This tool implements the Fast Fourier Transform (FFT) functionality within ComfyUI, mimicking features found in Photoshop's FFT plugin. It enhances the original code by introducing high-pass, low-pass, and band-pass filters, providing users with greater flexibility for image adjustments.
- Offers low-pass filtering to retain frequencies below a specified cutoff, enabling smoother image processing.
- Includes high-pass filtering to preserve frequencies above a defined cutoff, facilitating the enhancement of image details.
- Features band-pass filtering to allow only a specific range of frequencies, which can be beneficial for targeted image corrections.
Context
The ComfyUI_LG_FFT tool is designed to integrate FFT capabilities into ComfyUI, allowing users to manipulate images through frequency domain processing. Its primary aim is to enhance image editing workflows by providing advanced filtering options that can improve the quality of visual outputs.
Key Features & Benefits
The tool's key features include low-pass, high-pass, and band-pass filters, each serving distinct purposes in image processing. Low-pass filters are particularly useful for reducing noise and smoothing images, while high-pass filters help in sharpening and enhancing fine details. Band-pass filters allow for selective frequency manipulation, giving users the ability to focus on specific aspects of an image.
Advanced Functionalities
In addition to basic filtering, the tool supports mask inversion, which adds another layer of flexibility in how users can apply filters. This feature allows for more complex adjustments and can be particularly useful in scenarios where specific areas of an image need to be enhanced or suppressed.
Practical Benefits
By incorporating this tool into their workflow, users can achieve more precise control over image quality and effects in ComfyUI. The ability to manipulate different frequency ranges not only enhances the visual appeal of images but also streamlines the editing process, making it more efficient and effective.
Credits/Acknowledgments
This tool builds upon foundational work from the original author, fssorc, whose contributions to the FFT node are acknowledged and appreciated. The repository is open-source, promoting collaboration and further development within the community.