def test_dynamic_init(self):
sampler = UniformSampler(reader=get_dynamic_window_reader(),
data_param=DYNAMIC_MOD_DATA,
batch_size=2,
windows_per_image=10,
queue_length=10)
with self.test_session() as sess:
coordinator = tf.train.Coordinator()
sampler.run_threads(sess, coordinator, 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_dynamic_init(self):
sampler = UniformSampler(reader=get_dynamic_window_reader(),
data_param=DYNAMIC_MOD_DATA,
batch_size=2,
windows_per_image=10,
queue_length=10)
with self.test_session() as sess:
coordinator = tf.train.Coordinator()
sampler.run_threads(sess, coordinator, 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_3d_concentric_init(self):
sampler = UniformSampler(reader=get_concentric_window_reader(),
data_param=MULTI_WINDOW_DATA,
batch_size=2,
windows_per_image=10,
queue_length=10)
with self.test_session() as sess:
coordinator = tf.train.Coordinator()
sampler.run_threads(sess, coordinator, 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()
def test_3d_concentric_init(self):
sampler = UniformSampler(reader=get_concentric_window_reader(),
data_param=MULTI_WINDOW_DATA,
batch_size=2,
windows_per_image=10,
queue_length=10)
with self.test_session() as sess:
coordinator = tf.train.Coordinator()
sampler.run_threads(sess, coordinator, 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()