Split Videos For WhatsApp Status Or Instagram On Android

In this article, we will take a look at how to split videos for WhatsApp status or Instagram stories. Since you all know that we can upload status videos on WhatsApp, we need these tools to split or trim the videos.

But wait a second,why we do we need to do that? Well, let me explain to you as to why there is a need to do that.

Why To Split Videos For WhatsApp Status?

So here is the thing. We want to upload our videos as WhatsApp status right? But the problem here is that WhatsApp does not allow videos to be longer than 30 sec in length. So what is the solution then? Well in that case, any video longer than that needs to be split or trimmed down!

But how do we go about doing that? That is what we will explain to you in our next section!

How To Split Video For WhatsApp Status?

So in the earlier sections we understood why we need to split our videos for WhatsApp status, right? In this section we will see different ways we can do that. So are you ready for that? Cool! Then let us get started right away!

Method 1: Using WhatsApp Video Trim Feature

So the first way to split video is to use the WhatsApp’s built-in video trimming feature.

Wait what? So WhatsApp has a feature to split videos? Yes, it does so! WhatsApp has a feature to trim videos to upload it as WhatsApp status.

WhatsApp Video Editor
WhatsApp Video Editor

So how do we do that? Here are the steps you need to follow to do that.

How To Split Video Using WhatsApp Video Trim Feature

  1. Click On My Status Option

    Open your WhatsApp app, click on the status button and click on the “My Status” option in it.WhatsApp Status Button

  2. Select Your Video

    Now you need to select the video from the gallery. This is the video you want to trim and upload as your status video.

  3. Split The Video

    Using the slider provided, select a 30 second window in the video. So this will be the part of the video that gets trimmed down and ready to be uploaded as your WhatsApp status video. You can move the slider on either sides to select the beginning and ending part of the video.Video Split For WhatsApp Status

  4. Upload The Video As You WhatsApp Status

    So now that you have your trimmed 30 sec WhatsApp status video ready, it is time to upload it. You can do that by clicking on the Send button.

Method 2: Split Videos Using Video Editor Apps

So in the second method, we will use 3rd party video editor apps to split our videos. But before we discuss this method, there is one question we need to ask ourselves.

Why are we going for a 3rd party video editor app when we already have video editing support in WhatsApp itself?

Any guess? Think about it a bit before moving down to find the reason behind it.

Alright, is any guess? Let me tell you the reason behind it.

Well you see, the video editing feature by WhatsApp is all well and good if you have a single video to edit. However, what if you want to use multiple videos and edit them to make a 30 sec status video?

You guessed it right. You just cant do that with WhatsApp Video Editor. So to work aroud that, we will make use of 3rd party video editor apps.

So the idea behind this is to install a good 3rd party video editor app onto your smartphone. You can then use this editor to add multiple videos, combine them and trim them down to 30 sec videos.

Once you are done with it, you can then upload them as your WhatsApp status video. It makes sense right? Great!

So what then are some of the best video editor apps for Android out there?

Well, there are many good video editors that are both free and paid apps. So which one you should use really depends on how much you are willing to spend. So it completely depends upon you.

But in any case we find these video editors to be good for splitting videos for WhatsApp.

Few Video Editor Apps On Android For WhatsApp Status Video

  • WhatCut Pro App
  • Adobe Premiere Clip
  • Power Director
  • Viva Video
  • Funimate etc

So as you can see, there a are a bunch of video editor apps available for Android. You can use either of these apps to create your 30 second WhatsApp status video.

Now since each one of these apps work differently, I wont be explaining to you how to work with each of them. I will let you download and explore them by yourselves on that.

But if you found some other app that are good for this, do let me know in the comments below and I will add them to the list above.

Method 3: Using Online Video Editor To split Videos For For WhatsApp Status

The third and final option we recommend you to use are the online video editors available on the internet. Now there are a plethora of web apps that you can use to edit your videos online. But they come with their own set of problems.

What are they, you ask?

