Img2Color Palette Extractor is a specialized tool designed for ComfyUI that enables users to extract dominant and complementary color palettes from images. It also converts these colors into English names that are suitable for use in text-to-image (txt2img) prompts.
- Utilizes KMeans clustering to identify and extract the primary colors from an image.
- Leverages the
webcolorsandcolornamerlibraries to provide the closest matching color names from various established color naming systems. - Features a
get_complementaryoption that allows users to retrieve complementary colors as needed.
Context
This tool serves as a ComfyUI node that facilitates the extraction of color palettes from images, enhancing the user’s ability to incorporate visually appealing color schemes into their projects. Its primary purpose is to streamline the process of obtaining both dominant and complementary colors, which can be particularly useful for artists and designers working with AI-generated content.
Key Features & Benefits
The Img2Color Palette Extractor provides practical features that allow users to easily identify and name colors extracted from images. By using KMeans clustering, it effectively isolates the most prominent colors, making it easier for users to select palettes that enhance their visual outputs. The inclusion of English color names simplifies the integration of these colors into prompts, ensuring that users can communicate their desired aesthetics clearly.
Advanced Functionalities
One of the advanced capabilities of this tool is its ability to toggle between extracting dominant colors and complementary colors. This feature allows users to explore a broader range of color relationships, enabling them to create more dynamic and visually interesting compositions. Additionally, the use of multiple color naming systems ensures that users have access to a diverse array of color names, accommodating different artistic styles and preferences.
Practical Benefits
By incorporating the Img2Color Palette Extractor into their workflow, users can significantly enhance their control over color selection and application in ComfyUI. This tool not only saves time by automating the color extraction process but also improves the overall quality of visual outputs by providing precise color information. As a result, users can achieve more cohesive and aesthetically pleasing results in their AI art projects.
Credits/Acknowledgments
The tool is based on contributions from various authors, with dependencies on libraries such as colornamer, scikit_learn, and webcolors. The project is open-source, allowing for community involvement and collaboration.