Welcome back to Best of the Design Web, where we feature some of the best design tutorials of this past month! Tackle new and exciting projects from across the web and let us know your favorites in the comments!
10 Amazing Tutorials From Across the Web
How to Create a Valentine’s Sweater Illustration in Adobe Illustrator
In this tutorial, our very own Ivan Petrusevski teaches you how to create a charming Valentine’s sweater. Learn how to create a lovely illustration using simple shapes, brushes, and colors.
Create a Wood Cut Text Treatment With Graphic Styles in Illustrator
In this tutorial, our very own Mary Winkler teaches you how to create an awesome wood-cut effect for your text in illustrator. Learn how to create a simple wood pattern first before turning it into an amazing graphic style.
How to Create a Big Bear Photo Manipulation in Photoshop
In this video, Rafy A shows you how to composite several images together to create a big bear photo manipulation. Learn how to use Layer Masks effectively as well as how to adjust colors using Adjustment Layers.
In this tutorial, Christian Krammer breaks down the steps of creating a realistic clock in Sketch. Achieve your own detailed clock with simple gradients and borders and add it to your forever growing icon collection.
How to Create an Editable Retro Text Style in Adobe Illustrator
In this tutorial, Chris Spooner shows you how to create an awesome retro text style to use in your designs. Learn some useful tricks using the Appearance panel to create a graphic style that works with live text.
In this tutorial, learn how to draw, color, and detail fabulously colorful hair in the popular manga style. Michelle Hoefener teaches you how to lay down the basic shapes before finishing up with the final details and color.
Step out of the norm of flat design graphics with this 3D Illustrator tutorial. In this tutorial, Thomas Burden teaches you how to use Illustrator’s 3D extrusions and Map Art function to create stunning illustrations.
Before you go, be sure to pick up some amazing premium design assets from GraphicRiver and Envato Elements. Browse the incredible selections of design graphics, fonts, and so much more for high-quality design.
Create a cool glitch effect with this awesome Photoshop template. This template features a fully layered, high-resolution file that lets you turn any photo into a glitch-inspired GIF animation. Step up your photo game and download this package to get instant results!
Create stunning sketch effects with this professional Photoshop action. This action allows you to simply brush over any image where you would like to apply the effect before pressing play. Turn any photo into a modern architectural sketch instantly! Helpful instructions are also included.
Create havoc in just a few short clicks with this explosive Photoshop action. This action contains four different effect directions, a fully layered file, and a helpful video tutorial for further instruction.
Create a Facebook timeline cover that is simply one of a kind. This set of timeline covers features 11 different covers with unique textural effects. Also included in this package are additional design elements like banners, ribbons, and logos that are completely customizable.
Need a professional YouTube cover for your channel? Then check out this stylish bundle pack. This pack features six creative YouTube covers that will instantly upgrade your channel. Get access to high-resolution files, professional designs, and free icons all in one awesome download.
Design incredible vector illustrations with this set of neon brushes. This set includes 19 flexible neon tube brushes you can easily adjust in Adobe Illustrator. Illuminate your designs with this awesome pack today! A quick reference guide is also available.
Or splash around with this amazing set of watercolor Photoshop brushes. This brush set includes 69 high-quality watercolor brushes along with 11 bonus textures. Incorporate these brushes into your next creative project to add gorgeous textures.
Create awesome infographics with this premium design package. This package features 40 fully layered and well-organized files with all the elements you need to design the perfect infographic. Every file is super easy to edit with versions available in both Photoshop and Illustrator formats.
Ice cream anyone? Take a big bite out of this delicious ice-cream-inspired menu template. Great for little shops looking to improve their marketing materials, this template features a clean, modern design with vibrant colors. It’s available in both Photoshop and Illustrator files, and we just know you’ll love this menu!
Infographics are a creative way to educate the world. So use this incredible modern infographics package to add that special pizazz to your presentations today! Included in this package are editable vector graphs, bars, and so much more!
Being creative is great, but when is it better to forgo style for substance? Well, according to the science, it’s when you’re trying to get people to look at your website and, more importantly, stay there (ie. have a low bounce rate). Now, the important misconception we need to abolish here is simplicity doesn’t mean less creativity. In fact, in some instances, implementing a “simple” design actually, takes a lot more creativity than letting your mind run away with you.
