def create_zipfile(zip_filepath, splits_with_ids, suffixes, maindir=None):
"""Generates a zipfile with a cityscapes-like file structure and random pngs.
Args:
zip_filepath (str): filepath to the zip archive that will be created
splits_with_ids (Dict[str, List[str]]): data-splits like 'train' or 'val'
that map to a list of image ids
suffixes (List[str]): suffix per modality that should be created e.g.
'leftImg8bit'
maindir (str): name of the root directory of the zipfile, defaults to the
name of the zipfile
"""
with zipfile.ZipFile(zip_filepath, 'w') as z:
for split, ids in splits_with_ids.items():
if maindir is None:
maindir = os.path.basename(zip_filepath).strip('.zip')
split = os.path.join(maindir, split)
for img_id in ids:
city = CITY_IN_ID_RE.match(img_id).group(1)
for suffix in suffixes:
if 'Img' in suffix:
img = get_random_png(height=1024,
width=2048,
channels=3)
else:
img = get_random_png(height=1024,
width=2048,
channels=1)
z.write(
img,
os.path.join(split, city,
'{}_{}.png'.format(img_id, suffix)))
def create_zip(fname, prefix):
out_path = os.path.join(_output_dir(), fname)
png = fake_data_utils.get_random_png(height=1, width=1)
with zipfile.ZipFile(out_path, 'w') as myzip:
myzip.write(png, prefix + 'rock/0.png')
myzip.write(png, prefix + 'paper/0.png')
myzip.write(png, prefix + 'scissors/0.png')
def _create_zip_files():
"""Saves png and label using name index."""
if not os.path.exists(_output_dir()):
os.makedirs(_output_dir())
images_out_path = os.path.join(_output_dir(), "data_object_image_2.zip")
with zipfile.ZipFile(images_out_path, "w") as image_zip:
for i in range(NUM_IMAGES):
png = fake_data_utils.get_random_png(HEIGHT, WIDTH)
image_zip.write(
png,
os.path.join("training", "image_2",
"image_{:06d}.png".format(i)))
label_out_path = os.path.join(_output_dir(), "data_object_label_2.zip")
with zipfile.ZipFile(label_out_path, "w") as label_zip:
for i in range(NUM_IMAGES):
annotation = _get_annotations()
label = _get_label_file(annotation)
label_zip.write(
label,
os.path.join("training", "label_2",
"label_{:06d}.txt".format(i)))
devkit_out_path = os.path.join(_output_dir(), "devkit_object.zip")
with zipfile.ZipFile(devkit_out_path, "w") as devkit_zip:
train_rand, train_mapping = _get_mapping_files()
devkit_zip.write(train_rand, os.path.join("mapping", "train_rand.txt"))
devkit_zip.write(train_mapping,
os.path.join("mapping", "train_mapping.txt"))
def _generate_image(fdir, fname):
dirname = os.path.join(_output_dir(), fdir)
if not os.path.exists(dirname):
os.makedirs(dirname)
tf.io.gfile.copy(fake_data_utils.get_random_png(1, 1),
os.path.join(dirname, fname),
overwrite=True)
def create_images(label):
images_dir = _output_dir()
if not tf.io.gfile.exists(images_dir):
tf.io.gfile.makedirs(images_dir)
for l in label:
image_name = 'obj1_{}.png'.format(l)
tf.io.gfile.copy(fake_data_utils.get_random_png(128, 128),
os.path.join(images_dir, image_name),
overwrite=True)
def create_folder(fname):
images_dir = os.path.join(_output_dir(), fname)
if not tf.io.gfile.exists(images_dir):
tf.io.gfile.makedirs(images_dir)
for i in range(2):
image_name = 'C189P150ThinF_IMG_20151203_141809_cell_{:03d}.png'.format(
i)
tf.io.gfile.copy(fake_data_utils.get_random_png(300, 300),
os.path.join(images_dir, image_name),
overwrite=True)
def _get_synset(synset_name):
"""Returns path to synset archive."""
