source code at

For this sample code, use branch 11–26–2021-The-Minimum-Vars:

Div class name, component name, import name, export name, … all those confused me when I was studying Vue.JS

Let’s assume we have two source files: A is the calling code, B is the called code.

To use B, A only need to do the following 2 things (red underline):

  • import from B
  • define above import in export…component

Here is what I plan to do:

Next step, let find the code for “Next” button:
The disable = true will cause the “Next” button to enter gray mode.

The idea is that display / undisplay the button based on uploadServer variable: uploadServer will be true if there are images selected, otherwise, uploadServer will be false.

The following this.files is the number of selected files, since it is located into another vue file (vue-upload-drop-images.vue), we have to use $emit to send the value back to the parent component file (datasets-data.vue)

The simplest example with code explanation

Step By Step

Get into the VSC terminal

  • Install VueJS by:
$ npm i -g @vue/cli
  • Create a simple example by vue cli:
$ vue create app1
  • Go to app1 and run it as a web app:
$ cd app1
$ yarn serve

Now we have done.

Next, how do we add our own Vue component?

Let’s understand the code struct of the above example:

No need to input a password when creating an ssh client to an ssh server.


Any machine can become an ssh server by install:

$ sudo apt-get install openssl-server

you can check ssh server running status by:

$ sudo service ssh status

Note: the ssh server will be auto-run after the above installation.

Any machine can be an ssh client.

On the client machine, we will generate a pair of RSA private/public keys by:

$ ssh-keygen -r rsa
$ scp /home/bxiong/.ssh/ bxiong@

On the server machine, add the public key to the authorized file by:

$ mv ~/.ssh/ ~/.ssh/authorized_keys

Thne we should be able to make a ssh connection w/o prompt of inputting password now by:

$ ssh bxiong@

Paul Xiong

Medical AI, computer vision, interest:self-supervised learning+annotation, imbalanced datasets, AI in embedded devices. Personal AI project:

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