ComfyUI Node: Inject Noise To Latent

Inject Noise To Latent:

The InjectNoiseToLatent node is designed to introduce noise into latent representations, which can be particularly useful for AI artists looking to add variability and randomness to their generated images. This node allows you to blend noise with latent samples, control the strength of the noise, normalize the output, and even apply a mask to selectively inject noise into specific regions. By using this node, you can achieve more diverse and creative outputs, enhancing the artistic quality of your AI-generated content.

Inject Noise To Latent Input Parameters:

latents

This parameter represents the latent samples to which noise will be injected. It is a dictionary containing the key "samples" which holds the actual latent data. The shape of this data must match the shape of the noise parameter.

strength

This parameter controls the intensity of the noise being injected into the latent samples. A higher value results in stronger noise influence. The default value is not specified, but it typically ranges from 0.0 to 1.0.

noise

This parameter represents the noise samples to be injected into the latent samples. It is a dictionary containing the key "samples" which holds the actual noise data. The shape of this data must match the shape of the latents parameter.

normalize

A boolean parameter that, when set to True, normalizes the noised latent samples to have a standard deviation of 1. This can help in maintaining consistent output quality.

average

A boolean parameter that, when set to True, averages the latent samples and noise instead of adding them. This can create a more subtle noise effect.

mix_randn_amount

This parameter controls the amount of random noise to mix with the injected noise. It ranges from 0.0 to 1.0, with 0.0 meaning no random noise is added and 1.0 meaning only random noise is used. The default value is 0.

seed

An optional parameter that sets the seed for random noise generation. This ensures reproducibility of the noise pattern when the same seed is used.

mask

An optional parameter that allows you to apply a mask to the latent samples. The mask determines which parts of the latent samples will be affected by the noise. The mask is resized to match the dimensions of the latent samples.

Inject Noise To Latent Output Parameters:

samples

This output parameter is a dictionary containing the key "samples" which holds the latent samples with the injected noise. The shape and type of this data match the input latent samples, but with the added noise effects.

Inject Noise To Latent Usage Tips:

• To achieve subtle noise effects, set the average parameter to True and use a low strength value.
• Use the normalize parameter to maintain consistent output quality, especially when working with high noise strengths.
• Apply a mask to selectively inject noise into specific regions of the latent samples, allowing for more controlled and artistic effects.
• Experiment with different mix_randn_amount values to blend structured noise with random noise for unique results.

Inject Noise To Latent Common Errors and Solutions:

Inject Noise To Latent: Latent and noise must have the same shape

• Explanation: This error occurs when the shapes of the latent samples and noise samples do not match.
• Solution: Ensure that the latents and noise parameters have the same shape before passing them to the node.

ValueError: Expected input batch size to match target batch size

• Explanation: This error occurs when the batch size of the mask does not match the batch size of the latent samples.
• Solution: Ensure that the mask is properly resized and repeated to match the batch size of the latent samples.

RuntimeError: The size of tensor a (X) must match the size of tensor b (Y)

• Explanation: This error occurs when there is a mismatch in the dimensions of the tensors being operated on.
• Solution: Verify that all input tensors (latents, noise, mask) have compatible dimensions and shapes.