Recursive_Symmetry_Aware_Materials_Microstructure_Explorer package

Subpackages

• Recursive_Symmetry_Aware_Materials_Microstructure_Explorer.util package
  • Submodules
  • Recursive_Symmetry_Aware_Materials_Microstructure_Explorer.util.google_images_download module
    • googleimagesdownload
      • googleimagesdownload.build_search_url()
      • googleimagesdownload.build_url_parameters()
      • googleimagesdownload.create_directories()
      • googleimagesdownload.download()
      • googleimagesdownload.download_executor()
      • googleimagesdownload.download_extended_page()
      • googleimagesdownload.download_image()
      • googleimagesdownload.download_image_thumbnail()
      • googleimagesdownload.download_page()
      • googleimagesdownload.file_size()
      • googleimagesdownload.format_object()
      • googleimagesdownload.get_all_tabs()
      • googleimagesdownload.get_next_tab()
      • googleimagesdownload.keywords_from_file()
      • googleimagesdownload.repair()
      • googleimagesdownload.replace_with_byte()
      • googleimagesdownload.similar_images()
      • googleimagesdownload.single_image()
    • main()
    • user_input()
  • Recursive_Symmetry_Aware_Materials_Microstructure_Explorer.util.image_collation module
    • image_collection()
    • image_dataset
  • Recursive_Symmetry_Aware_Materials_Microstructure_Explorer.util.image_scraping module
    • download_images_from_google()
  • Module contents
• Recursive_Symmetry_Aware_Materials_Microstructure_Explorer.viz package
  • Submodules
  • Recursive_Symmetry_Aware_Materials_Microstructure_Explorer.viz.viz module
    • imscatter()
    • plot_embedding()
  • Module contents

Submodules

Recursive_Symmetry_Aware_Materials_Microstructure_Explorer.select_model module

Recursive_Symmetry_Aware_Materials_Microstructure_Explorer.select_model.select_model(data_loader, batch_size, images, model_type='vgg', N_EPOCHS=5, verbose=False)

Parameters:

• data_loader (torch.utils.data.DataLoader) – input data loader

• batch_size (int) – number of data for everytime training

• images (numpy array) – same size of the input data

• model_type (string) – set the model type for training

• resnet_model_path (string) – path of the resnet model

• N_EPOCHS (int) – number of epochs for autoencoder model training

• verbose (bool) – Does the program output information

Returns:

training result

Return type:

numpy arrray

Module contents