ComfyUI Node: 🔧 Image Random Transform

🔧 Image Random Transform+:

The ImageRandomTransform+ node is designed to apply a series of random transformations to an image, enhancing its variability and augmenting your dataset. This node is particularly useful for AI artists looking to introduce randomness and diversity into their image processing workflows. By applying transformations such as perspective distortion, rotation, color jittering, horizontal flipping, and resized cropping, this node helps in creating a wide range of image variations from a single input. This can be beneficial for training machine learning models, creating unique artistic effects, or simply experimenting with different visual styles. The transformations are controlled by a seed value, ensuring reproducibility, and a variation parameter that adjusts the intensity of the transformations.

🔧 Image Random Transform+ Input Parameters:

image

The image parameter is the input image that you want to transform. It should be a tensor representing the image data. This is the primary input on which all the transformations will be applied.

seed

The seed parameter is an integer value used to initialize the random number generator. This ensures that the transformations are reproducible. By using the same seed value, you can generate the same set of transformations on the input image. There is no specific minimum or maximum value for the seed, but it should be an integer.

repeat

The repeat parameter is an integer that specifies how many times the input image should be repeated before applying the transformations. This allows you to generate multiple transformed versions of the same image in one go. The default value is typically 1, and it should be a positive integer.

variation

The variation parameter is a float that controls the intensity of the transformations. It scales the amount of distortion, rotation, brightness, contrast, saturation, hue, and scale applied to the image. A higher variation value will result in more pronounced transformations. The default value is usually 1.0, with a minimum value of 0.0 and no strict maximum, but practical values typically range from 0.0 to 1.0.

🔧 Image Random Transform+ Output Parameters:

IMAGE

The output of the ImageRandomTransform+ node is a tensor containing the transformed image(s). The output tensor has the same dimensions as the input image but includes the applied transformations. This allows you to use the transformed images for further processing, visualization, or as input to other nodes in your workflow.

🔧 Image Random Transform+ Usage Tips:

• To achieve consistent results, use the same seed value when applying transformations to similar images.
• Adjust the variation parameter to control the intensity of the transformations. For subtle changes, use a lower variation value; for more dramatic effects, increase the variation.
• Use the repeat parameter to generate multiple variations of the same image in a single execution, which can be useful for data augmentation in machine learning tasks.

🔧 Image Random Transform+ Common Errors and Solutions:

Invalid image tensor shape

• Explanation: The input image tensor does not have the expected shape.
• Solution: Ensure that the input image tensor has the correct dimensions, typically [batch_size, height, width, channels].

Seed value is not an integer

• Explanation: The seed parameter is not an integer.
• Solution: Provide an integer value for the seed parameter to ensure reproducibility of the transformations.

Repeat value is not a positive integer

• Explanation: The repeat parameter is not a positive integer.
• Solution: Ensure that the repeat parameter is a positive integer to correctly repeat the input image.

Variation value out of range

• Explanation: The variation parameter is set to an impractical value.
• Solution: Adjust the variation parameter to a value between 0.0 and 1.0 for practical transformation intensities.