def get_images(artworks_filename):
"""
Iterates through a JSON data file, and retrieves all images associated with
it, and downloads them to an image directory
Args:
artworks_filename : the filename of the JSON data file
"""
artworks_file = open(artworks_filename)
artworks_data = json.load(artworks_file)
classification_labels = {}
nation_labels = {}
date_labels = {}
start_date_labels = {}
end_date_labels = {}
time_period_labels = {}
i = 0
for artwork in artworks_data:
url = artwork['URL']
object_id = artwork['ObjectID']
classification = artwork['Classification']
nation = artwork['Nationality']
date = artwork['Date']
start_date, end_date = process_date(date)
if url is not None and classification is not None and len(
nation) != 0 and date is not None:
if classification in class_check and date in date_check and nation[
0] in nation_check:
if not image_available(url):
continue
# Get the filename of the image using the Object ID of the image, and save the image
# to disk.
image_filename = 'moma_' + str(object_id).zfill(
padding) + '.jpg'
# get_image(url, image_filename)
classification_labels[
'moma_' + str(object_id).zfill(padding)] = classification
nation_labels['moma_' +
str(object_id).zfill(padding)] = nation[0]
date_labels['moma_' + str(object_id).zfill(padding)] = date
if start_date is not None:
start_date_labels['moma_' + str(object_id).zfill(
padding)] = Interval.range_str(start_date)
if end_date is not None:
end_date_labels['moma_' + str(object_id).zfill(
padding)] = Interval.range_str(end_date)
if start_date is not None:
time_period_labels['moma_' + str(object_id).zfill(
padding)] = Interval.time_period(start_date)
write_labels(classification_labels, "moma_class.csv")
write_labels(nation_labels, "moma_nation.csv")
write_labels(date_labels, "moma_date.csv")
write_labels(start_date_labels, "moma_start_date.csv")
write_labels(end_date_labels, "moma_end_date.csv")
write_labels(time_period_labels, "moma_time_period.csv")
artworks_file.close()
