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Load pre-trained scratch detection model for photo restoration workflow automation.
The BOPBTL_LoadScratchMaskModel
node is designed to load a pre-trained model specifically for detecting scratches in old photos. This node is a crucial part of the photo restoration process, as it provides the necessary model to identify and mask scratches, which can then be repaired or enhanced using other nodes in the workflow. By loading the scratch detection model, this node enables you to automate the process of identifying damaged areas in photographs, making it easier to restore and enhance old images with minimal manual intervention. The primary goal of this node is to streamline the initial step of photo restoration by providing a reliable and efficient way to load the scratch detection model.
The scratch_model
parameter specifies the name of the pre-trained scratch detection model that you want to load. This parameter is essential as it determines which model will be used to detect scratches in the images. The available options for this parameter are the filenames of the models stored in the "checkpoints" directory. Selecting the appropriate model can significantly impact the accuracy and effectiveness of the scratch detection process. There are no minimum or maximum values for this parameter, but it must be a valid filename from the specified directory.
The scratch_model
output parameter provides the loaded scratch detection model. This model is used in subsequent nodes to detect and mask scratches in old photos. The output is crucial for the photo restoration workflow, as it serves as the foundation for identifying damaged areas that need to be repaired. The loaded model is returned as a tuple containing the model object, which can then be passed to other nodes for further processing.
scratch_model
parameter is set to a valid filename from the "checkpoints" directory to avoid errors during model loading.scratch_model
filename does not exist in the "checkpoints" directory.© Copyright 2024 RunComfy. All Rights Reserved.