For example, in our recent round-up of electricity related logos, the most instantly recognisable and, therefore appealing in a commercial sense where the simpler ones. The Single lightning bolt from electricity or the flash symbol with the taxi-style color combinations for the Electric Taxi Company would be considered by many more striking than the more complex offering from elektrika S.
Of course, perception and personal preference play a huge part in whether something is considered both simple and attractive, but anything that does fall into the former category is more appealing according to Google. A 2012 study into our perception of websites found that visitors judge a website’s “beauty” or appeal within 1/50th of a second. Moreover, websites that were deemed “visually complex” were rated less attractive than sites with simple designs.
This drive for simplicity is something that taps into our human psyche as we strive for cognitive fluency through prototypical designs. In other words, we naturally gravitate to things that are easy to think about which is why prototypical (recognizable) patterns and designs are appealing.
For example, if you’re a fan of social media websites, Facebook draws you in because it’s not only what you “expect” from a social media site, but it’s easy to read. Forgetting the two side bars for a moment, the main interface is simply a feed/list of text and images.
Nowhere on the site are you bombarded with flashing images, banners, overly ornate decorating or garish color schemes? In fact, it’s Facebook’s simplicity that makes it both popular and functional. Indeed, the goal of any user on Facebook is to read updates from their friends and interact with them. The overall design allows this process to take place in the most direct and efficient way possible. Similarly, if you’re looking for the best deal on something, you expect a comparison/review site to have a set format. For example, in this list at OnlineCasinos, you’ll receive a quick overview of the platform in question and highlights such as the number of games available and how big the bonus is.
We Gravitate to What’s Simple and Familiar
This trend can also be seen over at Amazon. Click on the “Today’s Deals” option and you’ll see a grid filled with images, star ratings and prices. From this, you can click on the “view deal” button to know more. Essentially, in this instance, a “prototypical” design for a review site is a list that provides the product name and a few highlights. As consumers, we understand this layout and, moreover, it’s easy to digest. So, even though it’s simple, it works and, therefore, looks appealing. Similarly, on this Canadian site for casino deals, star ratings and teaser text help you make a snap decision on which review/site you want to visit.
In fact, as we move increasingly to a mobile-based internet experience, this focus on simplicity becomes even more important. No longer can you cram a page with text, animations, and endless buttons. Yes, it might look great on your desktop, but when it comes to browsing via a mobile, people want ease of access. Indeed, according to stats from 2016, people around the world spent 86 minutes a day browsing via their phones compared to 36 minutes on their desktops.
This discrepancy highlights the need for web designers to get creative with their use of space. Where white space and scaled backed graphics used to be frowned upon, they’re now the in thing. As well as jiving with the way our mind seeks out information, it’s a necessary as we move towards mobile browsing. So, while complexity is often seen as attractive in some arenas, the internet is all about simplicity. If you want to create something that’s both beautiful and useful, it pays to strip take things back to basics.
Just in time for the entry deadline of March 1st, the following guest post from Sissy Hobizal of FirstMates reveals the process behind branding The Motion Awards by Motionographer. First Mate’s goal: build an ego-destroying design machine to do the work for them.
This is a full chapter excerpt from Wladston Viana Ferreira Filho’s brand new book Computer Science Distilled which he has graciously allowed for us to publish here.
In almost every computation, a variety of arrangements for the processes is possible. It is essential to choose that arrangement which shall tend to minimize the time necessary for the calculation.
How much time does it take to sort 26 shuffled cards? If instead, you had 52 cards, would it take twice as long? How much longer would it take for a thousand decks of cards? The answer is intrinsic to the method used to sort the cards.
A method is a list of unambiguous instructions for achieving a goal. A method that always requires a finite series of operations is called an algorithm. For instance, a card-sorting algorithm is a method that will always specify some operations to sort a deck of 26 cards per suit and per rank.
Less operations need less computing power. We like fast solutions, so we monitor the number of operations in our algorithms. Many algorithms require a fast-growing number of operations when the input grows in size. For example, our card-sorting algorithm could take few operations to sort 26 cards, but four times more operations to sort 52 cards!
