Chair of Continuum Mechanics

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401 to 410 of 492 Results

Frac_Unet_postprocess.py Jul 7, 2021 - Fracture network segmentation Plain Text - 3.0 KB - MD5: 8af741da7af5db62a1855a4c4eed56d0 With the code, the predictions of trained model for given input files can be generated and saved.
Frac_Unet_preprocess.py Jul 7, 2021 - Fracture network segmentation Plain Text - 2.2 KB - MD5: a269c380d683920ac900d3539a4fdc6a Preparation of training data can be done with the code
Frac_Unet_training.py Jul 7, 2021 - Fracture network segmentation Plain Text - 5.6 KB - MD5: 0d2949b2c023b9f5b67ccefb8487d803 With the pre-processed training data, the code performs training of U-net model and saves a trained model after training.
img_seg.py Jul 7, 2021 - Fracture network segmentation Plain Text - 15.4 KB - MD5: 9a20bdaef7a1f87ecfdd053873a642bf This file contains the load/save functions and core functions of the Sato and the Local threshold methods.
Local_threshold.py Jul 7, 2021 - Fracture network segmentation Plain Text - 1.5 KB - MD5: 68ae24ecafdaa06a04bf09504eb44fd2 This file contains the workflow of the local threshold method
post_random_forest.py Jul 7, 2021 - Fracture network segmentation Plain Text - 1.5 KB - MD5: 2c64aaca9f227470a4c9602988e8f9e8 The predictions of the Random forest method can be merged into the original size of image with the code.
processing.bsh Jul 7, 2021 - Fracture network segmentation Unknown - 2.0 KB - MD5: 4e3d9a1297a097e73d8e5433ca5449e3 Prediction generator of the random forest method. The input file path, save path and trained model have to be chosen.
readme.txt Jul 7, 2021 - Fracture network segmentation Plain Text - 2.6 KB - MD5: 1d388e58b5fd9037ef315ff386a6da77 This file contains instruction of how to operate the codes.
Sato.py Jul 7, 2021 - Fracture network segmentation Plain Text - 908 B - MD5: 14c9f9428402bc7a550102032725a288 This file contains the workflow of the Sato method
trained_model_U_net_27.hdf5 Jul 7, 2021 - Fracture network segmentation Hierarchical Data Format - 89.9 MB - MD5: f8caecb9a1ddb337df1df2b6be0d82ed Trained model of the U-net model. This file is required to reproduce the results.

Frac_Unet_postprocess.py