Disadvantages of Online Video Editors

Well for one, you need to have good internet connection to use them. Why is that?

That is because you will be required to upload your videos to the online video editor’s servers. So, if your video file size is too big, your internet speed better be good for quick upload. Or else you will end up waiting forever uploading the video files.

Advantages of Online Video Editors

But on the other hand, this will be a good option to go for editing your videos for WhatsApp if your smartphone is running low on battery. Why is that?

It is because all the video processing will take place in the web app’s server side. So your smartphone will not be doing much work other than uploading the video and downloading edited video. Since that real editing happens on the web server, your smartphone’s battery power will not be used.

There is one more advantage to using online video editors. Since most of the video editing happens on the web server that are more powerful than your smartphones, you will have good editing options. Why so?

Well, as you know editing video files are very resource intensive.

Wait..what do mean by that?

What it means is that video editing requires powerful processors and memory. Since web servers will definitely have better processors and memory than your smartphones, they will always be better.

So what does that mean to you?

It simply means that you will have more video editing features than what you will see on your smartphone video editor apps.

So there you have it. These were some of the ways you can edit your videos for your WhatsApp Status. Each of these methods come at its own advantages and disadvantages. So which one you should use will completely depend on your requirement.

So hope this article was helpful to you. If you have any queries or comments about it, do let us know in the comment section below.

So until next time. take care!

Looking For Dark Sky Alternative Android App? Check this out!


Python Add Text To An Image Using Matplotlib Library

We can use Python programming language to add text to an image using its Matplotlib library. In this tutorial, we will take a look at the Matplotlib library and learn how to accomplish this. The process of adding text to an image is often also called as annotating text to an image.

What Is Python Matplotlib library?

Matplotlib is a Python data visualization library that is often used to plot graphs and charts to represent a dataset in a meaningful way. However, we can also use Matlplotlib to do some basic editing on an image file. We can use it to overlay graphical data over an image or plot graphs.

But in this tutorial let us make use of Matlplotlib to add basic text annotation to our image. In other words, we will use Python Matplotlib to add text to our image file.

Adding Text To An Image Using Python Matplotlib Library

In order to get started, we first need to use an image file over which we would like to add text. In this example, I will make use of this picture of a butterfly that I shot in my garden. This is a simple JPG file that I got by capturing the butterfly image using my Android smartphone’s camera.

Picture Of A Butterfly. Shot On Motorola One Action Android smartphone

This is a 278KB JPG file over which I would like to add an annotated text stating “What A Wondeful World!”. I woud like the text to be Orange in color with a font size of 30 and stylized to be bold. I would also like to place this text at the bottom of the image, somewhere over here:

Butterfly image highlighting the area where we would like our text to appear at.
Butterfly image highlighting the area where we would like our text to appear at.

So enough of theory, let us start writing our Python program to add the text to our image. Fire up your favorite text editor to start writing your code. In my case I use VS Code editor, but you can use any text editor you want.

Want to learn more about VS Code editor? Check this article.

Python Program To Add Text To An Image Using Matplotlib

The first line of code we would like to add in our program is:

import matplotlib.pyplot as plt

What this line does is that it would import our matlotlib library’s pyplot module into our program. So this is imported as plt so every time we want to make use of it, we would call it by using the plt name.

Next thing we would like to import is the Python Imaging Library (aka PIL)’s Image module. We need to use this module to import the image file (butterfly.jpg) into our program. So this is achieved by using the following piece of code:

from PIL import Image

We will then go ahead with importing the butterfly.jpg file into our program using the line:

img ="/home/amar/Pictures/butterfly.jpg")

The method will open our file, read its content and store it into the variable img. Notice here again that we have imported the buttefly.jpg file into a new Python variable called img. Because of this from now on wards, we will be able to access the content of this image file by using the img Python variable.

With the image being available, its time to start editing it using Matplotlib library.

The first step in using Matplotlib library is to create a Matplotlib’s figure object, which forms the canvas of our image. All the operations we do from now on will be with respect to this canvas element. We can create Matplotlib’s figure object by using the lines:


Wait a second! What does this line even mean? What does figsize stand for and what values are we passing here? Let us answer these questions first.

