def test_download_and_extract_openomr_dataset_expect_folder_to_be_created(
self):
destination_directory = "OpenOMR"
downloader = OpenOmrDatasetDownloader()
zip_file = downloader.get_dataset_filename()
number_of_samples_in_the_dataset = 706
target_file_extension = "*.png"
self.download_dataset_and_verify_correct_extraction(
destination_directory, number_of_samples_in_the_dataset,
target_file_extension, zip_file, downloader)
def __download_and_extract_datasets(self, datasets, width, height, use_fixed_canvas, staff_line_spacing,
staff_line_vertical_offsets, stroke_thicknesses_for_generated_symbols,
random_position_on_canvas: bool):
if 'homus' in datasets:
raw_dataset_directory = os.path.join(self.dataset_directory, "homus_raw")
dataset_downloader = HomusDatasetDownloader(raw_dataset_directory)
dataset_downloader.download_and_extract_dataset()
generated_image_width = width
generated_image_height = height
if not use_fixed_canvas:
# If we are not using a fixed canvas, remove those arguments to
# allow symbols being drawn at their original shapes
generated_image_width, generated_image_height = None, None
bounding_boxes = HomusImageGenerator.create_images(raw_dataset_directory, self.image_dataset_directory,
stroke_thicknesses_for_generated_symbols,
generated_image_width,
generated_image_height, staff_line_spacing,
staff_line_vertical_offsets,
random_position_on_canvas)
bounding_boxes_cache = os.path.join(self.dataset_directory, "bounding_boxes.txt")
with open(bounding_boxes_cache, "wb") as cache:
pickle.dump(bounding_boxes, cache)
if 'rebelo1' in datasets:
dataset_downloader = RebeloMusicSymbolDataset1Downloader(self.image_dataset_directory)
dataset_downloader.download_and_extract_dataset()
if 'rebelo2' in datasets:
dataset_downloader = RebeloMusicSymbolDataset2Downloader(self.image_dataset_directory)
dataset_downloader.download_and_extract_dataset()
if 'printed' in datasets:
dataset_downloader = PrintedMusicSymbolsDatasetDownloader(self.image_dataset_directory)
dataset_downloader.download_and_extract_dataset()
if 'fornes' in datasets:
raw_dataset_directory = os.path.join(self.dataset_directory, "fornes_raw")
dataset_downloader = FornesMusicSymbolsDatasetDownloader(raw_dataset_directory)
dataset_downloader.download_and_extract_dataset()
image_preparer = FornesMusicSymbolsImagePreparer()
image_preparer.prepare_dataset(raw_dataset_directory, self.image_dataset_directory)
if 'audiveris' in datasets:
raw_dataset_directory = os.path.join(self.dataset_directory, "audiveris_omr_raw")
intermediate_image_directory = os.path.join(self.dataset_directory, "audiveris_omr_images")
dataset_downloader = AudiverisOmrDatasetDownloader(raw_dataset_directory)
dataset_downloader.download_and_extract_dataset()
image_generator = AudiverisOmrImageGenerator()
image_generator.extract_symbols(raw_dataset_directory, intermediate_image_directory)
image_preparer = AudiverisOmrImageExtractor()
image_preparer.prepare_dataset(intermediate_image_directory, self.image_dataset_directory)
if 'muscima_pp' in datasets:
raw_dataset_directory = os.path.join(self.dataset_directory, "muscima_pp_raw")
dataset_downloader = MuscimaPlusPlusDatasetDownloader(raw_dataset_directory)
dataset_downloader.download_and_extract_dataset()
image_generator = MuscimaPlusPlusImageGenerator2()
image_generator.extract_symbols_for_training(raw_dataset_directory, self.image_dataset_directory)
if 'openomr' in datasets:
raw_dataset_directory = os.path.join(self.dataset_directory, "open_omr_raw")
dataset_downloader = OpenOmrDatasetDownloader(raw_dataset_directory)
dataset_downloader.download_and_extract_dataset()
image_preparer = OpenOmrImagePreparer()
image_preparer.prepare_dataset(raw_dataset_directory, self.image_dataset_directory)
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")
source_folder = os.path.join(raw_dataset_directory, symbol_class)
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(flags.raw_dataset_directory)
#dataset_downloader.download_and_extract_dataset()
# Actually prepare our dataset
dataset_preparer = OpenOmrImagePreparer()
dataset_preparer.prepare_dataset(flags.raw_dataset_directory,
flags.image_dataset_directory)
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)
#%% Audiveris
from omrdatasettools.downloaders.AudiverisOmrDatasetDownloader import AudiverisOmrDatasetDownloader
dataset_downloader = AudiverisOmrDatasetDownloader("./data/audiveris")
dataset_downloader.download_and_extract_dataset()
from omrdatasettools.image_generators.AudiverisOmrImageGenerator import AudiverisOmrImageGenerator, AudiverisOmrSymbol
imgen = AudiverisOmrImageGenerator()
imgen.extract_symbols(raw_data_directory='./data/audiveris',
destination_directory='./data/audiveris/images')
#%% Open OMR
from omrdatasettools.downloaders.OpenOmrDatasetDownloader import OpenOmrDatasetDownloader
dataset_downloader = OpenOmrDatasetDownloader("./data/openomr")
dataset_downloader.download_and_extract_dataset()
#%% Capitan
'''
from omrdatasettools.downloaders.CapitanDatasetDownloader import CapitanDatasetDownloader
dataset_downloader = CapitanDatasetDownloader("./data/capitan")
dataset_downloader.download_and_extract_dataset()
'''
#%% MUSCIMA
from omrdatasettools.downloaders.MuscimaPlusPlusDatasetDownloader import MuscimaPlusPlusDatasetDownloader
dataset_downloader = MuscimaPlusPlusDatasetDownloader("./data/muscima")
dataset_downloader.download_and_extract_dataset()