Tag Archives: images

Mobile-First indexing, structured data, images, and your site

It's been two years since we started working on "mobile-first indexing" - crawling the web with smartphone Googlebot, similar to how most users access it. We've seen websites across the world embrace the mobile web, making fantastic websites that work on all kinds of devices. There's still a lot to do, but today, we're happy to announce that we now use mobile-first indexing for over half of the pages shown in search results globally.

Checking for mobile-first indexing

In general, we move sites to mobile-first indexing when our tests assure us that they're ready. When we move sites over, we notify the site owner through a message in Search Console. It's possible to confirm this by checking the server logs, where a majority of the requests should be from Googlebot Smartphone. Even easier, the URL inspection tool allows a site owner to check how a URL from the site (it's usually enough to check the homepage) was last crawled and indexed.

If your site uses responsive design techniques, you should be all set! For sites that aren't using responsive web design, we've seen two kinds of issues come up more frequently in our evaluations:

Missing structured data on mobile pages

Structured data is very helpful to better understand the content on your pages, and allows us to highlight your pages in fancy ways in the search results. If you use structured data on the desktop versions of your pages, you should have the same structured data on the mobile versions of the pages. This is important because with mobile-first indexing, we'll only use the mobile version of your page for indexing, and will otherwise miss the structured data.

Testing your pages in this regard can be tricky. We suggest testing for structured data in general, and then comparing that to the mobile version of the page. For the mobile version, check the source code when you simulate a mobile device, or use the HTML generated with the mobile-friendly testing tool. Note that a page does not need to be mobile-friendly in order to be considered for mobile-first indexing.

Missing alt-text for images on mobile pages

The value of alt-attributes on images ("alt-text") is a great way to describe images to users with screen-readers (which are used on mobile too!), and to search engine crawlers. Without alt-text for images, it's a lot harder for Google Images to understand the context of images that you use on your pages.

Check "img" tags in the source code of the mobile version for representative pages of your website. As above, the source of the mobile version can be seen by either using the browser to simulate a mobile device, or by using the Mobile-Friendly test to check the Googlebot rendered version. Search the source code for "img" tags, and double-check that your page is providing appropriate alt-attributes for any that you want to have findable in Google Images.

For example, that might look like this:

With alt-text (good!):
<img src="cute-puppies.png" alt="A photo of cute puppies on a blanket">

Without alt-text:
<img src="sad-puppies.png">

It's fantastic to see so many great websites that work well on mobile! We're looking forward to being able to index more and more of the web using mobile-first indexing, helping more users to search the web in the same way that they access it: with a smartphone. We’ll continue to monitor and evaluate this change carefully. If you have any questions, please drop by our Webmaster forums or our public events.


An update to referral source URLs for Google Images

Every day, hundreds of millions of people use Google Images to visually discover and explore content on the web. Whether it be finding ideas for your next baking project, or visual instructions on how to fix a flat tire, exploring image results can sometimes be much more helpful than exploring text.

Updating the referral source

For webmasters, it hasn't always been easy to understand the role Google Images plays in driving site traffic. To address this, we will roll out a new referrer URL specific to Google Images over the next few months. The referrer URL is part of the HTTP header, and indicates the last page the user was on and clicked to visit the destination webpage.
If you create software to track or analyze website traffic, we want you to be prepared for this change. Make sure that you are ingesting the new referer URL, and attribute the traffic to Google Images. The new referer URL is: https://images.google.com.
If you use Google Analytics to track site data, the new referral URL will be automatically ingested and traffic will be attributed to Google Images appropriately. Just to be clear, this change will not affect Search Console. Webmasters will continue to receive an aggregate list of top search queries that drive traffic to their site.

How this affects country-specific queries

The new referer URL has the same country code top level domain (ccTLD) as the URL used for searching on Google Images. In practice, this means that most visitors worldwide come from images.google.com. That's because last year, we made a change so that google.com became the default choice for searchers worldwide. However, some users may still choose to go directly to a country specific service, such as google.co.uk for the UK. For this use case, the referer uses that country TLD (for example, images.google.co.uk).
We hope this change will foster a healthy visual content ecosystem. If you're interested in learning how to optimize your pages for Google Images, please refer to the Google Image Publishing Guidelines. If you have questions, feedback or suggestions, please let us know through the Webmaster Tools Help Forum.

