def test_rasterize_batch_view_only(self):
triangles = np.array(((0, 1, 2),), np.int32)
vertices, view_projection_matrix = _generate_vertices_and_view_matrices()
_, _, mask = rasterization_backend.rasterize(vertices[0], triangles,
view_projection_matrix,
(_IMAGE_WIDTH, _IMAGE_HEIGHT))
self.assertAllEqual(mask[0, ...], tf.ones_like(mask[0, ...]))
self.assertAllEqual(mask[1, ...], tf.zeros_like(mask[1, ...]))
def test_rasterize_batch_vertices_only(self):
triangles = np.array(((0, 1, 2),), np.int32)
vertices, view_projection_matrix = _generate_vertices_and_view_matrices()
_, _, mask = rasterization_backend.rasterize(vertices, triangles,
view_projection_matrix[0],
(_IMAGE_WIDTH, _IMAGE_HEIGHT))
self.assertAllEqual(mask[0, ...], tf.ones_like(mask[0, ...]))
gt_layer_1 = np.zeros((_IMAGE_HEIGHT, _IMAGE_WIDTH), np.float32)
gt_layer_1[_IMAGE_HEIGHT // 2:, _IMAGE_WIDTH // 2:] = 1.0
self.assertAllEqual(mask[1, ...], gt_layer_1)
def test_rasterize_batch_view_only(self):
triangles = np.array(((0, 1, 2), ), np.int32)
vertices, view_projection_matrix = _generate_vertices_and_view_matrices(
)
vertices = np.array([vertices[0], vertices[0]], dtype=np.float32)
predicted_fb = rasterization_backend.rasterize(
vertices, triangles, view_projection_matrix,
(_IMAGE_WIDTH, _IMAGE_HEIGHT))
self.assertAllEqual(predicted_fb.foreground_mask[0, ...],
tf.ones_like(predicted_fb.foreground_mask[0, ...]))
self.assertAllEqual(
predicted_fb.foreground_mask[1, ...],
tf.zeros_like(predicted_fb.foreground_mask[1, ...]))
def test_rasterize_batch_vertices_only(self):
triangles = np.array(((0, 1, 2), ), np.int32)
vertices, view_projection_matrix = _generate_vertices_and_view_matrices(
)
# Use just first view projection matrix.
view_projection_matrix = [
view_projection_matrix[0], view_projection_matrix[0]
]
predicted_fb = rasterization_backend.rasterize(
vertices, triangles, view_projection_matrix,
(_IMAGE_WIDTH, _IMAGE_HEIGHT))
mask = predicted_fb.foreground_mask
self.assertAllEqual(mask[0, ...], tf.ones_like(mask[0, ...]))
gt_layer_1 = np.zeros((_IMAGE_HEIGHT, _IMAGE_WIDTH, 1), np.float32)
gt_layer_1[_IMAGE_HEIGHT // 2:, _IMAGE_WIDTH // 2:, 0] = 1.0
self.assertAllEqual(mask[1, ...], gt_layer_1)
def _proxy_rasterize(vertices, triangles, view_projection_matrices):
return rasterization_backend.rasterize(vertices, triangles,
view_projection_matrices,
(_IMAGE_WIDTH, _IMAGE_HEIGHT))
def test_rasterize_preset(self):
camera_origin = (0.0, 0.0, 0.0)
camera_up = (0.0, 1.0, 0.0)
look_at_point = (0.0, 0.0, 1.0)
field_of_view = (60 * np.math.pi / 180, )
near_plane = (0.01, )
far_plane = (400.0, )
# Construct the view projection matrix.
model_to_eye_matrix = look_at.right_handed(camera_origin,
look_at_point, camera_up)
perspective_matrix = perspective.right_handed(
field_of_view, (float(_IMAGE_WIDTH) / float(_IMAGE_HEIGHT), ),
near_plane, far_plane)
view_projection_matrix = tf.linalg.matmul(perspective_matrix,
model_to_eye_matrix)
view_projection_matrix = tf.expand_dims(view_projection_matrix, axis=0)
depth = 1.0
vertices = np.array([[(-2.0 * _TRIANGLE_SIZE, 0.0, depth),
(0.0, _TRIANGLE_SIZE, depth), (0.0, 0.0, depth),
(0.0, -_TRIANGLE_SIZE, depth)]],
dtype=np.float32)
triangles = np.array(((1, 2, 0), (0, 2, 3)), np.int32)
predicted_fb = rasterization_backend.rasterize(
vertices, triangles, view_projection_matrix,
(_IMAGE_WIDTH, _IMAGE_HEIGHT))
with self.subTest(name="triangle_index"):
groundtruth_triangle_index = np.zeros(
(1, _IMAGE_HEIGHT, _IMAGE_WIDTH, 1), dtype=np.int32)
groundtruth_triangle_index[..., :_IMAGE_WIDTH // 2, 0] = 0
groundtruth_triangle_index[..., :_IMAGE_HEIGHT // 2,
_IMAGE_WIDTH // 2:, 0] = 1
self.assertAllEqual(groundtruth_triangle_index,
predicted_fb.triangle_id)
with self.subTest(name="mask"):
groundtruth_mask = np.ones((1, _IMAGE_HEIGHT, _IMAGE_WIDTH, 1),
dtype=np.int32)
groundtruth_mask[..., :_IMAGE_WIDTH // 2, 0] = 0
self.assertAllEqual(groundtruth_mask, predicted_fb.foreground_mask)
attributes = np.array(((1.0, 0.0, 0.0), (0.0, 1.0, 0.0),
(0.0, 0.0, 1.0))).astype(np.float32)
perspective_correct_interpolation = lambda geometry, pixels: glm.perspective_correct_interpolation( # pylint: disable=g-long-lambda,line-too-long
geometry, attributes, pixels, model_to_eye_matrix,
perspective_matrix,
np.array((_IMAGE_WIDTH, _IMAGE_HEIGHT)).astype(np.float32),
np.array((0.0, 0.0)).astype(np.float32))
with self.subTest(name="barycentric_coordinates_triangle_0"):
geometry_0 = tf.gather(vertices, triangles[0, :], axis=1)
pixels_0 = tf.transpose(grid.generate((3.5, 2.5), (6.5, 4.5),
(4, 3)),
perm=(1, 0, 2))
barycentrics_gt_0 = perspective_correct_interpolation(
geometry_0, pixels_0)
self.assertAllClose(barycentrics_gt_0,
predicted_fb.barycentrics.value[0, 2:, 3:, :],
atol=1e-3)
with self.subTest(name="barycentric_coordinates_triangle_1"):
geometry_1 = tf.gather(vertices, triangles[1, :], axis=1)
pixels_1 = tf.transpose(grid.generate((3.5, 0.5), (6.5, 1.5),
(4, 2)),
perm=(1, 0, 2))
barycentrics_gt_1 = perspective_correct_interpolation(
geometry_1, pixels_1)
self.assertAllClose(barycentrics_gt_1,
predicted_fb.barycentrics.value[0, 0:2, 3:, :],
atol=1e-3)
def _proxy_rasterize(vertices, triangles, view_projection_matrices):
return rasterization_backend.rasterize(vertices, triangles,
view_projection_matrices,
(_IMAGE_WIDTH, _IMAGE_HEIGHT),
_ENABLE_CULL_FACE, _NUM_LAYERS)