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58 lines
2.6 KiB
58 lines
2.6 KiB
# Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
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# SPDX-License-Identifier: MIT
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import os
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import ntpath
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import urllib.request
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import zipfile
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import pytest
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script_dir = os.path.dirname(__file__)
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@pytest.fixture(scope="session")
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def test_data_folder():
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"""
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This fixture returns path to folder with shared test resources among all tests
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"""
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data_dir = os.path.join(script_dir, "testdata")
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if not os.path.exists(data_dir):
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os.mkdir(data_dir)
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sys_arch = os.uname().machine
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if sys_arch == "x86_64":
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libarmnn_url = "https://github.com/ARM-software/armnn/releases/download/v21.11/ArmNN-linux-x86_64.tar.gz"
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else:
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libarmnn_url = "https://github.com/ARM-software/armnn/releases/download/v21.11/ArmNN-linux-aarch64.tar.gz"
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files_to_download = ["https://raw.githubusercontent.com/opencv/opencv/4.0.0/samples/data/messi5.jpg",
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"https://raw.githubusercontent.com/opencv/opencv/4.0.0/samples/data/basketball1.png",
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"https://raw.githubusercontent.com/opencv/opencv/4.0.0/samples/data/Megamind.avi",
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"https://github.com/ARM-software/ML-zoo/raw/master/models/object_detection/ssd_mobilenet_v1/tflite_uint8/ssd_mobilenet_v1.tflite",
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"https://git.mlplatform.org/ml/ethos-u/ml-embedded-evaluation-kit.git/plain/resources/kws/samples/yes.wav",
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"https://raw.githubusercontent.com/Azure-Samples/cognitive-services-speech-sdk/master/sampledata/audiofiles/myVoiceIsMyPassportVerifyMe04.wav",
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"https://tfhub.dev/google/lite-model/magenta/arbitrary-image-stylization-v1-256/int8/prediction/1?lite-format=tflite",
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"https://tfhub.dev/google/lite-model/magenta/arbitrary-image-stylization-v1-256/int8/transfer/1?lite-format=tflite",
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libarmnn_url
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]
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for file in files_to_download:
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path, filename = ntpath.split(file)
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if filename == '1?lite-format=tflite' and 'prediction' in file:
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filename = 'style_predict.tflite'
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elif filename == '1?lite-format=tflite' and 'transfer' in file:
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filename = 'style_transfer.tflite'
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file_path = os.path.join(data_dir, filename)
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if not os.path.exists(file_path):
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print("\nDownloading test file: " + file_path + "\n")
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urllib.request.urlretrieve(file, file_path)
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path, filename = ntpath.split(libarmnn_url)
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file_path = os.path.join(data_dir, filename)
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os.system(f"tar -xvzf {file_path} -C {data_dir} ")
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return data_dir
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