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Welcome to the 3D Instance Skeletonization Wiki

We summarize here the steps and code needed to be run for generating a training dataset for skeleton prediction. SegEM dataset is used as an exemplary dataset. We only utilize the ground truth skeletons from the dataset for training and evaluation.

As described in my masters thesis we encode skeletons into a flux field and train a U-net to predict the flux. Decoding skeletons from flux is achieved by thresholding divergence of the predicted flux field.

Below steps will describe the complete process of training data generation, model training, prediction, and skeleton decoding.