Understanding Figsize Parameter Of Matplotlib’s Figure Object

figsize is a parameter we need to pass to the matplotlib plt module’s figure() method. It allows us to specify the exact width and height of our image.

Therefore when we pass the values (12,8) to this parameter, we are specifying these exact values. These values are expressed in the unit of inches. So when we say (12,8), we are asking the Matplotlib library to draw a figure with a width of 12 inches and a height of 8 inches.

Following this, we will ask Matplotlib library to draw our picture onto the figure‘s canvas by calling imshow fuction as follows:


As a result of the above code, Matplotlib will draw to image onto our figure object. However, it must be noted that it only draws the image to our figure object. But nothing will be displayed to the end user. If we want to display this image, we need to call another Matplotlib function But we do not want to display it yet. Therefore, we will discuss about this function later in the article when we actually make use of it.

So for now we will further move on with our code. As of now we have created a Matplotlib’s figure canvas object, we have opened our image file and drawn this image onto our figure object’s canvas. It is now time to write our intended “What a wonderful world!” text on top of it.

Adding Text Using Plot’s Text Function

In order for us to write text over an image, Matlplotlib provides us with yet another method, not surprisingly called the text function. So we can access it as part of the plt module. Also, we can find this function’s signature and the parameters it takes in link to its official documentation. With this information, we can finally call the text function to print our string onto the figure object’s canvas like this:

plt.text(200, 700, "What A Wonderful World!", color="orange", fontdict={"fontsize":30,"fontweight":'bold',"ha":"left", "va":"baseline"})

From the above code, we can interpret the parameters of plt.text function as follows:

X & Y Co-Ordinates Parameter

The first two parameters of this function are the x & y co-ordinates of the image. We set its values to be 200 and 700 so that the string starts from there.

Annotation Text Parameter

Following the two co-ordinate parameters is the annotation text paramter. This is the parameter which takes in the text string that we would like to print. We have set it to our string “What A Wonderful World!” that we wanted to add to our image.

Text Color Parameter

Following the the text parameter is the color parameter. We use this parameter to set the color of the string. In our case, we have set this to orange color.

Font Dict Parameters

Finally, we set the parameters for the type of font to use and its properties. In our case, we are asking Matplotlib library to set the following properties to our text fonts:

  • We want to use a font size of 30
  • We want the font to be bold
  • Next, we want the text’s horizontal alignment to be to its left
  • Finally, we also want it to be vertically aligned to its baseline

So with these properties set, we have finally defined the text that we wanted on our canvas. Hence, it is now time to display this image on our screen.

Displaying Image On Screen Using Matplotlib

This is the final stage of our code. At this point, we want our program to simply display the content of our modified image on our screen. So we will achieve this by using the function that we had discussed earlier.

Using Matplotlib’s Show Function To Display The Image On Screen

The code to display our image on screen is pretty simple

We just call the function as shown above. This should finally display the image in a new window on our screen.

Summary Of Python Program To Add Text To Image

So to summarize, our final program in full looks like this:

import matplotlib.pyplot as plt
from PIL import Image

img ="/home/amar/Pictures/butterfly.jpg")

#Finishes drawing a picture of it. Does not display it.
plt.text(200, 700, "What A Wonderful World!", color="orange", fontdict={"fontsize":30, "fontweight":'bold', "ha":"left", "va":"baseline"})
#Display the image

How To Save Matplotlib Image To A File

So far we edited the image file and added our own text on top of it. We were also able to display the final result to the end user screen in a separate window.

But what if we wanted to save this image? Can we write the program to save this edited image automatically to a new file? How to achieve this? If these are some of the questions you have running your mind then fret not. Because Matplotlib library comes to our rescue, once again!

To save the image onto a new file, Matplotlib provides us with yet another function called savefig().

