{"id":29290,"date":"2023-06-09T07:00:00","date_gmt":"2023-06-09T14:00:00","guid":{"rendered":"https:\/\/cloudinary.com\/blog\/?p=29290"},"modified":"2025-11-17T05:46:12","modified_gmt":"2025-11-17T13:46:12","slug":"computer-vision-image-analysis-e-commerce-website","status":"publish","type":"post","link":"https:\/\/cloudinary.com\/blog\/computer-vision-image-analysis-e-commerce-website","title":{"rendered":"Computer Vision Image Analysis for Your E-commerce Website"},"content":{"rendered":"\n

A successful e-commerce website or app uses images that enhance the buyer’s experience. Appealing images can spell the difference between a buyer doing a quick perusal, or staying on your site for hours.<\/p>\n\n\n\n

As such, you might be tempted to spend time editing each image. At face value, it seems like you’ll need a human to do the job \u2014 to actually look at the images and make decisions about how to handle them, like which shade of purple would make the best background. However, doing this manually can quickly drain your resources, and computer vision can do these types of tasks just as well. <\/p>\n\n\n\n

If you work with a lot of images simultaneously, or if you welcome user-generated content<\/a> (UGC) on your website or app, computer vision image analysis can help make sure your site looks its very best.<\/p>\n\n\n\n

What\u2019s Computer Vision Image Analysis?<\/h2>\n\n\n\n

Computer vision is a field of artificial intelligence (AI) that enables computers to \u201cobserve\u201d and \u201cunderstand\u201d the content of photos and videos. Image analysis means extracting meaningful information from that content. As a result, using computer vision image analysis gives insight into how to automate actions. <\/p>\n\n\n\n

If you manage images in bulk, you can use computer vision image analysis for your e-commerce website to automatically crop, size, and place each image in a way that looks natural.<\/p>\n\n\n\n

For example, if you\u2019re building an e-commerce app for an appliance retailer, computer vision can detect which appliance appears in the images. You can then easily write an app that automatically handles the image.<\/p>\n\n\n\n

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Sink<\/figcaption><\/figure>\n\n\n\n
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Microwave<\/figcaption><\/figure>\n\n\n\n
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Refrigerator<\/figcaption><\/figure>\n<\/figure>\n\n\n\n

How Can I Use Computer Vision in My App?<\/h2>\n\n\n\n

With Cloudinary<\/a>, a platform that empowers you to manage your media files end-to-end.<\/p>\n\n\n\n

When you upload images, Cloudinary can use computer vision to return lots of information, including whether or not the image contains adult content, which objects are detected; the coordinates of any faces, the width, and height; the predominant colors; any detectable text… and so much more.<\/p>\n\n\n\n

Use that information to make decisions about how to handle your images. For example, don’t display images that have adult content, give the images an automatically generated title that reflects the recognized objects, place an overlay on each person, group images on your sites according to color scheme, or create a border around the images using predominant colors.<\/p>\n\n\n\n

The possibilities are endless!<\/p>\n\n\n\n

Cloudinary Computer Vision Demo App<\/h2>\n\n\n\n

This demo shows how you can use Cloudinary’s computer vision to handle your images. You can use it as a starting point for embedding Cloudinary’s computer vision and image analysis in your e-commerce website.<\/p>\n\n\n\n

In this demo, you\u2019ll upload up to three images of your choice. Then, Cloudinary will automatically use computer vision to analyze them and transform them accordingly. You\u2019ll also see a description of your images based on computer vision.<\/p>\n\n\n\n

Go to GitHub<\/a> to try it out.<\/p>\n\n\n\n

\n \n \n <\/a>\n<\/div> \n\n\n\n

Upload and Analyze Images in Your Own Product Environment<\/h3>\n\n\n\n

You can replicate all of the functionality described in this blog on your own product environment. Just sign up<\/a> for your free Cloudinary account and save the cloud name and API Environment variable from your credentials<\/a>. <\/p>\n\n\n\n

Then, either copy and paste the source code<\/a> onto your own environment.\u00a0<\/p>\n\n\n

Note:<\/strong>

Don\u2019t forget to set your environment variable and configure the Upload widget in the index.html<\/code> file with your cloud name.<\/p>\n