Google AI Image Analysis Tool is available for free


Google AI Image Analysis Tool

Discover how Google's Vision tool categorizes photographs on a large scale and how you can use it to examine how Google interprets your images. 

An AI picture categorization tool from Google analyzes photographs to categorize their content and assign labels to each one. 

The application is designed to serve as a demonstration of Google Vision, which can scale picture classification on an automatic basis and be used independently to observe how an image detection algorithm perceives your images and what they're relevant for. 

It's interesting to upload photographs to check how Google's Vision algorithm categorizes them even if you don't utilize the Google Vision API to scale image detection and classification because the tool offers an intriguing look into what Google's image-related algorithms are capable of. 

This tool showcases Google's machine learning and artificial intelligence (AI) picture comprehension technologies. 

It is a component of Google's Cloud Vision API family, which gives apps and websites access to vision machine learning models. 

Does Cloud Vision Tool Reflect Google’s Algorithm? 

This is not a ranking algorithm; it is only a machine learning model. 

Therefore, expecting this tool to provide information regarding Google's image ranking system is unlikely. 

It is a fantastic tool for figuring out how Google's AI and machine learning algorithms can comprehend photos, though, and it will provide some insight into how sophisticated current vision-related algorithms are. 

This tool's information can be used to determine how a computer would interpret an image's subject matter and perhaps to get a sense of how well the image corresponds with the webpage's general theme.

Why Is An Image Classification Tool Useful? 

Due to the numerous ways that Google surfaces webpage information, images can significantly impact search visibility and click-through rates (CTR). 

Images are used by potential site visitors who are conducting research to find the appropriate material. 

To immediately convey that a webpage is relevant to what a person is searching for, beautiful graphics that are pertinent to search queries may be useful in some instances. 

The Google Vision tool gives users a means to comprehend how an algorithm might interpret and categorize an image based on its contents.

Google’s guidelines for image SEO recommend: 

Users prefer crisp, clear photos over blurry, indistinct ones. Additionally, people find clear photos in the result thumbnail to be more enticing, which increases the likelihood of receiving user traffic. 

A hint that potential site visitors may be experiencing the same problems and choosing not to visit the site is if the Vision tool is having trouble determining what the image is about.

What Is The Google Image Tool? 

It serves as a demonstration of Google's Cloud Vision API. 

The machine learning technology may be accessed by apps and websites using the Cloud Vision API, which offers scalable image analysis services. 

You can upload a picture to the standalone program and receive information about how Google's machine learning algorithm perceives it. 

The following is an example of how the service might be applied: 

"Cloud Vision enables developers to effortlessly incorporate optical character recognition (OCR), face and landmark identification, image labeling, and tagging of explicit information into apps." 

These are five ways Google’s image analysis tools classify uploaded images: 

• Faces. 

• Objects. 

• Labels. 

• Properties. 

• Safe Search. 


The emotion conveyed by the photograph is examined in the "faces" tab. 

This outcome's accuracy is largely correct. 

The individual in the image below is supposedly bewildered, yet confusion isn't truly an emotion. 

With a confidence level of 96%, the AI classifies the facial expression as astonished. 

Images for the author's July 2022 composite image came from the Google Cloud Vision API and Shutterstock/Cast Of Thousands.


The “objects” tab shows what objects are in the image, like glasses, person, etc. 

The tool accurately identifies horses and people. 

Composite image created by author, July 2022; images sourced from Google Cloud Vision API and Shutterstock/Lukas Gojda 


Glasses, a person, and other items are displayed in the "objects" tab. 

The device correctly distinguishes between people and horses. 

Images used in the author's July 2022 composite image came from the Google Cloud Vision API and Shutterstock/Lukas Gojda. 


This tool's purpose may not be immediately apparent upon first glance, and it might even appear to be fairly pointless. 

However, in actuality, an image's colors can be crucial, especially if it's a featured image. 

Wide color spectrums in images can be a sign of a poorly chosen image with an inflated size, therefore be on the lookout for them. 

Photos with a darker color range typically result in larger image files, which is another important observation regarding images and color.

When it comes to SEO, the Property section may be helpful for locating photos that need to be replaced with smaller versions on a website as a whole. 

Featured photographs with muted or even grayscale color ranges may also be something to watch out for since these images don't typically stand out on social media, Google Discover, or Google News. 

For instance, since they draw the attention more effectively than photos that are muted and blend into the backdrop, featured images that are vibrant can be quickly scanned and may even have a greater click-through rate (CTR) when displayed in the search results or in Google Discover. 

Although there are many factors that might influence an image's CTR performance, this offers a technique to speed up the auditing process for all of a website's images. 

When eBay looked at product photographs and CTR, they found that pictures with lighter backgrounds typically had better CTRs. 

The study by eBay found: 

In this study, we discovered that product visual attributes could affect users' search behavior. 

We discover that several image attributes are correlated with click-through rates (CTR) in product search engines and that these features can be used to estimate CTR for apps that use shopping search. 

This study may encourage vendors to provide more attractive photos of the goods they offer for sale. 

Anecdotally, the use of vivid colors for featured images might be helpful for increasing the CTR for sites that depend on traffic from Google Discover and Google News. 

Obviously, there are many factors that impact the CTR from Google Discover and Google News. But an image that stands out from the others may be helpful. 

So for that reason, using the Vision tool to understand the colors used can be helpful for a scaled audit of images.

Safe Search 

Safe Search shows how the image ranks for unsafe content. The descriptions of potentially unsafe images are as follows: 

• Adult. 

• Spoof. 

• Medical. 

• Violence. 

• Racy. 

Google search has filters that check a webpage for potentially harmful or inappropriate content. 

As a result, the tool's Safe Search section is critical because if an image unintentionally triggers a safe search filter, the webpage may fail to rank for potential site visitors looking for the content on the webpage.

The above screenshot shows the evaluation of a photo of racehorses on a race track. The tool accurately identifies 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 in photographs. 

The Vision tool can correctly read the text in the image below: 

Author created a composite image in July 2022 using images from Google Cloud Vision API and Shutterstock/Melissa King. 

As demonstrated above, Google has the ability (via Optical Character Recognition, a.k.a. OCR) to read words in images. 

However, this does not imply that Google uses OCR for search ranking purposes. 

The truth is that Google recommends using words around images to help it understand what an image is about, and it's possible that even for images with text, Google still relies on the words surrounding the image to understand what the image is about and relevant for.

Google's image guidelines SEO emphasizes the importance of using words to provide context for images. 

"By including more context around images, results can become much more useful, resulting in higher quality traffic to your site." 

Place images near relevant text whenever possible. 

...Google extracts information about the image's subject matter from the page's content... 

...Google understands the subject matter of the image by using alt text, computer vision algorithms, and the page's content." 

Google's documentation makes it abundantly clear that Google relies on the context of the text surrounding images to determine what the image is about. 


Google's Vision AI tool allows a publisher to connect to Google's Vision AI via an API and use it to scale image classification and extract data for use on the site. 

However, it also shows how far image labeling, annotation, and optical character recognition algorithms have progressed. 

Upload an image to see how it is classified and whether a machine sees it the same way you do.


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