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Transform images into pixelated art with customizable scale and intensity using advanced image processing techniques.
The FL_ImagePixelator node is designed to transform your images into pixelated art, providing a unique and creative effect that can add a retro or stylized look to your visuals. This node leverages advanced image processing techniques to apply pixelation, allowing you to control the scale and intensity of the effect. By adjusting parameters such as scale factor, kernel size, and modulation, you can achieve a wide range of pixelation styles, from subtle to highly pronounced. The node supports both PIL images and PyTorch tensors, making it versatile for different workflows. Whether you're looking to create pixel art, reduce image detail for artistic purposes, or simply experiment with new visual styles, the FL_ImagePixelator offers a powerful and flexible toolset to enhance your creative projects.
This parameter accepts the image you want to pixelate. The image can be in the form of a PIL image or a PyTorch tensor. The node will process the image based on the provided scale factor, kernel size, and modulation settings.
The scale factor determines the degree of pixelation applied to the image. A lower scale factor results in finer pixelation, while a higher scale factor produces a more pronounced pixelated effect. The default value is 0.0500, with a minimum of 0.0100 and a maximum of 0.2000, adjustable in steps of 0.0100.
The kernel size defines the size of the kernel used in the image processing step. It affects the smoothing and blending of the pixelated image. The default value is 3, with a maximum of 10, adjustable in steps of 1.
The modulation parameter allows you to introduce a dynamic variation in the scale factor, creating a modulated pixelation effect. This can add an interesting visual rhythm to the pixelation. The default value is 0.0, with a minimum of 0.0 and a maximum of 1.0, adjustable in steps of 0.01.
The output parameter is the pixelated image, which retains the same format as the input (either a PIL image or a PyTorch tensor). The pixelated image reflects the applied scale factor, kernel size, and modulation settings, providing a transformed version of the original image with the desired pixelation effect.
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