def test_dynamic_init(self):
sampler = UniformSampler(reader=get_dynamic_window_reader(),
window_sizes=DYNAMIC_MOD_DATA,
batch_size=2,
windows_per_image=10,
queue_length=10)
with self.test_session() as sess:
sampler.set_num_threads(2)
out = sess.run(sampler.pop_batch_op())
self.assertAllClose(out['image'].shape[1:], (8, 2, 256, 2))
sampler.close_all()
def test_2d_init(self):
sampler = UniformSampler(reader=get_2d_reader(),
window_sizes=MOD_2D_DATA,
batch_size=2,
windows_per_image=10,
queue_length=10)
with self.test_session() as sess:
sampler.set_num_threads(2)
out = sess.run(sampler.pop_batch_op())
self.assertAllClose(out['image'].shape, (2, 10, 9, 1))
sampler.close_all()
def test_3d_concentric_init(self):
sampler = UniformSampler(reader=get_concentric_window_reader(),
window_sizes=MULTI_WINDOW_DATA,
batch_size=2,
windows_per_image=10,
queue_length=10)
with self.test_session() as sess:
sampler.set_num_threads(2)
out = sess.run(sampler.pop_batch_op())
img_loc = out['image_location']
seg_loc = out['label_location']
self.assertTrue(np.all(img_loc[:, 0] == seg_loc[:, 0]))
self.assertTrue(np.all((img_loc - seg_loc)[:, 1:4] == [1, 1, 0]))
self.assertTrue(np.all((img_loc - seg_loc)[:, 4:] == [-2, -1, 1]))
self.assertAllClose(out['image'].shape, (2, 4, 10, 3, 1))
self.assertAllClose(out['label'].shape, (2, 7, 12, 2, 1))
sampler.close_all()
reader.add_preprocessing_layers( # add volume padding layer
[PadLayer(image_name=['MR'], border=volume_padding_size, mode='constant')])
###
# show 'volume' -- without window sampling
###
image_2d = ImageWindowDataset(reader)()['MR'][0, :, :, 0, 0, 0]
vis_coordinates(image_2d, saving_name='output/image.png')
###
# create & show uniform random samples
###
uniform_sampler = UniformSampler(reader,
spatial_window_size,
windows_per_image=100)
next_window = uniform_sampler.pop_batch_op()
coords = []
with tf.Session() as sess:
for _ in range(20):
uniform_windows = sess.run(next_window)
coords.append(uniform_windows['MR_location'])
coords = np.concatenate(coords, axis=0)
vis_coordinates(image_2d, coords, 'output/uniform.png')
###
# create & show all grid samples
###
grid_sampler = GridSampler(reader, spatial_window_size, window_border=border)
next_grid = grid_sampler.pop_batch_op()
coords = []
with tf.Session() as sess: