ComfyUI Node: ⭐ Star Model Latent Upscaler

⭐ Star Model Latent Upscaler:

The Starupscale node is designed to enhance the resolution of images by utilizing advanced upscaling models. It serves as a powerful tool for AI artists who wish to improve the quality and detail of their images without losing the original essence. By leveraging sophisticated algorithms, this node can upscale images to a higher resolution, making them suitable for various applications such as printing, digital art, and more. The node ensures that the upscaled images maintain their visual integrity by carefully adjusting the size and applying appropriate interpolation methods. This process is particularly beneficial for artists looking to refine their work and achieve a polished, high-quality output.

⭐ Star Model Latent Upscaler Input Parameters:

VAE_OUT

This parameter specifies the Variational Autoencoder (VAE) model to be used for processing. It determines the initial model setup for the upscaling process. If set to "Default," the node will use a standard configuration. Otherwise, it can be set to specific models like "taesd," "taesdxl," "taesd3," or "taef1," which are tailored for different upscaling needs. The choice of VAE model can significantly impact the quality and characteristics of the output image.

VAE_Device

This parameter defines the device on which the VAE model will be executed, such as a CPU or GPU. The device selection can affect the processing speed and efficiency of the upscaling operation. For optimal performance, especially with large images or complex models, using a GPU is recommended.

UPSCALE_MODEL

This parameter indicates the specific upscaling model to be used. If set to "Default," no specialized model is applied. Otherwise, it allows the selection of a custom model that can enhance the upscaling process by providing more detailed and refined results. The choice of model can influence the final image quality and should be selected based on the desired output characteristics.

OUTPUT_LONGEST_SIDE

This parameter sets the target size for the longest side of the output image. It ensures that the upscaled image is resized appropriately while maintaining its aspect ratio. The value must be divisible by 64, with a minimum size of 64, to ensure compatibility with the upscaling process. Adjusting this parameter allows for control over the final image dimensions.

INTERPOLATION_MODE

This parameter specifies the interpolation method used during the resizing process. It determines how pixel values are calculated when scaling the image, affecting the smoothness and quality of the output. The mode is converted to uppercase and spaces are replaced with underscores to match the available options in the InterpolationMode class. Choosing the right interpolation mode can enhance the visual appeal of the upscaled image.

VAE_INPUT

This optional parameter allows for the input of a pre-processed VAE model. When provided, it can be used in conjunction with a latent input to decode and upscale the image. This parameter is useful for advanced users who wish to integrate custom VAE models into the upscaling workflow.

LATENT_INPUT

This optional parameter accepts a latent input that can be decoded using the VAE model. It is used when both VAE and latent inputs are connected, allowing for a more controlled and precise upscaling process. This parameter is ideal for users who want to experiment with latent space manipulations.

IMAGE

This optional parameter allows for the direct input of an image to be upscaled. If no VAE or latent inputs are provided, the node will use this image as the basis for upscaling. This parameter is straightforward and suitable for users who want to quickly enhance the resolution of an existing image.

⭐ Star Model Latent Upscaler Output Parameters:

OUTPUT VAE

This output provides the processed VAE model, which can be used for further image manipulations or analysis. It represents the encoded state of the upscaled image and is valuable for users who wish to explore the latent space or apply additional transformations.

IMAGE

This output delivers the final upscaled image, ready for use in various applications. It reflects the enhanced resolution and quality achieved through the upscaling process, making it suitable for printing, digital art, and other creative endeavors.

LATENT

This output offers the latent representation of the upscaled image, which can be used for further processing or exploration. It provides insights into the underlying structure of the image and is useful for advanced users interested in latent space analysis.

⭐ Star Model Latent Upscaler Usage Tips:

• Ensure that the OUTPUT_LONGEST_SIDE is set to a value divisible by 64 to avoid errors and ensure optimal upscaling results.
• Experiment with different UPSCALE_MODEL options to find the one that best suits your artistic style and desired output quality.
• Use a GPU for the VAE_Device to significantly speed up the processing time, especially when working with large images or complex models.

⭐ Star Model Latent Upscaler Common Errors and Solutions:

"Output image is not a torch.Tensor"

• Explanation: This error occurs when the output image is not correctly initialized or processed as a tensor.
• Solution: Ensure that the input parameters are correctly set and that the image is properly loaded or initialized before processing.

"OUTPUT_LONGEST_SIDE must be divisible by 64"

• Explanation: The specified output size is not compatible with the upscaling requirements.
• Solution: Adjust the OUTPUT_LONGEST_SIDE parameter to a value that is divisible by 64 to ensure proper resizing.

"Invalid INTERPOLATION_MODE"

• Explanation: The specified interpolation mode is not recognized or incorrectly formatted.
• Solution: Verify that the INTERPOLATION_MODE is correctly formatted in uppercase with underscores and matches one of the available options in the InterpolationMode class.