def test_backward_case1():
"""Backward if non-zero gradient is out of a face."""
vertices = [[0.8, 0.8, 1.], [0.0, -0.5, 1.], [0.2, -0.4, 1.]]
faces = [[0, 1, 2]]
pxi = 35
pyi = 25
grad_ref = [
[1.6725862, -0.26021874, 0.],
[1.41986704, -1.64284933, 0.],
[0., 0., 0.],
]
renderer = Renderer()
renderer.image_size = 64
renderer.anti_aliasing = False
renderer.perspective = False
renderer.light_intensity_ambient = 1.0
renderer.light_intensity_directional = 0.0
vertices = cp.array(vertices, 'float32')
faces = cp.array(faces, 'int32')
textures = cp.ones((faces.shape[0], 4, 4, 4, 3), 'float32')
grad_ref = cp.array(grad_ref, 'float32')
vertices, faces, textures, grad_ref = utils.to_minibatch(
(vertices, faces, textures, grad_ref))
vertices = chainer.Variable(vertices)
images = renderer.render(vertices, faces, textures)
images = cf.mean(images, axis=1)
loss = cf.sum(cf.absolute(images[:, pyi, pxi] - 1))
loss.backward()
chainer.testing.assert_allclose(vertices.grad, grad_ref, rtol=1e-2)
def test_backward_silhouette():
"""Backward if non-zero gradient is out of a face."""
grad_ref = [
[1.6725862, -0.26021874, 0.],
[1.41986704, -1.64284933, 0.],
[0., 0., 0.],
]
vertices = [[0.8, 0.8, 1.], [0.0, -0.5, 1.], [0.2, -0.4, 1.]]
faces = [[0, 1, 2]]
vertices = cp.array(vertices, 'float32')
faces = cp.array(faces, 'int32')
grad_ref = cp.array(grad_ref, 'float32')
vertices, faces, grad_ref = utils.to_minibatch((vertices, faces, grad_ref))
pxi = 35
pyi = 25
renderer = Renderer()
renderer.image_size = 64
renderer.anti_aliasing = False
renderer.fill_back = False
renderer.perspective = False
print(vertices.shape)
print(faces.shape)
vertices = chainer.Variable(vertices)
images = renderer.render_silhouettes(vertices, faces)
loss = cf.sum(cf.absolute(images[:, pyi, pxi] - 1))
loss.backward()
chainer.testing.assert_allclose(vertices.grad, grad_ref, rtol=1e-2)
def test_forward_ch_1():
"""Rendering a teapot without anti-aliasing."""
# load teapot
vertices, faces, textures = utils.load_teapot_batch()
# create renderer
renderer = Renderer()
renderer.image_size = 256
renderer.anti_aliasing = False
# render
images = renderer.render(vertices, faces, textures)
images = images.data.get()
image = images[2]
image = image.transpose((1, 2, 0))
scipy.misc.imsave('./tests/data/test_rasterize1.png', image)
def test_backward_silhouette_ch_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]])
pyi = 40
pxi = 50
grad_ref = np.array([
[0.98646867, 1.04628897, 0.],
[-1.03415668, -0.10403691, 0.],
[3.00094461, -1.55173182, 0.],
])
renderer = Renderer()
renderer.image_size = 64
renderer.anti_aliasing = False
renderer.perspective = False
# Prepare chainer inputs
vertices = cp.array(vertices, 'float32')
faces = cp.array(faces, 'int32')
grad_ref = cp.array(grad_ref, 'float32')
vertices, faces, grad_ref = utils.to_minibatch((vertices, faces, grad_ref))
vertices = chainer.Variable(vertices)
images = renderer.render_silhouettes(vertices, faces)
loss = cf.sum(cf.absolute(images[:, pyi, pxi]))
loss.backward()
chainer.testing.assert_allclose(vertices.grad, grad_ref, rtol=1e-2)
def __init__(self, filename_obj, filename_ref):
super(Model, self).__init__()
with self.init_scope():
# load .obj
vertices, faces = load_obj(filename_obj)
self.vertices = chainer.Parameter(vertices[None, :, :])
self.faces = faces[None, :, :]
# create textures
texture_size = 2
textures = np.ones((1, self.faces.shape[1], texture_size,
texture_size, texture_size, 3), 'float32')
self.textures = textures
# load reference image
self.image_ref = scipy.misc.imread(filename_ref).astype(
'float32').mean(-1) / 255.
# setup renderer
renderer = Renderer()
renderer.anti_aliasing = False
self.renderer = renderer
def test_forward_th_2():
"""Rendering a teapot without anti-aliasing."""
# load teapot
vertices, faces, textures = utils.load_teapot_batch_th()
# create renderer
renderer = Renderer()
renderer.image_size = 256
renderer.anti_aliasing = False
# render
images_th = renderer.render(cp.asarray(vertices.cpu().numpy()),
cp.asarray(faces.cpu().numpy()),
cp.asarray(textures.cpu().numpy()))
images = images_th.data.get()
image = images[2]
image = image.transpose((1, 2, 0))
scipy.misc.imsave('./tests/data/test_rasterize_th1.png', image)
ref = scipy.misc.imread('./tests/data/test_rasterize1.png')
ref = ref.astype('float32')
assert np.abs((ref / 255 - image)).mean() < 1e-3
def test_forward_th():
"""Whether a silhouette by neural renderer matches that by Blender."""
# load teapot
vertices, faces, textures = utils.load_teapot_batch()
vertices_th, faces_th, textures_th = utils.load_teapot_batch_th()
# create renderer
renderer_th = RendererTh()
renderer_th.image_size = 256
renderer_th.anti_aliasing = False
renderer = Renderer()
renderer.fill_back = False
renderer.image_size = 256
renderer.anti_aliasing = False
images = renderer.render_silhouettes(vertices, faces)
images_th = renderer.render_silhouettes(
cp.asarray(vertices_th.cpu().numpy()),
cp.asarray(faces_th.cpu().numpy()))
assert (images_th - images).data.get().sum() == 0
def test_forward_chainer():
"""Whether a silhouette by neural renderer matches that by Blender."""
# load teapot
vertices, faces, textures = utils.load_teapot_batch()
# create renderer
renderer = Renderer()
renderer.fill_back = False
renderer.image_size = 256
renderer.anti_aliasing = False
images = renderer.render_silhouettes(vertices, faces)
images = images.data.get()
image = images[2]
# load reference image by blender
ref = scipy.misc.imread('./tests/data/teapot_blender.png')
ref = ref.astype('float32')
ref = (ref.min(-1) != 255).astype('float32')
chainer.testing.assert_allclose(ref, image)