ComfyUI Node: Latent Frequency Enhancer (lrzjason)

Latent Frequency Enhancer (lrzjason):

The LatentFrequencyEnhancer_lrzjason node is designed to enhance the high-frequency components of latent images during the sampling process. This node is particularly useful for AI artists who want to improve the detail and sharpness of generated images by focusing on the high-frequency details that often contribute to the perceived clarity and texture of an image. By applying a frequency-based enhancement technique, this node separates the latent image into low and high-frequency components using a Gaussian filter in the frequency domain. The high-frequency components are then selectively enhanced, allowing for a more detailed and refined output. This process is beneficial for tasks that require high precision and detail, such as generating photorealistic images or enhancing textures in digital art.

Latent Frequency Enhancer (lrzjason) Input Parameters:

latent

The latent parameter represents the input latent image that will undergo frequency enhancement. It is a tensor containing the image data in a latent space format, which is typically used in generative models. This parameter is crucial as it serves as the base image from which high-frequency details will be enhanced.

high_freq_mult

The high_freq_mult parameter controls the multiplication factor applied to the high-frequency components of the latent image. By adjusting this value, you can increase or decrease the emphasis on high-frequency details. The default value is 1.05, with no specified minimum or maximum, allowing for flexible enhancement based on artistic needs.

sigma

The sigma parameter defines the standard deviation of the Gaussian filter used for frequency separation. It determines the cutoff frequency between low and high-frequency components. A smaller sigma results in a sharper separation, while a larger sigma provides a smoother transition. The default value is 5.0, with a range from 0.01 to 20.0.

denoise_threshold

The denoise_threshold parameter sets the threshold for noise reduction in the high-frequency components. It helps in minimizing unwanted noise that might be amplified during the enhancement process. The default value is 0.05, with a range from 0.0 to 1.0, allowing for precise control over noise levels.

mask_hardness

The mask_hardness parameter controls the transition sharpness of the mask used in the enhancement process. A higher value results in a harder transition, while a lower value provides a softer transition. The default value is 2.0, with a range from 0.01 to 100.0, offering flexibility in mask application.

hf_pre_blur_sigma

The hf_pre_blur_sigma parameter specifies the amount of pre-blurring applied to the high-frequency components before enhancement. This helps in grouping noise and reducing artifacts. The default value is 0.5, with a range from 0.0 to 1.0, allowing for fine-tuning of the pre-blur effect.

Latent Frequency Enhancer (lrzjason) Output Parameters:

enhanced_latent

The enhanced_latent output is the processed latent image with enhanced high-frequency details. This output retains the original structure of the input latent image but with improved clarity and detail, making it suitable for further processing or direct use in image generation tasks.

mask_preview

The mask_preview output provides a visual representation of the mask used during the enhancement process. It is a grayscale image that highlights the areas where high-frequency enhancement was applied, allowing users to understand the impact of the enhancement on different regions of the image.

Latent Frequency Enhancer (lrzjason) Usage Tips:

• Experiment with the high_freq_mult parameter to find the right balance of detail enhancement for your specific artistic needs. A higher value can bring out more details but may also introduce noise.
• Adjust the sigma parameter to control the separation between low and high frequencies. This can help in achieving the desired level of detail and smoothness in the final image.

Latent Frequency Enhancer (lrzjason) Common Errors and Solutions:

"Invalid latent input format"

• Explanation: This error occurs when the input latent image does not conform to the expected tensor format.
• Solution: Ensure that the input latent image is correctly formatted as a tensor with the appropriate dimensions and data type.

"High frequency multiplier out of range"

• Explanation: This error indicates that the high_freq_mult parameter is set to a value that is not supported.
• Solution: Adjust the high_freq_mult parameter to a reasonable value, typically around the default of 1.05, to ensure proper enhancement without introducing excessive noise.