To avoid bad surprises when our problem size grows, we find the algorithm’s time complexity. In this chapter, you’ll learn to:
Count and interpret time complexities
Express their growth with fancy Big-O‚s
Run away from exponential algorithms
Make sure you have enough computer memory.
But first, how do we define time complexity?
Time complexity is written T(n). It gives the number of operations the algorithm performs when processing an input of size n. We also refer to an algorithm’s T(n) as its running cost. If our card-sorting algorithm follows T(n)=n2, we can predict how much longer it takes to sort a deck once we double its size: T(2n)T(n)=4.
Hope for the best, prepare for the worst
Isn’t it faster to sort a pile of cards that’s almost sorted already?
Input size isn’t the only characteristic that impacts the number of operations required by an algorithm. When an algorithm can have different values of T(n) for the same value of n, we resort to cases:
Best Case: when the input requires the minimum number of operations for any input of that size. In sorting, it happens when the input is already sorted.
Worst Case: when the input requires the maximum number of operations for any input of that size. In many sorting algorithms, that’s when the input was given in reverse order.
Average Case: refers to the average number of operations required for typical inputs of that size. For sorting, an input in random order is usually considered.
In general, the most important is the worst case. From there, you get a guaranteed baseline you can always count on. When nothing is said about the scenario, the worst case is assumed. Next, we’ll see how to analyze a worst case scenario, hands on.
2.1 Counting Time
We find the time complexity of an algorithm by counting the number of basic operations it requires for a hypothetical input of size n. We’ll demonstrate it with Selection Sort, a sorting algorithm that uses a nested loop. An outer for loop updates the current position being sorted, and an inner for loop selects the item that goes in the current position1:
for current ← 1 … list.length - 1
smallest ← current
for i ← current + 1 … list.length
if list[i] < list[smallest]
smallest ← i
Let’s see what happens with a list of n items, assuming
the worst case. The outer loop runs n-1 times and does two
operations per run (one assignment and one swap) totaling 2n-2 operations. The inner loop first runs n-1 times, then n-2 times, n-3 times, and so on. We know how to sum these types of sequences2:
number of inner loop runs=
n-1 + n-2 + ⋯+2+1⏞n-1total runs of the outer loop.
In the worst case, the if condition is always met. This means the inner loop does one comparison and one assignment (n2-n)/2 times, hence n2-n operations. In total, the algorithm costs 2n-2 operations for the outer loop, plus n2-n operations for the inner loop. We thus get the time complexity:
Now what? If our list size was n=8 and we double it, the
sorting time will be multiplied by:
If we double it again we will multiply time by 3.90. Double it over and over and find 3.94, 3.97, 3.98. Notice how this gets closer and closer to 4? This means it would take four times as long to sort two million items than to sort one million items.
2.1.1 Understanding Growth
Say the input size of an algorithm is very large, and we increase it even more. To predict how the execution time will grow, we don’t need to know all terms of T(n). We can approximate T(n) by its fastest-growing term, called the dominant term.
The Index Card Problem: Yesterday, you knocked over one box of index cards. It took you two hours of Selection Sort to fix it. Today, you spilled ten boxes. How much time will you need to arrange the cards back in?
We’ve seen Selection Sort follows T(n)=n2+n-2. The fastest-growing term is n2,
therefore we can write T(n)≈n2. Assuming there are n cards per box, we find:
It will take you approximately (100×2)hours=200 hours! What if we had used a different sorting method? For example, there’s one called „Bubble Sort” whose time complexity is T(n)=0.5n2+0.5n. The fastest-growing term then gives T(n)≈0.5n2, hence:
The 0.5 coefficient cancels itself out! The idea that n2-n-2 and 0.5n2+0.5n both grow like n2 isn’t easy to get. How does the fastest-growing term of a function ignore all other numbers and dominate growth? Let’s try to visually understand this.
In Figure 2.2, the two time complexities we’ve seen are compared to n2 at different zoom levels. As we plot them for larger and larger values of n, their curves seem to get closer and closer. Actually, you can plug any numbers into the bullets of T(n)=∙n2+∙n+∙, and it will still grow like n2.
