def get_array_numpy_images():
"""returns labels, ndarry (shape (~, 28, 28))"""
# max_drawings -- maximum number of drawings to be loaded into memory,
# defaults to 1000 (3 minutes)
qd = QuickDrawData(max_drawings=1000)
# LIST OBJECT
drawing_names = qd.drawing_names
# LABELS
list_of_labels = []
# just append your arrays to a Python list and convert it at the end;
# the result is simpler and faster
list_of_np = []
for label in drawing_names:
# QuickDrawDataGroup Object
qd_data_group = qd.get_drawing_group(label)
# QuickDrawing Object
for drawing in qd_data_group.drawings:
list_of_labels.append(label)
# PIL IMAGE
PIL_im = drawing.image.convert('L').resize((28, 28),
Image.ANTIALIAS)
nump_im = np.array(PIL_im)
list_of_np.append(nump_im)
# convert to ndarray
array_of_np = np.asarray(list_of_np)
array_of_labels = np.asarray(list_of_labels)
print("IMAGES SHAPE ", array_of_np.shape)
print("LABELS SHAPE ", array_of_labels.shape)
np.save("images-new.npy", array_of_np)
np.save("labels-new.npy", array_of_labels)
def test_get_drawing_group():
qd = QuickDrawData()
assert isinstance(qd.get_drawing_group("anvil"), QuickDrawDataGroup)
