Skip to content

Latest commit

 

History

History
8 lines (7 loc) · 1.36 KB

README.md

File metadata and controls

8 lines (7 loc) · 1.36 KB

README for NIST16 DATASET

This Dir is used to place the dataset from NIST16, To reduce the size of git repo, I added all the *jpg files to the ".gitigore".

If you want to perform Mantra-Net with NIST16 data, you can download it on the official website of NIST, and view the data file or resize the file to (256, 256) with Python scriprt given in this dir:

  • 1-ReadData.py Shows and illustrate part of data in NIST16 dataset
  • 2-resizeData.py Will resize the raw pictures to a smaller scale in order to accelerate the training. However, in our test, resize can eliminate a large number of features used to identify modifications, which means reduce the performance of the net. You could set parameters and scale you like to reproduce your own sub-dataset. This script will also create an index.csv file to make an index for the output images in directory ./NIST2016.
  • 3-SplitDataset.py This Python file will create two split index files randomly for Training dataset and Testing dataset, respectively. It is generated from ./NIST2016/index.csv file, so you must run 2-resizeData.py in advance to create Train.csv and Test.csv correctly.

    The Train.py in root directory needs to read Train.csv and Test.csv to run the trainning process.