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Facilitates dataset configuration for HYDiT training environment, streamlining setup and management of parameters for training tasks.
The MZ_HYDiTDatasetConfig
node is designed to facilitate the configuration of datasets for the HYDiT training environment. This node allows you to set up and manage various parameters related to your dataset, ensuring that it is properly configured for training tasks. By using this node, you can streamline the process of preparing your dataset, making it easier to handle different resolutions, captions, and image settings. This node is particularly useful for AI artists who need to manage large datasets with specific requirements, as it provides a structured way to configure and organize your data.
This parameter expects a configuration object of type MZ_TT_HYDiT_WorkspaceConfig
. It contains essential settings and paths related to the workspace where the dataset will be managed. This configuration ensures that the dataset is correctly linked to the workspace, allowing for seamless integration and management.
This parameter is an integer that specifies the resolution of the images in the dataset. The default value is 1024. Setting the correct resolution is crucial for ensuring that the images are processed correctly during training. Higher resolutions may provide more detail but require more computational resources, while lower resolutions may speed up processing but at the cost of image quality.
This parameter can be set to either "enable" or "disable", with the default being "disable". When enabled, it forces the clearing of existing data in the workspace before new data is added. This is useful for ensuring that old or irrelevant data does not interfere with the current training process.
Similar to force_clear
, this parameter can be set to "enable" or "disable", with the default being "disable". When enabled, it specifically clears only the images in the workspace, leaving other data intact. This is useful if you want to update the images without affecting other configurations or data.
This parameter can be set to either "enable" or "disable", with the default being "disable". When enabled, it generates the same caption for all images in the dataset. This can be useful for certain types of training where uniform captions are required.
This is a string parameter that allows you to specify a caption that will be applied to all images if same_caption_generate
is enabled. It supports dynamic prompts and multiline text, providing flexibility in how captions are generated and applied.
This optional parameter accepts images that will be included in the dataset. It allows you to add specific images to the dataset, providing a way to customize the data that will be used for training.
This output parameter is a string that provides the directory path where the images for the workspace are stored. This path is essential for accessing and managing the images that are part of the dataset, ensuring that they are correctly linked to the training process.
workspace_config
parameter is correctly set up to avoid issues with linking the dataset to the workspace.resolution
parameter to balance between image quality and computational resources. Higher resolutions provide more detail but require more processing power.force_clear
or force_clear_only_images
if you need to refresh the dataset without retaining old data, ensuring a clean slate for new training tasks.same_caption_generate
and same_caption
parameters to create uniform captions for all images, which can be useful for specific training scenarios.train_name
parameter is not provided or is empty.train_name
parameter is set and not empty in the workspace_config
.resolution
parameter is correctly set and that all necessary files and paths are accessible. Check the console for more details.© Copyright 2024 RunComfy. All Rights Reserved.