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