def test_cityscapes(self):
with cityscapes_root() as root:
for mode in ['coarse', 'fine']:
if mode == 'coarse':
splits = ['train', 'train_extra', 'val']
else:
splits = ['train', 'val', 'test']
for split in splits:
for target_type in ['semantic', 'instance']:
dataset = torchvision.datasets.Cityscapes(
root,
split=split,
target_type=target_type,
mode=mode)
self.generic_segmentation_dataset_test(dataset,
num_images=2)
color_dataset = torchvision.datasets.Cityscapes(
root, split=split, target_type='color', mode=mode)
color_img, color_target = color_dataset[0]
self.assertTrue(isinstance(color_img, PIL.Image.Image))
self.assertTrue(np.array(color_target).shape[2] == 4)
polygon_dataset = torchvision.datasets.Cityscapes(
root, split=split, target_type='polygon', mode=mode)
polygon_img, polygon_target = polygon_dataset[0]
self.assertTrue(isinstance(polygon_img, PIL.Image.Image))
self.assertTrue(isinstance(polygon_target, dict))
self.assertTrue(
isinstance(polygon_target['imgHeight'], int))
self.assertTrue(isinstance(polygon_target['objects'],
list))
# Test multiple target types
targets_combo = ['semantic', 'polygon', 'color']
multiple_types_dataset = torchvision.datasets.Cityscapes(
root,
split=split,
target_type=targets_combo,
mode=mode)
output = multiple_types_dataset[0]
self.assertTrue(isinstance(output, tuple))
self.assertTrue(len(output) == 2)
self.assertTrue(isinstance(output[0], PIL.Image.Image))
self.assertTrue(isinstance(output[1], tuple))
self.assertTrue(len(output[1]) == 3)
self.assertTrue(isinstance(output[1][0],
PIL.Image.Image)) # semantic
self.assertTrue(isinstance(output[1][1], dict)) # polygon
self.assertTrue(isinstance(output[1][2],
PIL.Image.Image)) # color
def test_cityscapes(self):
with cityscapes_root() as root:
for mode in ['coarse', 'fine']:
if mode == 'coarse':
splits = ['train', 'train_extra', 'val']
else:
splits = ['train', 'val', 'test']
for split in splits:
for target_type in ['semantic', 'instance']:
dataset = Cityscapes(root,
split=split,
target_type=target_type,
mode=mode)
self.generic_segmentation_dataset_test(dataset,
num_images=2)
color_dataset = Cityscapes(root,
split=split,
target_type='color',
mode=mode)
color_img, color_target = color_dataset[0]
self.assertTrue(isinstance(color_img, PIL.Image.Image))
self.assertTrue(np.array(color_target).shape[2] == 4)
polygon_dataset = Cityscapes(root,
split=split,
target_type='polygon',
mode=mode)
polygon_img, polygon_target = polygon_dataset[0]
self.assertTrue(isinstance(polygon_img, PIL.Image.Image))
self.assertTrue(isinstance(polygon_target, dict))
self.assertTrue(
isinstance(polygon_target['imgHeight'], int))
self.assertTrue(isinstance(polygon_target['objects'],
list))