File: LayoutGAN_Mnist.ipynb
Download it to your local PC or upload it to the Google Colab. You can use any tool which supports notebook (.ipynb) files.
Download the mnist_data.npy file from the link [link].
Perform below steps to modify the code according your environment:
-
Update the sample_dir variable with the path to the folder where you want to store the result images.
-
Update the dataset_path variable with the path where you stored mnist_data.npy file.
-
Run the LayoutGAN_Mnist.ipynb from the beginning.
-
Prediction will be stored in the sample_dir folder.
File: LayoutGAN_PubLayNet.ipynb
Download it to your local PC or upload it to the Google Colab. You can use any tool which supports notebook (.ipynb) files.
Download the sorted_c1publay.npy file from the link [link].
Perform below steps to modify the code according your environment:
-
Update the sample_dir variable with the path to the folder where you want to store the result images.
-
Update the dataset_path variable with the path where you stored sorted_c1publay.npy file.
-
Run the LayoutGAN_PubLayNet.ipynb file from the beginning.
-
Prediction will be stored in the sample_dir folder.
GPU is preferred, but not necessary. Machine with GPU can perform the training faster compared to non-GPU machines.