Remember, this effect of curves getting closer works if the fastest-growing term is the same. The plot of a function with a linear growth (n) never gets closer and closer to one with a quadratic growth (n2), which in turn never gets closer and closer to one having a cubic growth (n3).
That’s why with very big inputs, algorithms with a quadratically growing cost perform a lot worse than algorithms with a linear cost. However, they perform a lot better than those with a cubic cost. If you’ve understood this, the next section will be easy: we will just learn the fancy notation coders use to express this.
2.2 The Big-O Notation
There’s a special notation to refer to classes of growth: the Big-O notation. A function with a fastest-growing term of 2n or weaker is O(2n); one with a quadratic or weaker growth is O(n2); growing linearly or less, O(n), and so on. The notation is used for expressing the dominant term of algorithms’ cost functions in the worst case—that’s the standard way of expressing time complexity3.
Both Selection Sort and Bubble Sort are O(n2), but we’ll soon discover O(nlogn) algorithms that do the same job. With our O(n2) algorithms, 10× the input size resulted in 100× the running cost. Using a O(nlogn) algorithm, 10× the input size results in only 10log10≈34× the running cost.
When n is a million, n2 is a trillion, whereas nlogn is just a few million. Years running a quadratic algorithm on a large input could be equivalent to minutes if a O(nlogn) algorithm was used. That’s why you need time complexity analysis when you design systems that handle very large inputs.
When designing a computational system, it’s important to anticipate the most frequent operations. Then you can compare the Big-O costs of different algorithms that do these operations4. Also, most algorithms only work with specific input structures. If you choose your algorithms in advance, you can structure your input data accordingly.
Some algorithms always run for a constant duration regardless of input size—they’re O(1). For example, checking if a number is odd or even: we see if its last digit is odd and boom, problem
solved. No matter how big the number. We’ll see more O(1) algorithms in the next chapters. They’re amazing, but first let’s see which algorithms are not amazing.
We say O(2n) algorithms are exponential time. From the graph of growth orders (Figure 2.3), it doesn’t seem the quadratic n2 and the exponential 2n are much different. Zooming out the graph, it’s obvious the exponential growth brutally dominates the quadratic one:
Exponential time grows so much, we consider these algorithms „not runnable”. They run for very few input types, and require huge amounts of computing power if inputs aren’t tiny. Optimizing every aspect of the code or using supercomputers doesn’t help. The crushing exponential always dominates growth and keeps these algorithms unviable.
To illustrate the explosiveness of exponential growth, let’s zoom out the graph even more and change the numbers (Figure 2.5). The exponential was reduced in power (from 2 to 1.5) and had its growth divided by a thousand. The polynomial had its exponent increased (from 2 to 3) and its growth multiplied by a thousand.
Some algorithms are even worse than exponential time algorithms. It’s the case of factorial time algorithms, whose time complexities are O(n!). Exponential and factorial time algorithms are horrible, but we need them for the hardest computational problems: the famous NP-complete problems. We will see important examples of NP-complete problems in the next chapter. For now, remember this: the first person to find a non-exponential algorithm to a NP-complete problem gets a million dollars5 from the Clay Mathematics Institute.
It’s important to recognize the class of problem you’re dealing with. If it’s known to be NP-complete, trying to find an optimal solution is fighting the impossible. Unless you’re shooting for that million dollars.
2.4 Counting Memory
Even if we could perform operations infinitely fast, there would still be a limit to our computing power. During execution, algorithms need working storage to keep track of their ongoing calculations. This consumes computer memory, which is not infinite.
The measure for the working storage an algorithm needs is called space complexity. Space complexity analysis is similar to time complexity analysis. The difference is that we count computer memory, and not computing operations. We observe how space complexity evolves when the algorithm’s input size grows, just as we do for time complexity.
For example, Selection Sort just needs working storage for a fixed set of variables. The number of variables does not depend on the input size. Therefore, we say Selection Sort’s space complexity is O(1): no matter what the input size, it requires the same amount of computer memory for working storage.
