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Facilitates loading EXR image files, supports batch loading, progress tracking, and color space conversion.
The LoadEXR
node is designed to facilitate the loading of EXR (OpenEXR) image files into your workflow. EXR files are commonly used in high-dynamic-range imaging and visual effects due to their ability to store a wide range of color and brightness information. This node allows you to load single or multiple EXR files from a specified directory, converting them into a format that can be processed further in your pipeline. It supports batch loading, progress tracking, and optional conversion from linear to sRGB color space, making it a versatile tool for handling high-quality image data efficiently.
The filepath
parameter specifies the path to the EXR file or directory containing EXR files that you want to load. If a single file is specified, it will be loaded directly. If a directory is specified, all EXR files within the directory will be loaded. The path should be a string and must end with .exr
or .EXR
. This parameter is crucial as it determines the source of the image data to be processed.
The image_load_cap
parameter limits the number of EXR files to be loaded from the specified directory. This is useful when dealing with a large number of files and you only need to process a subset. The value should be an integer, with a default of 0, which means no limit. Setting this parameter helps manage memory usage and processing time.
The skip_first_images
parameter allows you to skip a specified number of initial EXR files in the directory. This can be useful if you want to ignore certain files at the beginning of the list. The value should be an integer, with a default of 0, meaning no files are skipped. This parameter helps in selectively processing files from a large dataset.
The select_every_nth
parameter enables you to load every nth EXR file from the directory. This is particularly useful for downsampling a sequence of images. The value should be an integer, with a default of 1, meaning every file is loaded. Adjusting this parameter can help in reducing the number of files processed, thus saving time and resources.
The samples
output parameter contains the loaded image data in a tensor format. This tensor can be directly used for further processing in your workflow. The samples
parameter is essential as it holds the actual image data extracted from the EXR files, ready for subsequent operations.
The batch_size
output parameter indicates the number of EXR files that were successfully loaded. This is an integer value and provides information about the size of the dataset being processed. The batch_size
parameter is useful for understanding the scope of the loaded data and for managing batch processing tasks.
filepath
parameter correctly points to the desired EXR file or directory to avoid file not found errors.image_load_cap
parameter to limit the number of files loaded, especially when working with large datasets, to manage memory usage effectively.skip_first_images
and select_every_nth
parameters to selectively load files, which can be helpful in scenarios where you need to process a specific subset of images.<filepath>
filepath
parameter is correct and that the path exists on your filesystem.filepath
parameter points to the correct directory.filepath
parameter ends with .exr
or .EXR
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