaixPy even graphic programming to develop your products with no more employees and time. For example, add a AI QA system to your production line, or add a AI security monitor to your office as your demand.

Contestants who want to win the competition.

MaixPy integrate many functions and easy to use, fasten your work to win the competition in limited time. There are already many contestants win the competition with MaixPy.

Performance comparison

K210 and v831 are outdated, they have many limitations in memory, performance, NPU operators missing etc.
No matter you are using them or new comer, it's recommended to upgrade to MaixCAM and MaixPy v4.

Here's the comparison between them:

Feature	Maix-I K210	Maix-II v831	MaixCAM
CPU	400MHz RISC-V x2	800MHz ARM7	1GHz RISC-V(Linux) 700MHz RISC-V(RTOS) 25~300MHz 8051(Low Power)
Memory	6MB SRAM	64MB DDR2	256MB DDR3
NPU	0.25Tops@INT8 official says 1T but...	0.25Tops@INT8	1Tops@INT8
Encoder	✖	1080p@30fps	2K@30fps
Screen	2.4" 320x240	1.3" 240x240	2.28" 552x368 / 5" 1280x720 / 7" 1280x800 / 10“ 1280x800
TouchScreen	✖	✖	2.3" 552x368
Camera	30W	200W	500W
WiFi	2.4G	2.4G	WiFi6 2.4G/5G
USB	✖	USB2.0	USB2.0
Eth	✖	100M(Optional)	100M(Optional)
SD Interface	SPI	SDIO	SDIO
BLE	✖	✖	BLE5.4
OS	RTOS	Tina Linux	Linux + RTOS
Language	C / C++ / MicroPython	C / C++ / Python3	C / C++ / Python3
Software	MaixPy	MaixPy3	MaixCDK + MaixPy v4 + opencv + numpy + ...
PC software	MaixPy IDE	MaixPy3 IDE	MaixVision Workstation
Docs	⭐️⭐️⭐️⭐️	⭐️⭐️⭐️	🌟🌟🌟🌟🌟
Online AI train	⭐️⭐️⭐️	⭐️⭐️⭐️⭐️	🌟🌟🌟🌟🌟
Official APPs	⭐️⭐️	⭐️⭐️⭐️	🌟🌟🌟🌟🌟
AI classify(224x224)	MobileNetv1 50fps MobileNetv2 ✖ Resnet ✖	MobileNet ✖ Resnet18 20fps Resnet50 ✖	MobileNetv2 130fps Resnet18 62fps Resnet50 28fps
AI detect(NPU forward part)	YOLOv2(224x224) 15fps	YOLOv2(224x224) 15fps	YOLOv5s(224x224) 100fps YOLOv5s(320x256) 70fps YOLOv5s(640x640) 15fps YOLOv8n(640x640) 23fps YOLO11n(224x224)175fps YOLO11n(320x224)120fps YOLO11n(320x320)95fps YOLO11n(640x640)23fps
Ease of use	⭐️⭐️⭐️⭐️	⭐️⭐️⭐️	🌟🌟🌟🌟🌟

Maix Ecosystem

MaixPy not only a Python SDK, but have a whole ecosystem, including hardware, software, tools, docs, even cloud platform etc. See the picture below:

What difference between MaixPy v1, MaixPy3 and MaixPy v4?

MaixPy v1 use MicroPython programming language, only support Sipeed Maix-I K210 series hardware, have limited third-party packages.
MaixPy3 is designed for Sipeed Maix-II-Dock v831, not a long-term support version.
MaixPy v4 use Python programming language, so there's much package we can use directly. MaixPy v4 support new hardware platforms of Sipeed, it's a long-term support version, the future's hardware platforms will support this version. MaixPy v4 have a MaixPy-v1 compatible API, so you can quickly migrate your MaixPy v1 project to MaixPy v4.

(MaixPy v4 Will not support Maix-I K210 series, if you are using Maix-I K210 series, it's recommended to upgrade hardware platform to use this to get more features and better performance.)

Compile Source Code

If you want to compile MaixPy firmware from source code, refer to Build MaixPy source code page.

License

All files in this repository are under the terms of the Apache License 2.0 Sipeed Ltd. except the third-party libraries or have their own license.

Community

Project sharing: maixhub.com/share
App sharing: maixhub.com/app
Discussion: maixhub.com/discussion
QQ group: 862340358
Telegram: t.me/maixpy
Github issues: github.com/sipeed/maixpy/issues

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

The dropdown lists show the available interpreters, ABIs, and platforms. Enable javascript to be able to filter the list of wheel files.

MaixPy-4.10.1-py3-none-any.whl (14.4 MB view details)

Uploaded Jan 14, 2025 Python 3

MaixPy-4.10.1-cp312-cp312-manylinux2014_x86_64.whl (3.8 MB view details)

Uploaded Jan 14, 2025 CPython 3.12

MaixPy-4.10.1-cp311-cp311-manylinux2014_x86_64.whl (3.8 MB view details)

Uploaded Jan 14, 2025 CPython 3.11

MaixPy-4.10.1-cp310-cp310-manylinux2014_x86_64.whl (3.8 MB view details)

Uploaded Jan 14, 2025 CPython 3.10

MaixPy-4.10.1-cp39-cp39-manylinux2014_x86_64.whl (3.8 MB view details)

Uploaded Jan 14, 2025 CPython 3.9

MaixPy-4.10.1-cp38-cp38-manylinux2014_x86_64.whl (3.8 MB view details)

Uploaded Jan 14, 2025 CPython 3.8

File details

Details for the file MaixPy-4.10.1-py3-none-any.whl.