However, many other algorithms need working storage that grows with input size. Sometimes, it’s impossible to meet an algorithm’s memory requirements. You won’t find an appropriate sorting algorithm with O(nlogn) time complexity and O(1) space complexity. Computer memory limitations sometimes force a tradeoff. With low memory, you’ll probably need an algorithm with slow O(n2) time complexity because it has O(1)
In this chapter, we learned algorithms can have different types of voracity for consuming computing time and computer memory. We’ve seen how to assess it with time and space complexity analysis. We learned to calculate time complexity by finding the exact T(n) function, the number of operations performed by an algorithm.
We’ve seen how to express time complexity using the Big-O notation (O). Throughout this book, we’ll perform simple time complexity analysis of algorithms using this notation. Many times, calculating T(n) is not necessary for inferring the Big-O complexity of an algorithm.
We’ve seen the cost of running exponential algorithms explode in a way that makes these algorithms not runnable for big inputs. And we learned how to answer these questions:
Given different algorithms, do they have a significant difference in terms of operations required to run?
Multiplying the input size by a constant, what happens with the time an algorithm takes to run?
Would an algorithm perform a reasonable number of operations once the size of the input grows?
If an algorithm is too slow for running on an input of a given size, would optimizing the algorithm, or using a supercomputer help?
1: To understand an new algorithm, run it on paper with a small sample input.
2: In the previous chapter, we showed ∑i=1ni=n(n+1)/2.
3: We say ‚oh’, e.g., „that sorting algorithm is oh-n-squared„.
5: It has been proven a non-exponential algorithm for any NP-complete problem could be generalized to all NP-complete problems. Since we don’t know if such an algorithm exists, you also get a million dollars if you prove an NP-complete problem cannot be solved by non-exponential algorithms!
Computer Science Distilled: Learn the Art of Solving Computational Problems by Wladston Viana Ferreira Filho is available on Amazon now.
These aren’t particularly hard to web search for, but just in case you didn’t know they existed I figured I’d drop them here. I’ve used all three of these in the past and I think they do a good job of driving home how cool of patterns you can make in SVG with such little code.
So there is polygon() in CSS and <polygon> in SVG. They are closely related, but there are all kinds of weirdnesses. For example, you can use path() in CSS to update the d attribute of a <path>, but you can’t do the same with polygon() and <polygon>.
Part of the problem is that polygon() in CSS only accepts numbers with units, like px, %, em, or whatever.
The trick is that you can force the SVG coordinates to behave like percentage coordinates (even with weird viewBoxes) with some light math, a transform attribute, and a special clipPathUnits attribute.
Those two values are 1/329.6667 and 1/86, respectively, and they effectively scale every point in the d attribute to fit into the needed 0–1 range. Thus we have an SVG clipping path that scales with the element and fits to its dimensions!
tutorial we’re going to learn how to create a set of four computer peripherals,
using the same body as the central structure to which we will add all the key features that make each object stand out. As always, we’re
going to rely on the use of some basic geometric shapes, combined with the
power of the Align panel.
That being said, grab that old coffee mug, and let’s get started!
Since I’m hoping that you already have
Illustrator up and running in the background, bring it up and let’s set up a New Document (File > New or Control-N)
using the following settings:
of Artboards: 1
And from the Advanced tab:
Effects: Screen (72ppi)
Preview Mode: Default
tip: some of you might have noticed that the Align New Objects to Pixel Grid option
is missing. That’s because I’m running the new CC 2017 version of the
software, where great changes have been made to the way Illustratorhandles the way shapes snap to the underlying Pixel Grid.
2. How to Set Up a Custom Grid
Since we’re going to be creating the icons
using a pixel-perfect workflow, we’ll want to set up a nice little grid so that we can have full control
over our shapes—that is if we’re running the older version of the software.
Go to the Edit > Preferences > Guides & Grid submenu, and adjust
the following settings:
Once we’ve set up our custom grid, all we
need to do in order to make sure our shapes look crisp is enable the Snap to Grid option found under the View menu, which will transform into Snap to Pixel each time you enter Pixel Preview mode.
Now, if you’re new to
the whole “pixel-perfect workflow”, I strongly recommend you go through my how
to create pixel-perfect artwork tutorial, which will help you widen your
technical skills in no time.
