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Enhance creative workflow with AI-driven image manipulation based on spatial conditions for unique visual effects.
The RunningHub_Omini_Spatial node is designed to enhance your creative workflow by providing a sophisticated method for image manipulation based on spatial conditions. This node leverages advanced AI techniques to process a reference image and apply transformations guided by a user-defined prompt and specific condition types. Its primary goal is to offer a flexible and powerful tool for artists to explore various visual effects, such as canny edge detection, depth mapping, coloring, and deblurring. By integrating these capabilities, the node allows for the generation of unique and compelling images, making it an invaluable asset for AI artists looking to push the boundaries of their creative projects.
The ref_image
parameter is the input image that serves as the basis for the node's processing. It is crucial as it provides the visual content that will be transformed according to the specified conditions and prompt. The quality and characteristics of this image can significantly influence the final output, making it essential to choose an image that aligns with your creative vision.
The prompt
parameter is a string input that allows you to guide the transformation process with descriptive text. This parameter supports multiline input, enabling you to provide detailed instructions or creative ideas that the node will interpret and apply to the reference image. The default value is an empty string, and the prompt's content can greatly affect the artistic direction and style of the output image.
The condition_type
parameter specifies the type of transformation to be applied to the reference image. It offers four options: "canny," "depth," "coloring," and "deblurring." Each option represents a different visual effect, allowing you to tailor the image processing to your specific needs. Selecting the appropriate condition type is crucial for achieving the desired artistic effect.
The seed
parameter is an integer that determines the randomness in the image generation process. It has a default value of 0 and can range from 0 to 0xffffffffffffffff. By setting a specific seed, you can ensure reproducibility of the results, which is particularly useful for iterative design processes or when you want to recreate a specific effect.
The image
output parameter is the final processed image resulting from the node's operations. This image reflects the transformations applied based on the reference image, prompt, and condition type. It is the primary output of the node and represents the culmination of the creative and technical inputs provided. The output image can be used for further artistic exploration or as a final piece in your creative projects.
condition_type
settings to explore a variety of visual effects and find the one that best suits your artistic vision.seed
parameter to maintain consistency across multiple runs, allowing you to fine-tune your results and achieve the perfect output.ref_image
is in a compatible format such as JPEG or PNG.condition_type
is one of the supported options: "canny," "depth," "coloring," or "deblurring."RunComfy is the premier ComfyUI platform, offering ComfyUI online environment and services, along with ComfyUI workflows featuring stunning visuals. RunComfy also provides AI Playground, enabling artists to harness the latest AI tools to create incredible art.