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Google offers an AI image classification tool that analyzes images to classify content and assign tags to them.
The tool is intended for demonstration purposes Google Visionwhich can automatically change the classification of images, but can be used as a standalone tool to see how the image detection algorithm views your images and what they are important for.
Even if you don’t use the Google Vision API to customize image detection and classification, the tool provides an interesting look at what Google’s image-related algorithms are capable of, which makes it interesting to upload images to see how the Google Vision algorithm classifies them.
This tool showcases Google’s AI and Machine learning image understanding algorithms.
It is part of Google Collection of Cloud Vision APIs which provides visual machine learning models for applications and websites.
Does Cloud Vision Tool reflect Google’s algorithm?
This is just a machine learning model and not a ranking algorithm.
Therefore, it is unrealistic to use this tool and expect it to reflect something about Google’s image ranking algorithm.
But it’s a great tool for understanding how Google’s AI and machine learning algorithms can understand images, and will offer an educational insight into how advanced today’s vision-related algorithms are.
The data provided by this tool can be used to understand how the machine might understand what the image is about and perhaps give an idea of how accurate it is the picture matches general theme of the website.
Why is the image sorting tool useful?
Pictures can play an important role in search visibility and CTR from the different ways in which web page content appears in Google.
Potential website visitors researching a topic use images to navigate to the right content.
Thus, using attractive images that are relevant to search queries can be useful in certain contexts to quickly communicate that a web page is relevant to what a person is looking for.
The Google Vision tool provides a way to understand how an algorithm can view and classify an image based on what is in the image.
Google’s guidelines for image SEO I recommend:
“High-quality photos attract users more than blurry, fuzzy images. In addition, sharp images are more attractive to users in the results thumbnail and increase the likelihood of users getting traffic.”
If the Vision tool is having trouble figuring out what the image is about, it could be a sign that potential website visitors may be having the same problem and decide not to visit the site.
What is Google Image Tool?
The tool is a way to expose Google’s Cloud Vision API.
The Cloud Vision API is a service that allows applications and websites to connect to machine learning tools and provide scalable image analysis services.
The standalone tool lets you upload an image and tells you how Google’s machine learning algorithm interprets it.
Google’s Cloud Vision page describes how the service can be used as follows:
“Cloud Vision enables developers to easily integrate vision detection features into applications, including image tagging, face and landmark detection, optical character recognition (OCR), and explicit content tagging.”
These are the five ways Google’s image analysis tools classify uploaded images:
- Faces.
- Objects.
- Labels.
- Properties.
- Safe search.
Faces
The “faces” tab offers an analysis of the emotions expressed by the image.
The accuracy of this result is fairly accurate.
The image below is of a person described as confused, but that is not really an emotion.
The AI describes the emotion expressed on the face as surprise with a 96% confidence level.
Objects
The “objects” tab shows what objects are in the picture, such as glasses, people, etc.
The tool accurately identifies horses and humans.

Labels
The “Tags” tab shows details about the image that Google recognizes, such as ears and mouth, as well as conceptual aspects such as portrait and photo.
This is particularly interesting because it shows how deeply Google’s AI can understand what’s in an image.

Does Google use this as part of their ranking algorithm? This is something that is not known.
Properties
Properties are the colors used in the image.

At first glance, the point of this tool is not obvious and it may seem a bit useless.
But in reality, the colors of an image can be very important, especially for a featured image.
Pictures that contain a very wide range of colors can be a sign of a poorly selected image with an inflated size, which should be paid attention to.
Another useful insight about images and color is that images with darker color gamuts tend to result in larger image files.
In terms of SEO, the Properties section can be useful for identifying images throughout the site that can be replaced with less bloated ones.
Additionally, attention should be paid to color ranges for featured images that are muted or even grayscale, as featured images that lack vibrant colors tend not to stand out on social media. Google Discoverand Google News.
For example, featured images that are vibrant can be easily scanned and may receive a higher click-through rate (CTR) when displayed in search results or on Google Discover because they attract the eye better than images that are muted and they fade. into the background.
There are many variables that can affect image CTR, but this provides a way to increase your site-wide image audit process.
eBay performed a product image study and CTR and discovered that images with lighter background colors tend to have higher CTR.
eBay researchers found:
“In this paper, we find that product image characteristics can influence user search behavior.
We find that certain image characteristics are related to product search CTR and that these features can help model CTR for shopping search applications.
This study may encourage sellers to provide better images for the products they sell.”
Oddly enough, using vibrant colors for featured images can be beneficial for increasing CTR for sites that rely on traffic from Google Discover and Google News.
Obviously, there are many factors that affect CTR from Google Discover and Google News. But an image that stands out from the rest can help.
For this reason, using the Vision tool to understand the colors used can be useful for reduced image revision.
Safe search
Safe search shows how the image is classified for dangerous content. Descriptions of potentially dangerous images are as follows:
- An adult.
- Scam.
- Medical.
- Violence.
- Racy.
Google Search has filters that rate a website for dangerous or inappropriate content.
This is why the SafeSearch section of the tool is very important, because if an image accidentally triggers the SafeSearch filter, the website may not rank among potential website visitors searching for the website’s content.

The screenshot above shows a photo evaluation of racehorses on a racetrack. The tool accurately recognizes that there is no medical or adult content in the image.
Text: Optical Character Recognition (OCR)
Google Vision has an amazing ability to read text on a photo.
The Vision tool can accurately read the text in the image below:

As seen above, Google has the option (via Optical Character Recognition or OCR), to read words on pictures.
However, this is not an indication that Google is using OCR for search ranking purposes.
The fact is that Google recommends using words around images to make it easier to understand what the image is about, and it may be that Google still depends on the words surrounding the image to understand what the image is. is about and relevant to.
Google’s SEO SEO guidelines repeatedly emphasize the use of words to provide context for the images.
“By adding more context around images, the results can become much more useful, which can lead to higher quality traffic to your website.
… Place images next to relevant text whenever possible.
… Google retrieves information about the subject of the image from the content of the page …
… Google uses alt text along with computer vision algorithms and page content to understand the content of the image.”
Google’s documentation makes it very clear that Google depends on the context of the text around the images to understand what the image is talking about.
Takeaway
Google’s Vision AI Tool provides a way to test Google’s Vision AI so that a publisher can connect to it via an API and use it to customize image classification and retrieve data for use on a website.
But it also provides insight into how far algorithms for image annotation, annotation, and optical character recognition have advanced.
Upload an image here to see how it’s sorted and whether the machine sees it the same way you do.
More resources:
Featured image by Maksim Shmeljov/Shutterstock
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