3. How to Set Up the Layers
With the new document created, it would be
a good idea to structure our project using a couple of layers, since this way
we can maintain a steady workflow by focusing on one icon at a time.
That being said, bring up the Layers panel, and create a total of five
layers, which we will rename as follows:
layer 1: reference grids
layer 2: tablet
layer 3: mouse
layer 4: keyboard
layer 5: midi
4. How to Create the Reference Grids
Reference Grids (or Base Grids)
are a set of precisely delimited reference surfaces, which allow us to build
our icons by focusing on size and consistency.
Usually, the size of the grids determines
the size of the actual icons, and they should always be the first decision you
make when you start a new project, since you’ll always want to start from the
smallest possible size and build on that.
Now, in our case, we’re going to be
creating the icon pack using just one size, more exactly 128 x 128 px, which is a fairly large one.
Start by locking all
but the reference grid layer, and then grab the Rectangle Tool (M) and create a 128 x 128 px orange (#F15A24) square, which will help define the
overall size of our icons.
Add a smaller 120 x 120 px one (#FFFFFF) which will
act as our active drawing area, thus giving us an all-around 4 px padding.
Group the two squares composing the
reference grid using the Control-G keyboard
shortcut, and then create three copies at a distance of 40 px from one another, making sure to align them to the center of
Once you’re done,
lock the current layer and move on to the next one where we’ll start working on
our first icon.
5. How to Create the Repeating Body
As I’ve already pointed out, we’re going
to create all four icons using the same body, onto which we will
gradually add the key features that give them their “identity”. That
being said, make sure you’re on the right layer (that would be the second one)
and then zoom in the first reference grid so that we can have a better view of the shapes.
Start by creating a 112 x 100 px rounded rectangle with an 8 px Corner Radius, which we will
color using #60677C, and then center align to the underlying active drawing
area, at a distance of 4 px from its
Give the shape that
we’ve just created an outline using the Stroke method, by creating a copy of it (Control-C
> Control-F) which we will adjust by first changing its color to #2B3249,
and then flipping its Fill with its Stroke (Shift-X), making sure to set its Weight to 8 px afterwards.
Using the Pen Tool (P) draw a 16 px tall 8 px thick Stroke line
(#2B3249) starting from the center of the outline’s top edge, and going all the
way to the outer limit of the active drawing area. Once you’re done, you
can select and group all three shapes together using the Control-G keyboard shortcut.
Now that we have our repeating body, all
we have to do is create three copies of it (Control-C > Control-F three times), and position one onto each
of the empty reference grids.
Once you have them
all in place, you can start locking the layers so that you can keep your focus
on the first icon.
6. How to Create
the Tablet Icon
The first icon
that we’re going to tackle is the little graphics tablet, so make sure you’re
on the right layer (that would be the second one) and then zoom in on its
reference grid so that we can get started.
Create the tablet’s display using an 80 x 60 px rectangle, which we will color using white (#FFFFFF) and
then center align to the repeating body, at a distance of 12 px from its top edge.
Give the shape that we’ve just created an 8 px thick
outline (#2B3249) using the Stroke
method, selecting and grouping the two together afterwards using the Control-G keyboard shortcut.
Using the Pen
Tool (P), draw three 8 px thick
diagonal Stroke lines (#2B3249),
which we will adjust by lowering their Opacity
to just 20%. Once you’re done, select and group them together (Control-G) center aligning them to the underlying display afterwards.
Start working on the tablet’s first button, by creating a 16 x 16 px square (#BAC0CE) with an 8 px thick outline (#2B3249) which we
will group (Control-G) and then
position onto the left side of the display, at a distance of 16 px from the larger outline’s top
Create the second left-sided button using a copy (Control-C > Control-F) of the one that we’ve just made, which we
will position underneath, making sure to change the fill shape’s color to white
(#FFFFFF) once we have it in place. Once you have both buttons, group them (Control-G) since we’ll be using them to
create the right-sided ones.