Similar items: Rich products feature on Google Image Search

Image Search recently launched “Similar items” on mobile web and the Android Search app. The “Similar items” feature is designed to help users find products they love in photos that inspire them on Google Image Search. Using machine vision technology, the Similar items feature identifies products in lifestyle images and displays matching products to the user. Similar items supports handbags, sunglasses, and shoes and will cover other apparel and home & garden categories in the next few months.

The Similar items feature enables users to browse and shop inspirational fashion photography and find product info about items they’re interested in. Try it out by opening results from queries like [designer handbags].

Finding price and availability information was one of the top Image Search feature requests from our users. The Similar items carousel gets millions of impressions and clicks daily from all over the world.

To make your products eligible for Similar items, make sure to add and maintain schema.org product metadata on your pages. The schema.org/Product markup helps Google find product offerings on the web and give users an at-a-glance summary of product info.

To ensure that your products are eligible to appear in Similar items:

  • Ensure that the product offerings on your pages have schema.org product markup, including an image reference. Products with name, image, price & currency, and availability meta-data on their host page are eligible for Similar items
  • Test your pages with Google’s Structured Data Testing Tool to verify that the product markup is formatted correctly
  • See your images on image search by issuing the query “site:yourdomain.com.” For results with valid product markup, you may see product information appear once you tap on the images from your site. It can take up to a week for Googlebot to recrawl your website.

Right now, Similar items is available on mobile browsers and the Android Google Search App globally, and we plan to expand to more platforms in 2017.

If you have questions, find us in the dedicated Structured data section of our forum, on Twitter, or on Google+. To prevent your images from showing in Similar items, webmasters can opt-out of Google Image Search.

We’re excited to help users find your products on the web by showcasing buyable items. Thanks for partnering with us to make the web more shoppable!

Introducing the Open Images Dataset

Originally posted on the Google Research Blog

In the last few years, advances in machine learning have enabled Computer Vision to progress rapidly, allowing for systems that can automatically caption images to apps that can create natural language replies in response to shared photos. Much of this progress can be attributed to publicly available image datasets, such as ImageNet and COCO for supervised learning, and YFCC100M for unsupervised learning.

Today, we introduce Open Images, a dataset consisting of ~9 million URLs to images that have been annotated with labels spanning over 6000 categories. We tried to make the dataset as practical as possible: the labels cover more real-life entities than the 1000 ImageNet classes, there are enough images to train a deep neural network from scratch and the images are listed as having a Creative Commons Attribution license*.

The image-level annotations have been populated automatically with a vision model similar to Google Cloud Vision API. For the validation set, we had human raters verify these automated labels to find and remove false positives. On average, each image has about 8 labels assigned. Here are some examples:
Annotated images form the Open Images dataset. Left: Ghost Arches by Kevin Krejci. Right: Some Silverware by J B. Both images used under CC BY 2.0 license
We have trained an Inception v3 model based on Open Images annotations alone, and the model is good enough to be used for fine-tuning applications as well as for other things, like DeepDream or artistic style transfer which require a well developed hierarchy of filters. We hope to improve the quality of the annotations in Open Images the coming months, and therefore the quality of models which can be trained.

The dataset is a product of a collaboration between Google, CMU and Cornell universities, and there are a number of research papers built on top of the Open Images dataset in the works. It is our hope that datasets like Open Images and the recently released YouTube-8M will be useful tools for the machine learning community.

By Ivan Krasin and Tom Duerig, Software Engineers

* While we tried to identify images that are licensed under a Creative Commons Attribution license, we make no representations or warranties regarding the license status of each image and you should verify the license for each image yourself.

Edit and adjust images from right inside Google Slides

Sometimes to get an image just right in a presentation, you need to make some small tweaks. To help you do this without leaving Slides, a few months ago we made it possible to crop and add borders, and today we’re giving you even more control of your images with a set of new editing options.
You can now select “Image options...” from the toolbar, format menu, or right-click menu, where you can adjust the opacity, brightness, and contrast of an image, or recolor it to match the theme of your presentation.

Check out some examples of how you can edit images inside Slides in the animated gifs below.
Change the opacity of your image
Recolor your image