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Process and output grid data for AI artists, facilitating grid management and visualization in AI art applications.
The GridOutput node is designed to process and output grid data in a structured format, making it easier to visualize and manipulate grid-based information. This node is particularly useful for AI artists who need to handle complex grid layouts and ensure that their dimensions and padding are correctly applied. By converting grid data into a more manageable format, GridOutput helps streamline the workflow, allowing for more efficient and accurate grid management. The node takes in grid data, applies specified padding, and outputs the processed grids along with their labels and a tensor representation of the image, facilitating further use in various AI art applications.
This parameter expects a JSON string containing the grid data. The grid data should include the dimensions and individual grid elements that need to be processed. The grids parameter is essential as it provides the raw data that the node will process and format.
This parameter specifies the padding to be applied to each grid element. Padding helps in adjusting the spacing around the grid elements, ensuring they are correctly aligned and spaced within the overall grid layout. The padding value should be provided as a list, with the first element being the padding amount.
This optional parameter allows you to specify the width of the output image. If not provided, the width will be determined based on the input grid data. Setting the width can help in standardizing the output dimensions, especially when working with multiple grids.
Similar to the width parameter, this optional parameter allows you to specify the height of the output image. If not provided, the height will be determined based on the input grid data. Specifying the height ensures consistency in the output dimensions.
This output parameter contains the processed grid data with the applied padding. Each grid element is adjusted according to the specified padding, ensuring they are correctly aligned and spaced.
This output parameter provides the labels associated with each grid element. Labels help in identifying and categorizing the grid elements, making it easier to manage and reference them in subsequent processes.
This output parameter is a tensor representation of the image created from the processed grid data. The tensor format is useful for further processing and manipulation within AI art applications, allowing for seamless integration with other nodes and tools.
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