Create the right-sided buttons using a copy (Control-C > Control-F) of the ones
that we’ve just grouped, which we will position onto the opposite side of the
Finish off the icon by adding the little pen,
which we will create using a 40 px wide 8 px thick Stroke line (#2B3249) with a Round
Cap, which we will center align to the tablet’s lower section. Once you’re
done, don’t forget to select and group all of the icon’s composing shapes
together using the Control-G
7. How to Create the
Assuming you’ve already moved on up to the next layer (that would be the
third one) and locked the previous one, zoom in on the second reference grid and
let’s start working on the mouse icon.
Create the mouse’s main body using a 44 x 68 px rectangle, which we will
color using white (#FFFFFF) and then center align to the underlying repeating
body’s main fill shape.
Adjust the shape that we’ve just created by
setting the Radius of its top Corners to 4 px and its bottom ones to 22
px from within the Transform panel’s Rectangle Properties.
Create the left-click button using a 22 x 20 px rectangle, which we will
color using #BAC0CE and then align to the larger shape’s top-left corner.
Give the mouse an 8 px thick outline (#2B3249) using the Stroke method, making sure to position it on top of its two fill
shapes (right click > Arrange >
Bring to Front).
Add the bottom button delimiter line using a 44 px wide 8 px thick Stroke (#2B3249) which we will center align to the mouse’s body, positioning it at a
distance of 12 px from the outline’s
Finish off the icon by adding the vertical
detail line separating the mouse’s two buttons, which
we will create using a 36 px tall 8 px thick Stroke line (#2B3249). Once you’re done, group (Control-G) all of the mouse’s composing
shapes together, doing the same for all of the icon’s sections afterwards.
8. How to Create
the Keyboard Icon
I’m guessing that
by now you already know the drill, so make sure you’re on the right layer (that
would be the fourth one) and zoom in on the third reference grid so that we can
Start working on the top row’s first key by creating a 14 x 14 px square (#FFFFFF) with an 8 px thick outline (#2B3249) which we
will group (Control-G) and then
position towards the repeating body’s top-left corner, at a distance of 6 px from the larger outline.
Create the top row’s remaining keys by selecting the one that we’ve
just made and then dragging it to the right side while holding down the Alt(to create the copy) and Shift keys (to drag in a perfect
straight line), to create the first instance.
Make sure that the duplicate’s outline overlaps the original one’s, and then simply press Control-D four times, which will repeat the last action and thus create the remaining duplicates,
grouping (Control-G) all the row’s
buttons together afterwards.
Create the second row of keys using the same Alt-Shift-Drag method, only this time repeat
the process by pulling down on the mouse until the copy overlaps the original’s outline.
Start working on the third row’s first key by creating a 20 x 14 px rectangle (#FFFFFF) with an 8 px thick outline (#2B3249) which we
will group (Control-G) and then
position underneath the shapes from the previous step, left aligning it to
Create the spacebar using a 44 x
14 px rectangle (#FFFFFF) with an 8
px thick outline (#2B3249), which we will group (Control-G) and then position onto the
right side of the previously created button.
Add the third row’s last button using a copy (Control-C > Control-F) of its first one, which we will position
onto the opposite side of the spacebar. Once you’re done, group (Control-G) all of the row’s shapes
together, doing the same for all the buttons afterwards.
Create the trackpad using a 28 x 20 px rectangle (#BAC0CE) with an 8 px thick outline (#2B3249), which we will group (Control-G) and then center align to the
lower section of the keyboard, positioning it at a distance of 12 px from the smaller buttons that we’ve just grouped.
Finish off the icon, by adding the little
fingerprint reader using a 12 px wide 8 px thick Stroke line (#2B3249) which we will position onto the repeating
body’s bottom-right corner, at a distance of 20 px from the trackpad. Once you’re
done, select and group all of the icon’s composing shapes together using the Control-G keyboard shortcut.
9. How to Create the Midi Controller Icon
We are now down to our fourth and last icon, so make sure you’re on the
right layer (that would be the fifth one) and let’s wrap things up!
Create the first out of the three adjustment
knobs, using an 8 x 8 px circle
which we will color using #2B3249, and then position onto the repeating body’s
top-left corner, at a distance of 8 px from
its left side and 6 px from its
Create the remaining knobs using two 8 x 8 px circles (#2B3249) which we
will vertically stack on the one from the previous step, distributing them at a
distance of 6 px from one another.
