thank for qidiso provide the 中文说明

AidLearning FrameWork is a Linux system with GUI running on Android phone for AI programming without needing root. Aidlearning is also a Python programming framwork for mobile devices. In addition to some of the features available in the Linux environment, AidLearning has supported GUI and neural network environments. For example, Caffe, Tensorflow, Mxnet,Gluoncv, ncnn, Keras,Pytorch are perfectly supported..

AidLearning is a Linux system running on the Android with GUI, AI and Python support . The AidLearning project which have the Linux+Anroid+AI 3IN1 environments Developed and Maintained by several students from Cas University and Yale University.

Furthermore we provide an AI coding develop tool named Aid_code. It can provide you a visual AI programming IDE by using Python from zero on our framework! It means that when it is installed, your Android phone owned a Linux system with GUI which can write and run AI program in it as same as in PC.

Now you have a complete linux with GUI running on Android (Real linux running on the busybox and not virtul environment. So it is faster and almost real-time.) and can write your AI code on it visually using the Python!

New Release : AidLearning 0.70
What's new:

• Full support for Python 3 and python 2, as well as pip3 and pip2 install
  

• Caffe/MXNET/Gluoncv/Tensorflow/ Keras/Pytorch/Opencv4 for Python3 and Python2 are perfectly supported
  

• With the new CVS package, you can easily customize your interface with Python code:

  cvs. setTitle ("Face Recognize")
  cvs. setInput_dict (usr_dict)
  cvs. setSubmitName ("Register your FaceID")
  cvs. setCamX (350,480)
  cvs. setInfoX (320,60)
  

• Now You can use apt (apt-get) to install new packages to improve your Linux Environment...
  

• Some BUGs have been solved, such as:
  Press the home key to return home and then enter the app: Instead of returning to the GUI, the problem is returning to the terminal.
  Reducing dependence on network traffic.
  

• Adding new buttons for running Python 3 and python 2 online for Aid_code IDE
  

• Add the AI Example Center, put some examples on the website, the new examples can be downloaded from the website in the future, in order to prevent the distribution of installation packages too large.
  

• Modified accounts that do not activate the mailbox can be logged in directly, but there are prompts to activate the interface after login...
  
  

The app （apk） is only 8M，when you install the apk ,the apk will download the depdence of the framework is 700M and 350M examples of AI codes using python. all is about 1G size to download .So it's recommended that you install it in a WiFi environment.

• [Caffe]https://github.com/BVLC/caffe
• [Tensorflow]https://github.com/tensorflow/tensorflow
• [Mxnet]https://github.com/apache/incubator-mxnet
• [Keras]https://github.com/keras-team/keras
• [ncnn]https://github.com/Tencent/ncnn
• [pytorch]https://github.com/pytorch/pytorch
• [opencv]https://github.com/opencv/opencv

As shown in the figure above, we divide an app into four areas: Title area, camera area, input area, info show area. An app display can consist of one or more areas.You can use Python (cvs class) statements to manipulate the Title, size and layout of these areas. for examples： in the info area ,you can do this:
cvs. setInfoX (320,60) # setting the width,height of the info area
cvs. infoshow ("this is info show") # show info in the info area

>>> Tutorial & Guide

PC can connect to mobile by using **ssh-keygen**. Generate a new key pair with ssh-keygen command in your PC. the command ssh-keygen produce the file of id_rsa and id_rsa.pub in the dir: ~/.ssh/

Just need you do: open the url:mobilephone'sip:8910/upload(for example:http://192.168.1.6:8910/upload) in the pc to upload ssh's file(id_rsa and id_rsa.pub).

We fixed Graphical User Interface for the Linux on Andorid(It has been pruned by andorid!), so you can use the GUI just like on the pc. For instance, You can use opencv to open and view camera!

Real linux running on the busybox and not virtul environment like VirtulBox. So it is faster and almost real-time

We provide a plenty of examples and by using our framework, you can run it with a tap, and then get a visual log to show the informations or errors.

You can coding on your phone anywhere, anytime. Every inch of fragmentation have been fully utilized. Your creativity can be instantly realized with a flash of inspiration.

According to the test on the mainstream smartphone like Samsung, Aid Learning Framework only use 1% power consumption in a whole day (Standby)

[Watch the video](https://youtu.be/bkvNXgCi3_c)

Facencnn(mobiefacenet ncnn) 15fps in mobile phone

Face Landmark (106 keypoints ncnn) 15fps in mobile phone

handpose (tensorflow ) 5fps in mobile phone

body posenet for single person(converted from google ) 10fps in mobile phone

body posenet for multi-person(converted from google ) 7fps in mobile phone

Stylized picture(GAN ) 3fps in mobile phone .....

We give special thanks to qidiso for his incredible and excellent work in translating AidLearning's documentation to the Chinese language. Find below the contact details of those who have contributed immensely to the AidLearning project.

Email: [email protected]
Website: http://www.aidlearning.net

Medium-- Stories about AidLearning

• VTE (libvte): Terminal emulator widget for GTK+, mainly used in gnome-terminal. Source, Open Issues, and All (including closed) issues.
• iTerm 2: OS X terminal application. Source, Issues and Documentation (which includes iTerm2 proprietary escape codes).
• Konsole: KDE terminal application. Source, in particular tests, Bugs and Wishes.
• hterm: JavaScript terminal implementation from Chromium. Source, including tests, and Google group.
• xterm: The grandfather of terminal emulators. Source.
• Connectbot: Android SSH client. Source
• Android Terminal Emulator: Android terminal app which Termux terminal handling is based on. Inactive. Source.
• Termux: Android terminal and Linux environment - app repository. Source.
• remi:Python REMote Interface library. Platform independent. In about 100 Kbytes, perfect for your diet.[Source] (https://github.com/dddomodossola/remi).
• [Caffe]https://github.com/BVLC/caffe
• [Tensorflow]https://github.com/tensorflow/tensorflow
• [Mxnet]https://github.com/apache/incubator-mxnet
• [Keras]https://github.com/keras-team/keras
• [ncnn]https://github.com/Tencent/ncnn
• [pytorch]https://github.com/pytorch/pytorch
• [opencv]https://github.com/opencv/opencv