Skip to main content

An automation black-box testing framework based on image recognition

Project description

LOGO

MaaFramework

✨ 基于图像识别的自动化黑盒测试框架 ✨

license C++ platform commit stars

简介

MaaFramework 是基于图像识别技术、运用 MAA 开发经验去芜存菁、完全重写的新一代自动化黑盒测试框架。

低代码的同时仍拥有高扩展性,旨在打造一款丰富、领先、且实用的开源库,助力开发者轻松编写出更好的黑盒测试程序,并推广普及。

即刻开始

最佳实践

  • M9A 1999 小助手 Pipeline
    基于全新架构的 亿韭韭韭 小助手。图像技术 + 模拟控制,解放双手!由 MaaFramework 强力驱动!

  • MAABH3 《崩坏3》小助手 | A one-click tool for the daily tasks of Honkai Impact. cpp
    基于全新架构的 蹦蹦蹦 小助手。图像技术 + 模拟控制,解放双手!由 MaaFramework 强力驱动!

  • MAALimbusCompany 边狱公司 小助手 Pipeline
    基于全新架构的 边狱公司 小助手。图像技术 + 模拟控制,解放双手!由 MaaFramework 强力驱动!

  • MBA BA 小助手 csharp
    基于 MAA 全新架构的 BA 小助手。图像技术 + 模拟控制,解放双手,不再点点点!由 MaaFramework 强力驱动!

  • MAS 森空岛 小助手 Pipeline
    基于全新架构的 森空岛 小助手。图像技术 + 模拟控制,解放双手!由 MaaFramework 强力驱动!

  • MRA 雷索纳斯 列车长 小助手 Rust Tauri
    基于全新架构的 列车长 小助手。图像技术 + 模拟控制,解放双手!由 MaaFramework 强力驱动!

  • MaaHatsuboshiTA 学院偶像大师 初星助教 Pipeline
    基于全新架构的制作人代肝工具,养肝护眼 + 节省时间,出轨美铃! 由 MaaFramework 强力驱动!

  • MCCA 交错战线 小助手 Pipeline
    基于全新架构的 交错战线 小助手。图像技术 + 模拟控制,解放双手!由 MaaFramework 强力驱动!

  • MSBA 分析员 小助手 Pipeline
    基于全新架构的 尘白禁区 小助手。图像技术 + 模拟控制,解放双手!由 MaaFramework 强力驱动!

  • MaaAeonFantasy 星神少女 预言之子 小助手 Pipeline
    基于全新架构的 星神少女 小助手。图像技术 + 模拟控制,让手去做它该做的事!由 MaaFramework 强力驱动!

  • maa-whmx 物华弥新 小助手 cpp qt
    基于全新架构的 物华弥新 小助手。图像技术 + 模拟控制,解放双手!由 MaaFramework 强力驱动!

  • MAA-for-Millennium-Tour 千年之旅 小助手 Pipeline python
    基于全新架构的 千年之旅 小助手。图像技术 + 模拟控制,解放侍主的大手!由 MaaFramework 强力驱动!

  • MFAWPF MFA 任务管理器 csharp
    基于 MAA 全新架构的 通用 GUI。由 MaaFramework 强力驱动!

  • MET 悠久之树 小助手 Pipeline
    基于全新架构的 悠久之树 小助手。图像技术 + 模拟控制,解放双手!由 MaaFramework 强力驱动!

生态共建

MAA 正计划建设为一类项目,而非舟的单一软件。

若您的项目依赖于 MaaFramework ,我们欢迎您将它命名为 MaaXXX, MXA, MAX 等等。当然,这是许可而不是限制,您也可以自由选择其他与 MAA 无关的名字,完全取决于您自己的想法!

同时,我们也非常欢迎您提出 PR ,在上方的最佳实践列表中添加上您的项目!

许可证

MaaFramework 采用 LGPL-3.0 许可证进行开源。

开发

请留意,仅当您准备开发 MaaFramework 本身时,才需要阅读本章节内容。若您仅希望基于 MaaFramework 开发自己的应用,则请参考 即刻开始

鸣谢

开源库

  • opencv
    Open Source Computer Vision Library
  • fastdeploy
    ⚡️An Easy-to-use and Fast Deep Learning Model Deployment Toolkit for ☁️Cloud 📱Mobile and 📹Edge. Including Image, Video, Text and Audio 20+ main stream scenarios and 150+ SOTA models with end-to-end optimization, multi-platform and multi-framework support.
  • onnxruntime
    ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
  • boost
    Boost provides free peer-reviewed portable C++ source libraries.
  • meojson
    A modern all-platform Json/Json5 parser/serializer, which is header-only and used magic!
  • minitouch
    Minimal multitouch event producer for Android.
  • maatouch
    Android native implementation of minitouch input protocol
  • minicap
    Stream real-time screen capture data out of Android devices.
  • zlib
    A massively spiffy yet delicately unobtrusive compression library.
  • gzip-hpp
    Gzip header-only C++ library
  • protobuf
    Protocol Buffers - Google's data interchange format
  • grpc
    The C based gRPC (C++, Python, Ruby, Objective-C, PHP, C#)
  • thrift
    Apache Thrift

