# Copyright (c) Microsoft. All rights reserved. # Licensed under the MIT license. See LICENSE.md file in the project root # for full license information. # ============================================================================== from __future__ import print_function import os, sys base_folder = os.path.dirname(os.path.abspath(__file__)) sys.path.append(os.path.join(base_folder, "..", "DataSets", "Flowers")) from install_flowers import download_flowers_data download_flowers_data() sys.path.append(os.path.join(base_folder, "..", "DataSets", "Animals")) from install_animals import download_animals_data download_animals_data() sys.path.append(os.path.join(base_folder, "..", "DataSets", "Grocery")) from install_grocery import download_grocery_data download_grocery_data() sys.path.append(os.path.join(base_folder, "..", "PretrainedModels")) from models_util import download_model_by_name download_model_by_name("ResNet_18")
sys.path.append( os.path.join(folder_path, "..", "..", "Detection", "utils", "annotations")) from annotations_helper import create_class_dict, create_map_files abs_path = os.path.dirname(os.path.abspath(__file__)) data_set_path = os.path.join(abs_path, cfg["CNTK"].MAP_FILE_PATH) class_dict = create_class_dict(data_set_path) create_map_files(data_set_path, class_dict, training_set=True) create_map_files(data_set_path, class_dict, training_set=False) if __name__ == '__main__': base_folder = os.path.dirname(os.path.abspath(__file__)) #downloads pretrained model pointed out in config.py that will be used for transfer learning sys.path.append(os.path.join(base_folder, "..", "..", "PretrainedModels")) from models_util import download_model_by_name download_model_by_name(cfg["CNTK"].BASE_MODEL) #downloads hotel pictures classificator dataset (HotailorPOC2) #comment out lines bellow if you're using a custom dataset sys.path.append( os.path.join(base_folder, "..", "..", "DataSets", "HotailorPOC2")) from download_HotailorPOC2_dataset import download_dataset download_dataset() #generates metadata for dataset required by FasterRCNN.py script print("Creating mapping files for data set..") create_mappings(base_folder)
# Copyright (c) Microsoft. All rights reserved. # Licensed under the MIT license. See LICENSE.md file in the project root # for full license information. # ============================================================================== from __future__ import print_function import zipfile import os, sys base_folder = os.path.dirname(os.path.abspath(__file__)) sys.path.append(os.path.join(base_folder, "..", "..", "DataSets", "grocery")) from install_grocery import download_grocery_data download_grocery_data() sys.path.append(os.path.join(base_folder, "..", "..", "PretrainedModels")) from models_util import download_model_by_name download_model_by_name("AlexNet")
# Copyright (c) Microsoft. All rights reserved. # Licensed under the MIT license. See LICENSE.md file in the project root # for full license information. # ============================================================================== from __future__ import print_function import zipfile import os, sys import os.path base_folder = os.path.dirname(os.path.abspath(__file__)) sys.path.append(os.path.join(base_folder, "..", "DataSets", "grocery")) from install_grocery import download_grocery_data download_grocery_data() sys.path.append(os.path.join(base_folder, "..", "PretrainedModels")) from models_util import download_model_by_name download_model_by_name("ResNet_18")
# Copyright (c) Microsoft. All rights reserved. # Licensed under the MIT license. See LICENSE.md file in the project root # for full license information. # ============================================================================== from __future__ import print_function import zipfile import os, sys base_folder = os.path.dirname(os.path.abspath(__file__)) sys.path.append(os.path.join(base_folder, "..", "..", "DataSets", "Grocery")) from install_grocery import download_grocery_data download_grocery_data() sys.path.append(os.path.join(base_folder, "..", "..", "PretrainedModels")) from models_util import download_model_by_name download_model_by_name("AlexNet")