def render(self, vertices, faces, textures):
# fill back
if self.fill_back:
faces = torch.cat(
[faces, faces[:, :, faces.new([2, 1, 0]).long()]], dim=1)
textures = torch.cat(
[textures, textures.permute(0, 1, 4, 3, 2, 5)], dim=1)
# lighting
faces_lighting = vertices_to_faces_th(vertices, faces)
textures = lighting_th(faces_lighting, textures,
self.light_intensity_ambient,
self.light_intensity_directional,
self.light_color_ambient,
self.light_color_directional,
self.light_direction)
# viewpoint transformation
if self.camera_mode == 'look_at':
vertices = look_at_th(vertices, self.eye)
elif self.camera_mode == 'look':
raise NotImplementedError
vertices = look(vertices, self.eye, self.camera_direction)
# perspective transformation
if self.perspective:
vertices = perspective_th(vertices, angle=self.viewing_angle)
# rasterization
faces = vertices_to_faces_th(vertices, faces)
images = self.rasterize_rgb(faces, textures)
return images
def test_forward_rgb_th_3():
"""Same silhouette as blender"""
# load teapot
vertices, faces, textures = utils.load_teapot_batch_th()
# Fill back by reversing face points order
faces = torch.cat([faces, faces[:, :, faces.new([2, 1, 0]).long()]], dim=1)
textures = torch.cat([textures, textures.permute(0, 1, 4, 3, 2, 5)], dim=1)
# Add lighting
light_intensity_ambient = 1
light_intensity_directional = 0
light_color_ambient = [1, 1, 1] # white
light_color_directional = [1, 1, 1] # white
light_direction = [0, 1, 0] # up-to-down
faces_lighting = vertices_to_faces_th(vertices, faces)
textures = lighting_th(faces_lighting, textures, light_intensity_ambient,
light_intensity_directional, light_color_ambient,
light_color_directional, light_direction)
faces_th = preprocess_th(vertices, faces, perspective=True)
rasterize_rgb_th = RasterizeRGB(256, 0.1, 100, 1e-3, [0, 0, 0])
images = rasterize_rgb_th(faces_th, textures)
image = images[2].cpu().numpy().mean(0)
# Extract silhouette from blender image
ref = scipy.misc.imread('./tests/data/teapot_blender.png')
ref = ref.astype('float32')
ref = (ref.min(-1) != 255).astype('float32')
scipy.misc.imsave('./tests/data/test_rasterize_rgb_th3.png', image)
assert np.mean(np.abs(ref - image)) < 1e-8
def test_backward_silhouette_th_2():
"""Backward if non-zero gradient is on a face."""
vertices = np.array([[0.8, 0.8, 1.], [-0.5, -0.8, 1.], [0.8, -0.8, 1.]])
faces = np.array([[0, 1, 2]])
textures = np.ones((faces.shape[0], 4, 4, 4, 3), 'float32')
pyi = 40
pxi = 50
grad_ref = np.array([
[0.98646867, 1.04628897, 0.],
[-1.03415668, -0.10403691, 0.],
[3.00094461, -1.55173182, 0.],
])
# Add lighting
light_intensity_ambient = 1
light_intensity_directional = 0
light_color_ambient = [1, 1, 1] # white
light_color_directional = [1, 1, 1] # white
light_direction = [0, 1, 0] # up-to-down
vertices, faces, textures, grad_ref = utils.to_minibatch_th(
(vertices, faces, textures, grad_ref))
faces_lighting = vertices_to_faces_th(vertices, faces)
textures = lighting_th(faces_lighting, textures, light_intensity_ambient,
light_intensity_directional, light_color_ambient,
light_color_directional, light_direction)
faces.requires_grad = True
vertices.requires_grad = True
faces_th = preprocess_th(vertices, faces, perspective=False)
rasterize_silhouettes_th = RasterizeRGB(64, 0.1, 100, 1e-3, [0, 0, 0])
images = rasterize_silhouettes_th(faces_th, textures)
images = images.mean(dim=1)
loss = torch.sum(torch.abs(images[:, pyi, pxi]))
loss.backward(retain_graph=True)
assert (vertices.grad - grad_ref).abs().mean() < 1e-3
def test_forward_rgb_th_2():
"""Different viewpoint"""
# load teapot
vertices, faces, textures = utils.load_teapot_batch_th()
# Fill back by reversing face points order
faces = torch.cat([faces, faces[:, :, faces.new([2, 1, 0]).long()]], dim=1)
textures = torch.cat([textures, textures.permute(0, 1, 4, 3, 2, 5)], dim=1)
# Add lighting
light_intensity_ambient = 0.5
light_intensity_directional = 0.5
light_color_ambient = [1, 1, 1] # white
light_color_directional = [1, 1, 1] # white
light_direction = [0, 1, 0] # up-to-down
faces_lighting = vertices_to_faces_th(vertices, faces)
textures = lighting_th(faces_lighting, textures, light_intensity_ambient,
light_intensity_directional, light_color_ambient,
light_color_directional, light_direction)
faces_th = preprocess_th(vertices,
faces,
perspective=True,
eye=[1, 1, -2.7])
rasterize_rgb_th = RasterizeRGB(256, 0.1, 100, 1e-3, [0, 0, 0])
images = rasterize_rgb_th(faces_th, textures)
image = images[2].cpu().numpy().transpose(1, 2, 0)
ref = scipy.misc.imread('./tests/data/test_rasterize2.png') / 255
scipy.misc.imsave('./tests/data/test_rasterize_rgb_th2.png', image)
assert np.mean(np.abs(ref - image)) < 1e-2
def test_lighting():
"""Test whether it is executable."""
faces = np.random.normal(size=(64, 16, 3, 3)).astype('float32')
textures = np.random.normal(size=(64, 16, 8, 8, 8, 3)).astype('float32')
lighted_textures = lighting(faces, textures)
textures_th = torch.Tensor(textures)
faces_th = torch.Tensor(faces)
lighted_textures_th = lighting_th(faces_th, textures_th)
mean_err = np.mean(
np.abs(lighted_textures.data - lighted_textures_th.numpy()))
assert mean_err < 1e-5