def test_two_triangle_layers(self):
"""Checks that two overlapping triangles are accumulated correctly."""
if self._backend == rasterization_backend.RasterizationBackends.OPENGL:
self.skipTest(
reason='OpenGL rasterizer only supports single layer.')
image_width = 32
image_height = 32
vertices = tf.constant(
[[[-0.2, -0.2, 0], [0.5, -0.2, 0], [0.5, 0.5, 0], [0.2, -0.2, 0.5],
[-0.5, -0.2, 0.5], [-0.5, 0.5, 0.5]]],
dtype=tf.float32)
triangles = [[0, 1, 2], [3, 5, 4]]
colors = tf.constant(
[[[0, 1.0, 0, 1.0], [0, 1.0, 0, 1.0], [0, 1.0, 0, 1.0],
[1.0, 0, 0, 1.0], [1.0, 0, 0, 1.0], [1.0, 0, 0, 1.0]]],
dtype=tf.float32)
composite, _, normalized_layers = splat.rasterize_then_splat(
vertices,
triangles, {'color': colors},
rasterization_test_utils.get_identity_view_projection_matrix(),
(image_height, image_width),
lambda x: x['color'],
num_layers=2,
return_extra_buffers=True,
backend=self._backend)
baseline_image = rasterization_test_utils.load_baseline_image(
'Two_Triangles_Splat_Composite.png')
baseline_image = tf.image.resize(baseline_image,
(image_height, image_width))
images_near, error_message = rasterization_test_utils.compare_images(
self, baseline_image, composite)
self.assertTrue(images_near, msg=error_message)
for i in range(3):
baseline_image = rasterization_test_utils.load_baseline_image(
'Two_Triangles_Splat_Layer_{}.png'.format(i))
image = normalized_layers[:, i, ...]
image = tf.image.resize(
image, (512, 512),
method=tf.image.ResizeMethod.NEAREST_NEIGHBOR)
images_near, error_message = rasterization_test_utils.compare_images(
self, baseline_image, image)
self.assertTrue(images_near, msg=error_message)
def test_renders_colored_cube_multilayer(self, num_layers):
"""Renders a simple colored cube with multiple layers."""
rasterized = rasterization_backend.rasterize(
self.cube_vertex_positions,
self.cube_triangles,
self.projection, (self.image_width, self.image_height),
num_layers=num_layers,
enable_cull_face=False,
backend=rasterization_backend.RasterizationBackends.CPU)
vertex_rgb = (self.cube_vertex_positions * 0.5 + 0.5)
vertex_rgba = tf.concat([vertex_rgb, tf.ones([1, 8, 1])], axis=-1)
rendered = interpolate.interpolate_vertex_attribute(
vertex_rgba, rasterized).value
image_shape = [1] + rendered.shape[2:]
for layer_index in range(num_layers):
baseline_image = rasterization_test_utils.load_baseline_image(
'Unlit_Cube_{}_{}.png'.format(0, layer_index), image_shape)
images_near, error_message = rasterization_test_utils.compare_images(
self, baseline_image, rendered[:, layer_index, ...])
self.assertTrue(images_near, msg=error_message)
def test_renders_colored_cube(self):
"""Renders a simple colored cube."""
num_layers = 1
rasterized = rasterization_backend.rasterize(
self.cube_vertex_positions,
self.cube_triangles,
self.projection, (self.image_width, self.image_height),
num_layers=num_layers,
enable_cull_face=False,
backend=rasterization_backend.RasterizationBackends.CPU)
vertex_rgb = (self.cube_vertex_positions * 0.5 + 0.5)
vertex_rgba = tf.concat([vertex_rgb, tf.ones([1, 8, 1])], axis=-1)
rendered = interpolate.interpolate_vertex_attribute(vertex_rgba,
rasterized).value
baseline_image = rasterization_test_utils.load_baseline_image(
'Unlit_Cube_0_0.png', rendered.shape)
images_near, error_message = rasterization_test_utils.compare_images(
self, baseline_image, rendered)
self.assertTrue(images_near, msg=error_message)
def test_render_simple_triangle(self):
"""Directly renders a rasterized triangle's barycentric coordinates."""
w_vector = tf.constant([1.0, 1.0, 1.0], dtype=tf.float32)
clip_init = tf.constant(
[[[-0.5, -0.5, 0.8], [0.0, 0.5, 0.3], [0.5, -0.5, 0.3]]],
dtype=tf.float32)
clip_coordinates = clip_init * tf.reshape(w_vector, [1, 3, 1])
triangles = tf.constant([[0, 1, 2]], dtype=tf.int32)
face_culling_enabled = False
framebuffer = rasterization_backend.rasterize(
clip_coordinates, triangles, tf.eye(4, batch_shape=[1]),
(self.IMAGE_WIDTH, self.IMAGE_HEIGHT), face_culling_enabled,
self._num_layers, self._backend).layer(0)
ones_image = tf.ones([1, self.IMAGE_HEIGHT, self.IMAGE_WIDTH, 1])
rendered_coordinates = tf.concat(
[framebuffer.barycentrics.value, ones_image], axis=-1)
baseline_image = rasterization_test_utils.load_baseline_image(
'Simple_Triangle.png', rendered_coordinates.shape)
images_near, error_message = rasterization_test_utils.compare_images(
self, baseline_image, rendered_coordinates)
self.assertTrue(images_near, msg=error_message)