Auto Quality powered by ML (Machine Learning)

By default, Optimole compresses the images on your website, and it uses Machine Learning algorithms to detect how to get the smallest possible size with minimum perceived quality losses. In case you feel this automatic process doesn't suit your needs, it is possible to disable it and manually set the level of compression/image quality you're okay with. You need to enable Custom compression mode and modify the Machine Learning per your needs.

🔌 Configure the Feature

To configure this feature, navigate to WP Dashboard > Optimole.

1: Open the Settings tab.

2: Expand the Advanced accordion and open the Compression panel.

3: Use the toggle to enable Custom mode.

4: Use the toggle to enable/disable Auto Quality powered by ML feature.

🚀 User Site and Image Impact

At the bottom, a dial lets you toggle through the compression levels. As soon as you move that dial in any direction, Optimole will show you a preview based on an image taken from your site's media library.

A higher compression might result in a small loss of image quality. Selecting the auto level will let Optimole choose the minimum size with no loss in the quality of your picture.

You can determine the image quality by inspecting the image URL and looking for the q:<value> parameter. If the feature is toggled on, the parameter becomes q:mauto.

If not, according to the quality level that you added, it will display that value, e.g. q:75.

🔄 Benefits and Trade-offs

Benefits

Efficiency - ML automation saves time by optimizing image quality without manual adjustments, simplifying the process.
Hands-Off management - once the feature is enabled, the ML algorithms will handle image quality optimization without the need to micromanage individual images.
Optimized image quality - ML algorithms predict the optimal quality for your images. This means that the images are compressed to the smallest size possible while maintaining an acceptable level of quality.

Trade-offs

Loss of manual control - by relying on automated ML algorithms, you give up the ability to manually control the quality of each image.
Quality perception variability - automated algorithms might not always perfectly match human judgment.

🧩 Use Cases

The feature can be very advantageous for multiple use cases, such as:

E-commerce Websites
Blogs and Content Websites
Portfolio Websites
News Website
Business Websites
Mobile Apps
Forums and Community Websites
Educational Platforms
Non-Profit and Charity Websites
Travel and Tourism Websites

🗂Useful Resources

You may find useful these guides:

Still looking for an answer? Contact us!

Enable the Feature	User Site and Image Impact
Use Cases	Benefits and Trade-offs
Useful Resources