How To Find A Pattern With Only A Picture: A Knitter’s and Crocheter’s Best Friend

We’ve all been there. You’re browsing the internet, and you stumble across a delightful snapshot of a crochet masterpiece or a beautifully knitted scarf. You want to create that project, but there’s just one problem – you don’t have a clue where that image originated or how to find a pattern.

Well, fret no more! Google Reverse Image Search is here to play detective for you, making your knitting or crocheting journey that much smoother. Let’s delve deeper into this amazing tool and learn how you can leverage it to unravel the secrets of inspiring images.

What’s Google Reverse Image Search Anyway?

In simple terms, Google Reverse Image Search is a useful feature provided by our favourite search engine that allows you to search the vast World Wide Web using an image rather than words.

It’s like asking Google, “Hey, where did this picture come from?” and Google promptly provides the best possible answers.

How Can This Help You as a Knitter or Crocheter?

Imagine that you’re scrolling through Pinterest and you spot an image of a brilliantly crafted granny square afghan. But alas! There’s no pattern, tutorial or any clue about its origin. Sound familiar?

Here’s where Google Reverse Image Search lights the path. All you need to do is use the image as the search query. Google will then scan its database for similar images and supply pertinent information, which may hold crucial details about the origin of the pattern featured in the image.

Your Step-by-Step Guide to Harness the Power of Google Reverse Image Search

Let’s break down this process into simple steps so that you can become a pro at unscrambling the origins of your next crochet or knitting project.

Step 1: Save the Image

Firstly, you need to save the desired image to your device. This might mean taking a screenshot if you’re on a mobile device, or right-clicking and choosing “Save Image As” if you’re on a computer.

Step 2: Open Google Images

Head over to Google Images. This takes you to the portal where the magic happens.

Step 3: Upload the Image

On your computer, click the camera icon in the search bar, then select ‘Upload an image’. Choose the image you saved earlier. If you’re on a mobile device, you might need to request the desktop site. Most mobile browsers will have this option in their menu.

Step 4: Let Google Do the Legwork

Once the image is uploaded, Google will get to work. Soon, it’ll present you with a list of websites where the image appears. This could be blogs, forums, online stores, or social media platforms.

Step 5: Go Detective!

Now it’s your turn to play detective. Scan through the provided links, looking for any that seem likely to have the information you need. You might find the original pattern, a tutorial, the name of the creator, or at least find where the image was first used.

Remember not to get discouraged if you don’t find the perfect match on your first try. It might take some rummaging, but the chances are high that the origins of that knitted scarf or crochet masterpiece will reveal themselves in the end, making your diligence very worthwhile!

Making the Most of Google Reverse Image Search

There’s no denying that the Internet has become a treasure trove of inspiration for crafters worldwide, but it can also be a labyrinth when trying to trace the source of that inspiration. Google Reverse Image Search becomes the guiding thread, triumphantly leading you to the desired pattern or tutorial.

This tool is especially handy when you find an image shared without credit or context. With a few simple clicks, you can make sure to give credit where credit’s due and even find some fantastic new fabric art blogs and communities in the process.

So, next time you find yourself ensnared by the appeal of an impressive knitting or crochet project and can’t find the pattern, turn to Google Reverse Image Search. It’s sure to become your new loyal sidekick on your yarn-spinning adventures, propelling you toward your next stunning creation.

This article was originally published on January 7, 2015.