def test_download_and_prepare_dataset(self):
# Arrange
datasetDownloader = OpenOmrDatasetDownloader()
expected_number_of_images = 503
# Act
datasetDownloader.download_and_extract_dataset("temp/open_omr_raw2")
image_generator = OpenOmrImagePreparer()
image_generator.prepare_dataset("temp/open_omr_raw2",
"temp/open_omr_image2")
all_image_files = [
y for x in os.walk("temp/open_omr_image2")
for y in glob(os.path.join(x[0], '*.png'))
]
actual_number_of_images = len(all_image_files)
# Assert
self.assertEqual(expected_number_of_images, actual_number_of_images)
# Cleanup
os.remove(datasetDownloader.get_dataset_filename())
shutil.rmtree("temp")
destination_folder = os.path.join(image_dataset_directory,
destination_class_name)
os.makedirs(destination_folder, exist_ok=True)
dir_util.copy_tree(source_folder, destination_folder)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--raw_dataset_directory",
type=str,
default="../data/open_omr_raw",
help="The directory, where the raw Muscima++ dataset can be found")
parser.add_argument(
"--image_dataset_directory",
type=str,
default="../data/images",
help="The directory, where the images will be copied to")
flags, unparsed = parser.parse_known_args()
# Download the dataset
dataset_downloader = OpenOmrDatasetDownloader()
dataset_downloader.download_and_extract_dataset(
flags.raw_dataset_directory)
# Actually prepare our dataset
dataset_preparer = OpenOmrImagePreparer()
dataset_preparer.prepare_dataset(flags.raw_dataset_directory,
flags.image_dataset_directory)