Edition Methods

Apply a blur effect to an image. Blurring an image can be useful for various purposes, such as anonymizing sensitive information, creating a soft-focus effect, loader skeletons, etc.

Blurring an image depends on a factor sigma that determines the intensity of the blur effect. The higher the value of sigma, the more intense the blur effect will be. This value represents the standard deviation of the Gaussian kernel used to apply the blur effect.

Adjust the brightness, saturation, and hue of an image.

Brightness is one of the three properties of color, along with hue and saturation. It refers to the amount of light in an image, with a high brightness making the image lighter and a low brightness making the image darker.

On the other hand, saturation refers to the intensity of the colors in an image. A high saturation value will make the colors more vivid, while a low saturation value will make the colors more muted.

Finally, hue refers to the color of the image. It is represented as a circular color space, with red, green, and blue forming the primary colors.

Remove the background from an image using a pre-trained model.

The removeBackground method uses a pre-trained model to detect the foreground object in an image and remove the background. The method is useful for creating images with transparent backgrounds or isolating objects in an image.

The method returns a new image with the background removed.