Using Matplotlib’s Savefig Function To Save An Image

Matplotlib provides us with the function savefig() to save our image in a new file. It takes in many parameters which can be seen in this official documentation link. However, for our case, we simply want to save the image to a simple jpg file. So we need not have to use all the parameters defined in that link. We can simply use the following code to save it as a JPG file:


From the above code, we can see that we used plt.savefig() in its simplest form. We just added a path to the new file and saved it as a jpg file. Yes, the format of the file in which we want it to be saved is given by simply using the appropriate file extension. Matplotlib is intelligent enough to understand this and save it accordingly. Hence, if you wanted to save it as a PNG file, you just need to change the extension to .png. Its that really simple!

So with this, we can finally get our captioned image file as shown below:

Final Image file created by the Python code containing added text over the image
Final Image file created by the Python code containing added text over the image

So this was a brief tutorial on how to use Python to add text over an image programatically using Matplotlib library. Hope this was easy for you to follow up and understand. I will continue to write more articles on Python and image/video editing libraries in the future including Matplotlib. If you have any more questions or queries regarding this, do let me know in the comment section below. Until next time, ciao!


Best Visual Studio Code Extensions For HTML (VS Code Extensions)

Looking for best Visual Studio Code extensions for my web development activities, I came across a plethora of VS Code extensions made available by various developers not just for web development, but for various other types of programming activities as well.

In this article, I will list out few of these Visual Studio Code extensions suitable for HTML coding activities.

List of Visual Studio Code extensions for HTML

Intellisense (Built-in, no extension required)

I agree that this blog post started as showcasing a list of HTML Visual Studio Code extensions, but I would be doing a disservice to the developers of VS Code if I did not mention the excellent support that has been provided as built in functionality in the Visual Studio Code itself via Intellisense. VS Code Intellisense provides support for suggestions and auto completion of basic HTML tags.

Visual Studio Code’s Intellisense auto-completion support for HTML

Emmet Feature In VS Code (Again, built in, no extension required)

Emmet is my next go to feature that is built into VS Code now that I highly recommend to everyone out there that is working with HTML coding or development using Visual Studio Code.

One of the main functionality of Emmet on VS Code is to provide basic abbreviations for most of HTML code.

So say for example you are about to create a new HTML page that you want it to be mobile friendly and descibes all the basic structure of an HTML page such as UTF charset meta data, viewport type, language type etc. You can do so by simply typing “html:5” at the beginning of the document and pressing TAB key. This will trigger the Emmet’s abbreviation feature resulting in autocompleting the basic structure of a web page as shown in the GIF below:

Emmet’s Abbreviation feature in action for HTML 5

HTML5-Boilerplate VS Code HTML Extension

The next Visual Studio Code extension for HTML deals specifically with HTML 5 and is called HTML5-Boilerplate VS Code extension.

The HTML5-Boilerplate VS Code extension is very similar to that of Emmet we had discussed earlier, but differs in the fact that it specifically deals with generating boilerplate code for HTML 5. Below is a GIF showing HTML5-Boilerplate Visual Studio Code (VS Code) extension in action:

Visual Studio Code (VS Code) HTML5-Boilerplate extension in action
Installation Code: ext install sidthesloth.html5-boilerplate

HTML Live Preview VS Code HTML Extension

HTML Live Preview is another Visual Studio Code extension that as the name suggests, helps its users to do a live preview of their HTML web page during its development. What is interesting is that the HTML Live Preview VS Code extension does this at real time as shown in the GIF below:

Visual Studio HTML Live Preview extension in action
Installation Code: ext install

These are some of the HTML extensions for Visual Studio Code editor that I have come across up until now. I am pretty sure I might have missed out a lot more useful HTML extensions for VS Code, which I would continue to add to my toolkit upon discovery and update this article accordingly. For now, these extensions are bound to make my life easy while developing HTML code for my web development activities.

If you are aware of any more Visual Studio Code extensions for HTML that you found useful and you think I should try and recommend it to others, do let me know in the comments below and I will definitely look into it.

Till then, happy coding!