开发者

感谢以下开发者对 MaaFramework 作出的贡献:

讨论

  • 集成/开发交流 QQ 群: 595990173

赞助

Project details


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

MaaFw-2.1.0b1-py3-none-win_arm64.whl (22.6 MB view details)

Uploaded Python 3 Windows ARM64

MaaFw-2.1.0b1-py3-none-win_amd64.whl (24.2 MB view details)

Uploaded Python 3 Windows x86-64

MaaFw-2.1.0b1-py3-none-manylinux2014_x86_64.whl (19.9 MB view details)

Uploaded Python 3

MaaFw-2.1.0b1-py3-none-macosx_13_0_x86_64.whl (16.6 MB view details)

Uploaded Python 3 macOS 13.0+ x86-64

MaaFw-2.1.0b1-py3-none-macosx_13_0_arm64.whl (13.8 MB view details)

Uploaded Python 3 macOS 13.0+ ARM64

File details

Details for the file MaaFw-2.1.0b1-py3-none-win_arm64.whl.

File metadata

  • Download URL: MaaFw-2.1.0b1-py3-none-win_arm64.whl
  • Upload date:
  • Size: 22.6 MB
  • Tags: Python 3, Windows ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.12

File hashes

Hashes for MaaFw-2.1.0b1-py3-none-win_arm64.whl
Algorithm Hash digest
SHA256 51eb3ebb4e58d04cc1caa0dfe4a116214554577e7f2c04dcdb2752a43ad7c57e
MD5 32b0c5f59fee5dfc66b53bce781de3c7
BLAKE2b-256 93ead99960bbc4904189d5d03a61e23290db3d9696ba830d9bcca9ce5b1ff795

See more details on using hashes here.

File details

Details for the file MaaFw-2.1.0b1-py3-none-win_amd64.whl.

File metadata

  • Download URL: MaaFw-2.1.0b1-py3-none-win_amd64.whl
  • Upload date:
  • Size: 24.2 MB
  • Tags: Python 3, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.12

File hashes

Hashes for MaaFw-2.1.0b1-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 91a807ece3527639d1ba84ed77577bd691fece50b375453ea8a57b208890b71a
MD5 758e712662c5007bb17b7ba5cfb2f693
BLAKE2b-256 4b376f0a474555c0afa7e8a962e16abc7414aa0c7f69e4f206ef66decd81c534

See more details on using hashes here.

File details

Details for the file MaaFw-2.1.0b1-py3-none-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for MaaFw-2.1.0b1-py3-none-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 596ca188f8f43b261198a6da1a357ee200d0b56bc48ff1eaddf3879d55e1359d
MD5 51fb1d180a033de06383966a68de2924
BLAKE2b-256 73b4c4c6b04b088f26e1414cdc84c046db0ada389f5b4e677f79eee3f74c5bea

See more details on using hashes here.

File details

Details for the file MaaFw-2.1.0b1-py3-none-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for MaaFw-2.1.0b1-py3-none-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 7250e3639353e9cb44a55be3e4b612ffce0f6ee7c4864c8c6dc8faad10077a64
MD5 c290593c465476ab0d8032fc8618eff4
BLAKE2b-256 2adc23b8275b9a7d099f029d6baa3a4e2ef7949af502a7df50fea725bb8e7e3e

See more details on using hashes here.

File details

Details for the file MaaFw-2.1.0b1-py3-none-macosx_13_0_x86_64.whl.

File metadata

File hashes

Hashes for MaaFw-2.1.0b1-py3-none-macosx_13_0_x86_64.whl
Algorithm Hash digest
SHA256 890e8ae6213c1e21e449848c52db6dbe0d9459d1bac6af5b6d45f3140130f50a
MD5 4629ad4848ef35cf0da283aa1d063b3e
BLAKE2b-256 e6879f4aad87d5ea8ee241266f99d85cf3ab03612ea82b8666ebdee96cce4fdb

See more details on using hashes here.

File details

Details for the file MaaFw-2.1.0b1-py3-none-macosx_13_0_arm64.whl.

File metadata

File hashes

Hashes for MaaFw-2.1.0b1-py3-none-macosx_13_0_arm64.whl
Algorithm Hash digest
SHA256 3e89df03d423f12270210a63c517e059fbf5ffd87efbeadceb553240731ff705
MD5 5608f54bdf4295138219db9fd285335b
BLAKE2b-256 0d27ed4677d719397e69520291c7b19b646f35a128ef98ffd8e90ff4be8820e0

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page