ComfyUI Node: Omini Kontext Image Scale

Omini Kontext Image Scale:

The OminiKontextImageScale node is designed to optimize image resolutions for use within the Omini Kontext framework. This node automatically scales images to a set of predefined resolutions that are considered optimal for processing within the Kontext environment. By adjusting images to these specific dimensions, the node ensures that they are compatible with the system's requirements, potentially enhancing the performance and quality of subsequent image processing tasks. The node leverages a sophisticated scaling method that maintains the aspect ratio of the original image while selecting the best matching resolution from a list of preferred options. This process is crucial for ensuring that images are processed efficiently and effectively, making the OminiKontextImageScale node an essential tool for users looking to integrate their images seamlessly into the Omini Kontext pipeline.

Omini Kontext Image Scale Input Parameters:

image

The image parameter is the primary input for the OminiKontextImageScale node. It accepts an image in the form of a tensor with dimensions [B, H, W, C], where B is the batch size, H is the height, W is the width, and C is the number of channels. This parameter is crucial as it provides the node with the image data that needs to be scaled. The node uses the dimensions of the input image to calculate the aspect ratio, which is then used to determine the best matching resolution from the predefined list. This ensures that the image is scaled appropriately while maintaining its original aspect ratio.

Omini Kontext Image Scale Output Parameters:

IMAGE

The output of the OminiKontextImageScale node is an IMAGE, which is the scaled version of the input image. This output retains the original image's content but is resized to one of the optimal resolutions specified by the Omini Kontext framework. The scaling process ensures that the image is compatible with the system's requirements, facilitating further processing within the pipeline. The output image maintains the same batch size and number of channels as the input, ensuring consistency and ease of integration into subsequent processing steps.

Omini Kontext Image Scale Usage Tips:

• Ensure that the input image is in the correct format and dimensions before passing it to the node to avoid any processing errors.
• Utilize the node when preparing images for tasks within the Omini Kontext framework to ensure optimal performance and compatibility.

Omini Kontext Image Scale Common Errors and Solutions:

Image shape mismatch

• Explanation: This error occurs when the input image does not have the expected dimensions or format.
• Solution: Verify that the input image is a tensor with dimensions [B, H, W, C] and adjust the format if necessary.

Unsupported image type

• Explanation: The node may not support certain image types or formats.
• Solution: Convert the image to a supported format, such as a tensor, before inputting it into the node.