ComfyUI Node: 🔍 CR Upscale Image

🔍 CR Upscale Image:

The CR Upscale Image node is designed to enhance the resolution of your images using advanced upscaling models. This node is particularly useful for AI artists who want to improve the quality and detail of their images without losing the original essence. By leveraging sophisticated upscaling techniques, the node can increase the image size while maintaining or even enhancing the visual quality. It supports various resampling methods and allows for multiple configurations to suit different artistic needs. The node also provides an option to rescale the image to a specific width, ensuring flexibility and control over the final output.

🔍 CR Upscale Image Input Parameters:

image

This parameter represents the input image that you want to upscale. It should be provided in a format compatible with the node's processing capabilities.

upscale_model

This parameter specifies the model to be used for upscaling the image. Different models may offer varying levels of detail and quality, so choosing the right model is crucial for achieving the desired results.

rounding_modulus

This parameter determines the rounding modulus used during the resizing process. It helps in maintaining the aspect ratio and ensuring that the dimensions are rounded to the nearest multiple of the specified modulus. The default value is 8.

loops

This parameter defines the number of times the upscaling process should be repeated. Increasing the number of loops can enhance the image quality but may also increase the processing time. The default value is 1.

mode

This parameter specifies the mode of resizing. The default mode is "rescale," which adjusts the image size based on the rescale factor.

supersample

This parameter indicates whether supersampling should be applied during the upscaling process. Supersampling can improve the image quality by reducing aliasing effects. The default value is 'true'.

resampling_method

This parameter determines the resampling method to be used during the resizing process. Options include "nearest-exact," "bilinear," "area," "bicubic," and "lanczos." The default method is "lanczos," which is known for its high-quality results.

rescale_factor

This parameter specifies the factor by which the image should be rescaled. A higher rescale factor will result in a larger image. The default value is 2.

resize_width

This parameter allows you to set a specific width for the resized image. It ensures that the final output matches the desired dimensions. The default value is 1024.

🔍 CR Upscale Image Output Parameters:

images_out

This parameter represents the upscaled image(s) produced by the node. The output is a tensor containing the enhanced image data, ready for further processing or display.

show_help

This parameter provides a URL to the help documentation for the CR Upscale Image node. It is useful for users who need additional guidance or information about the node's functionality.

🔍 CR Upscale Image Usage Tips:

• Experiment with different upscale models to find the one that best suits your artistic style and the specific details of your image.
• Use the rescale_factor parameter to control the level of upscaling. A higher factor will produce a larger image but may require more processing time.
• Enable supersampling to reduce aliasing and improve the overall quality of the upscaled image.
• Choose the appropriate resampling_method based on your quality requirements. The "lanczos" method is generally recommended for high-quality results.

🔍 CR Upscale Image Common Errors and Solutions:

Model loading error

• Explanation: This error occurs when the specified upscale model cannot be loaded.
• Solution: Ensure that the model file exists and is correctly specified in the upscale_model parameter.

Image size mismatch

• Explanation: This error happens when the dimensions of the upscaled image do not match the expected size.
• Solution: Check the rescale_factor and resize_width parameters to ensure they are set correctly.

Unsupported resampling method

• Explanation: This error occurs when an invalid resampling method is specified.
• Solution: Verify that the resampling_method parameter is set to one of the supported methods: "nearest-exact," "bilinear," "area," "bicubic," or "lanczos."