Python download_model_by_nameの例

コード例 #1

ファイル: install_data_and_model.py プロジェクト: BorisJineman/CNTK

# 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")

コード例 #2

ファイル: install_data_and_model.py プロジェクト: ngcaden/CNTK-Hotel-pictures-classificator

    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)

コード例 #3

# 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")

コード例 #4

# 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")

コード例 #5

ファイル: install_fastrcnn.py プロジェクト: BorisJineman/CNTK

# 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")