fobj = tempfile.NamedTemporaryFile(delete=False, mode='wb', suffix='.tar')
tar = tarfile.open(mode='w', fileobj=fobj)
for i in range(1, TRAIN_IMAGES_PER_SYNSET + 1):
fname = '%s_%s.JPEG' % (synset_name, i)
# There are a few PNG and CMYK images:
if synset_name == 'n01440764' and i == 1:
path = fake_data_utils.get_random_png()
elif synset_name == 'n01440764' and i in [2, 3]:
path = os.path.join(FLAGS.tfds_dir, 'testing', 'test_data',
'6pixels_cmyk.jpeg')
else:
path = fake_data_utils.get_random_jpeg()
tar.add(path, arcname=fname)
fobj.close()
return fobj.name
def _generate_data():
"""Generate images archive."""
# Generate images
images_dir = os.path.join(_output_dir(), 'images')
if not tf.io.gfile.exists(images_dir):
tf.io.gfile.makedirs(images_dir)
for i in range(_TRAIN_IMAGES_NUMBER + _TEST_IMAGES_NUMBER):
image_name = 'image{:03d}.jpg'.format(i)
tf.io.gfile.copy(fake_data_utils.get_random_jpeg(),
os.path.join(images_dir, image_name),
overwrite=True)
# Generate annotations
annotations_dir = os.path.join(_output_dir(), 'annotations')
if not tf.io.gfile.exists(annotations_dir):
tf.io.gfile.makedirs(annotations_dir)
# Generate trimaps
trimaps_dir = os.path.join(annotations_dir, 'trimaps')
if not tf.io.gfile.exists(trimaps_dir):
tf.io.gfile.makedirs(trimaps_dir)
global_count = 0
for filename, num_examples in [('trainval.txt', _TRAIN_IMAGES_NUMBER),
('test.txt', _TEST_IMAGES_NUMBER)]:
fobj = tempfile.NamedTemporaryFile(delete=False, mode='w')
with fobj:
for i in range(num_examples):
fobj.write('image{:03d} {} 0 0\n'.format(global_count, i % 37))
global_count += 1
tf.io.gfile.copy(fobj.name,
os.path.join(annotations_dir, filename),
overwrite=True)
# Create trimaps
for i in range(_TRAIN_IMAGES_NUMBER + _TEST_IMAGES_NUMBER):
trimap_name = 'image{:03d}.png'.format(i)
tf.io.gfile.copy(fake_data_utils.get_random_png(channels=1),
os.path.join(trimaps_dir, trimap_name),
overwrite=True)
def _generate_data(split):
"""Generate images archive."""
# Generate images
images_dir = os.path.join(_output_dir(), 'images', split)
if not tf.io.gfile.exists(images_dir):
tf.io.gfile.makedirs(images_dir)
for i in range(_IMAGE_NUMBERS[split]):
image_name = 'CLEVR_{}_{:06d}.png'.format(split, i)
tf.io.gfile.copy(fake_data_utils.get_random_png(),
os.path.join(images_dir, image_name),
overwrite=True)
if split in ['train', 'val']:
# Generate annotations
scenes_dir = os.path.join(_output_dir(), 'scenes')
if not tf.io.gfile.exists(scenes_dir):
tf.io.gfile.makedirs(scenes_dir)
annotations = {
'scenes': [{
'objects': [{
'color': 'red',
'shape': 'sphere',
'size': 'small',
'material': 'rubber',
'3d_coords': [0.0, 0.0, 0.0],
'pixel_coords': [0.0, 0.0, 0.0],
'rotation': 0.0
}] * _NUM_OBJECTS
}] * _IMAGE_NUMBERS[split]
}
annotations_file = os.path.join(scenes_dir,
'CLEVR_{}_scenes.json'.format(split))
with tf.io.gfile.GFile(annotations_file, 'w') as f:
json.dump(annotations, f)
def create_zip(fname):
out_path = os.path.join(_output_dir(), fname)
png = fake_data_utils.get_random_png(height=1, width=1)
with zipfile.ZipFile(out_path, 'w') as myzip:
myzip.write(png, 'horses/0.png')
myzip.write(png, 'humans/0.png')