Then, once you’re done, don’t forget to select and group them
together using the Control-G keyboard
Create the volume slider using a 12
x 28 px rectangle (#FFFFFF) with an 8
px thick Stroke (#2B3249) on top
of which we will add a 12 px wide 8 px thick state indicator line (#2B3249),
which we will position in its bottom section. Group (Control-G) all three shapes together and then position them onto
the right side of the adjustment knobs, at a distance of 8 px.
Start working on the little D-pad buttons by
creating a 14 x 14 px square (#BAC0CE)
with an 8 px thick outline (#2B3249)
which we will group (Control-G) and
then position onto the right side of the volume slider, at a distance of 14 px.
Finish off the first row of D-pads by adding two
copies of the one that we’ve just made, using the Alt-Shift-Drag method, making sure to select and group (Control-G) all three of them
Create the second row of pads using a copy (Control-C > Control-F) of the one
that we’ve just finished working on, which we will position just underneath,
selecting and grouping (Control-G)
them both together afterwards.
Start working on the controller’s keys by creating a 16 x 44 px rectangle (#FFFFFF) with an 8 px thick outline (#2B3249), which we
will group (Control-G) and then
align to the bottom edge of the repeating body, at a distance of 8 px from its left edge.
Create the remaining keys using four copies (Control-C > Control-F four times) of the one that we’ve just
made, which we will distribute along its right side.
Finish off the keyboard, and with it the icon itself, by adding a 16 x 22 px rectangle (#2B3249) to the
center of the first two set of keys, selecting and grouping all of them
together afterwards. Then, once you’re done, don’t forget to select and group (Control-G) all of the icon’s composing
shapes as well.
Awesome Work, You’re Done!
There you have it—a nice and easy tutorial on how to create your
very own computer peripherals using nothing more than some simple shapes and
tools. I hope you’ve managed to keep up with each and every step and most
importantly learned something new along the way.
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Some might be happy with a couch and a laptop. Others, meanwhile, want something else to fuel their creativity.
Unfortunately, home creative spaces aren’t the easiest thing in the world to conjure up. Sure, take to any creative design agency and your mind will be blitzed with inspiration – but all of this comes at a price. A big price.
There are certainly some elements of a home creative space that are more important than others and the following shows a breakdown of the most important aspects.
If you’re like 99% of creative minds out there – you need just one thing to fuel your work. This comes in the form of music.
While phones may have become hugely capable in terms of their music-playing ability – they just don’t cut it for day-to-day use. Instead, you need a more specific solution, something along the lines of bookshelf speakers from Q Acoustics.
Let there be light
While the first suggestion looked at a type of product, the next is going to look at the light factor in more detail. In other words, you simply have to find a way to let more light creep into your room – it’s the bread and butter of creativity.
You might find the odd person who gets a spark from a blacked out room but on the whole, these people are few and far between. Instead, natural light is key and if you can’t get this, try and invest the bulk of your budget into decent overhead and task lighting which will just make your deals so much easier.
Just roll with it
This next suggestion isn’t going to appeal to every reader, but rolling carts can be an absolute godsend for anyone working in the creative industry at home. Particularly if your home is small, and you are sharing with the rest of the family, the ability to wheel in your supplies at will can be second to none.
It means that your work can travel with you around the house and in relation to families again, this can be key.
The display factor
It doesn’t matter how big your space is, you need somewhere within there to show off your best work. Just like natural light can fuel your creativity, so can your past creations.
It doesn’t matter whether you are a web designer or an artist – have somewhere to display your best work. The best suggestions tend to come in the form of magnetic rails, or maybe picture wires for artists, which can allow you to chop and change your display at a whim.
Accept that it might take baby steps
Unless you are awash with money, you aren’t going to get your dream studio straight away. Instead, you will have to chip away and build it gradually.
As such, you need to hold onto your dream. Keep taking small steps to keep your workspace alive, and keep working towards the end goal. Again, by sticking to such a philosophy, you can fuel your inspiration even more.
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