File metadata

Download URL: MaixPy-4.10.1-py3-none-any.whl
Upload date: Jan 14, 2025
Size: 14.4 MB
Tags: Python 3
Uploaded using Trusted Publishing? No
Uploaded via: twine/6.0.1 CPython/3.11.11

File hashes

Hashes for MaixPy-4.10.1-py3-none-any.whl
Algorithm	Hash digest
SHA256	`36f9afc440900c7fcdd416d6c93b530192c2d1ee9892f3a7f892e1729e1456f9`
MD5	`ba4b7d40d1be244ef95553da6f5f0128`
BLAKE2b-256	`387c76d8eaf86d95dbd76c59f0190b7f62e447a73fc456730371501606ca4269`

See more details on using hashes here.

File details

Details for the file MaixPy-4.10.1-cp312-cp312-manylinux2014_x86_64.whl.

File metadata

Download URL: MaixPy-4.10.1-cp312-cp312-manylinux2014_x86_64.whl
Upload date: Jan 14, 2025
Size: 3.8 MB
Tags: CPython 3.12
Uploaded using Trusted Publishing? No
Uploaded via: twine/6.0.1 CPython/3.12.8

File hashes

Hashes for MaixPy-4.10.1-cp312-cp312-manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`a8c18ffe51b4b505b8e1b3bfbe9e6a115259ab0519fbe945e2b3def3533faa79`
MD5	`f0fd43dda09bd56cd10187eb61a41a63`
BLAKE2b-256	`7d186e1d156844055c19760f2217a609ffc558cbf5084adee929e7c84fd0efb3`

See more details on using hashes here.

File details

Details for the file MaixPy-4.10.1-cp311-cp311-manylinux2014_x86_64.whl.

File metadata

Download URL: MaixPy-4.10.1-cp311-cp311-manylinux2014_x86_64.whl
Upload date: Jan 14, 2025
Size: 3.8 MB
Tags: CPython 3.11
Uploaded using Trusted Publishing? No
Uploaded via: twine/6.0.1 CPython/3.11.11

File hashes

Hashes for MaixPy-4.10.1-cp311-cp311-manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`29b667e0b2c1c537fe8c38cccf74e43aefbe4038f7bf086a2b174d8105feb8b1`
MD5	`14009fba6e0b02b7eb61e4020396b77d`
BLAKE2b-256	`284d36b05851b57a360bf3a4902b5d80c46846e31b5fd1b309296d70d4f72d64`

See more details on using hashes here.

File details

Details for the file MaixPy-4.10.1-cp310-cp310-manylinux2014_x86_64.whl.

File metadata

Download URL: MaixPy-4.10.1-cp310-cp310-manylinux2014_x86_64.whl
Upload date: Jan 14, 2025
Size: 3.8 MB
Tags: CPython 3.10
Uploaded using Trusted Publishing? No
Uploaded via: twine/6.0.1 CPython/3.10.16

File hashes

Hashes for MaixPy-4.10.1-cp310-cp310-manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`0f2debfd262decf469cc8bd9aba202ba126ad4baf76d9cfb5add4efeedb8ba89`
MD5	`588a53169a749c997003b01098a40da6`
BLAKE2b-256	`08717ec9b60bc3df0625d48eefeabd334a49d88cd0f2cdfcc4cb593466da7e1a`

See more details on using hashes here.

File details

Details for the file MaixPy-4.10.1-cp39-cp39-manylinux2014_x86_64.whl.

File metadata

Download URL: MaixPy-4.10.1-cp39-cp39-manylinux2014_x86_64.whl
Upload date: Jan 14, 2025
Size: 3.8 MB
Tags: CPython 3.9
Uploaded using Trusted Publishing? No
Uploaded via: twine/6.0.1 CPython/3.9.21

File hashes

Hashes for MaixPy-4.10.1-cp39-cp39-manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`ec4fe3c8913b1ad205009bf2b83f6dc8673a1adb73e085037e30249f6b6e58b4`
MD5	`1cb4ff9f60b787992cbdc94f8a1fa2a2`
BLAKE2b-256	`0138cf62e9dd8b697e5c596df8ba8e9b75149cd807f145cebf0535e530d95350`

See more details on using hashes here.

File details

Details for the file MaixPy-4.10.1-cp38-cp38-manylinux2014_x86_64.whl.

File metadata

Download URL: MaixPy-4.10.1-cp38-cp38-manylinux2014_x86_64.whl
Upload date: Jan 14, 2025
Size: 3.8 MB
Tags: CPython 3.8
Uploaded using Trusted Publishing? No
Uploaded via: twine/6.0.1 CPython/3.8.18

File hashes

Hashes for MaixPy-4.10.1-cp38-cp38-manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`84a4d00cdf01d4c20b4a689365c1cc99c076143ab92dcd80688667c8cb7d3363`
MD5	`c9e87874fa88ac3a7554d765d1d29dae`
BLAKE2b-256	`d658245ddda5ceedb8af96b5953824165275892a6e59a0e6554db909d3454302`