def __init__(self,
camera: pyredner.Camera,
shapes: List[pyredner.Shape] = [],
shape_id=dict(),
materials: List[pyredner.Material] = [],
area_lights: List[pyredner.AreaLight] = [],
objects: Optional[List[pyredner.Object]] = None,
envmap: Optional[pyredner.EnvironmentMap] = None):
self.camera = camera
self.envmap = envmap
self.shape_id = shape_id
if objects is None:
self.shapes = shapes
self.materials = materials
self.area_lights = area_lights
else:
# Convert objects to shapes/materials/lights
shapes = []
materials = []
area_lights = []
material_dict = {}
current_material_id = 0
for obj in objects:
mid = -1
if obj.material in material_dict:
mid = material_dict[obj.material]
else:
mid = current_material_id
material_dict[obj.material] = current_material_id
materials.append(obj.material)
current_material_id += 1
if obj.light_intensity is not None:
current_shape_id = len(shapes)
area_light = pyredner.AreaLight(
shape_id=current_shape_id,
intensity=obj.light_intensity,
two_sided=obj.light_two_sided)
area_lights.append(area_light)
shape = pyredner.Shape(vertices=obj.vertices,
indices=obj.indices,
material_id=mid,
uvs=obj.uvs,
normals=obj.normals,
uv_indices=obj.uv_indices,
normal_indices=obj.normal_indices,
colors=obj.colors)
shapes.append(shape)
self.shapes = shapes
#self.shape_id = shape_id
self.materials = materials
self.area_lights = area_lights
shape_light = pyredner.Shape(\
vertices = torch.tensor([[-1.0, -1.0, -7.0],
[ 2.0, -1.0, -7.0],
[-1.0, 1.0, -7.0],
[ 2.0, 1.0, -7.0]], device = pyredner.get_device()),
indices = torch.tensor([[0, 1, 2],[1, 3, 2]],
dtype = torch.int32, device = pyredner.get_device()),
uvs = None,
normals = None,
material_id = 0)
# The shape list of our scene contains two shapes:
shapes = [shape_diamond, shape_light]
light = pyredner.AreaLight(shape_id=1,
intensity=torch.tensor([200.0, 200.0, 200.0]))
area_lights = [light]
# Finally we construct our scene using all the variables we setup previously.
scene = pyredner.Scene(cam, shapes, materials, area_lights)
#shapes = []
#for _, mesh in mesh_list:
# assert(mesh.normal_indices is None)
# shapes.append(pyredner.Shape(\
# vertices = mesh.vertices,
# indices = mesh.indices,
# uvs = None,
# normals = mesh.normals,
# material_id=0))
# The previous tutorial used a mesh area light for the scene lighting,
def parse_shape(node, material_dict, shape_id, shape_group_dict=None):
if node.attrib['type'] == 'obj' or node.attrib['type'] == 'serialized':
print(node.attrib['id'])
to_world = torch.eye(4)
serialized_shape_id = 0
mat_id = -1
light_intensity = None
filename = ''
mat_name2id = {}
for child in node:
if 'name' in child.attrib:
if child.attrib['name'] == 'filename':
filename = child.attrib['value']
elif child.attrib['name'] == 'toWorld':
to_world = parse_transform(child)
elif child.attrib['name'] == 'shapeIndex':
serialized_shape_id = int(child.attrib['value'])
if child.tag == 'ref':
mat_id = material_dict[child.attrib['id']]
if 'name' in child.attrib.keys(
) and child.attrib['name'] != 'bsdf':
mat_name2id[child.attrib['name']] = child.attrib['id']
elif child.tag == 'bsdf':
#TODO hack! use default diffuse if countering internal declaration bsdf
mat_id = 0
# node_id, material = parse_material(child)
# if node_id is not None:
# material_dict[node_id] = len(materials)
# materials.append(material)
elif child.tag == 'emitter':
for grandchild in child:
if grandchild.attrib['name'] == 'radiance':
light_intensity = parse_vector(
grandchild.attrib['value'])
if light_intensity.shape[0] == 1:
light_intensity = torch.tensor(\
[light_intensity[0],
light_intensity[0],
light_intensity[0]])
if node.attrib['type'] == 'obj':
_, mesh_list, _ = pyredner.load_obj.load_obj_fast(
filename, is_load_mtl=False)
shape_list = []
for mesh in mesh_list:
mat_name = mesh[0]
vertices = mesh[1].vertices.cpu()
indices = mesh[1].indices.cpu()
uvs = mesh[1].uvs
normals = mesh[1].normals
if uvs is not None:
uvs = uvs.cpu()
if normals is not None:
normals = normals.cpu()
# Transform the vertices and normals
vertices = torch.cat(
(vertices, torch.ones(vertices.shape[0], 1)), dim=1)
vertices = vertices @ torch.transpose(to_world, 0, 1)
vertices = vertices / vertices[:, 3:4]
vertices = vertices[:, 0:3].contiguous()
if normals is not None:
normals = normals @ (torch.inverse(
torch.transpose(to_world, 0, 1))[:3, :3])
normals = normals.contiguous()
assert (vertices is not None)
assert (indices is not None)
lgt = None
if light_intensity is not None:
lgt = pyredner.AreaLight(shape_id, light_intensity)
if pyredner.get_use_gpu():
# Copy to GPU
vertices = vertices.cuda()
indices = indices.cuda()
if uvs is not None:
uvs = uvs.cuda()
if normals is not None:
normals = normals.cuda()
# Assign material
if mat_name != '' and mat_name is not None: # skip no material mesh
mat_id = material_dict[mat_name2id[mat_name]]
shape_list.append(
pyredner.Shape(vertices, indices, uvs, normals, mat_id))
return shape_list, lgt
else:
assert (node.attrib['type'] == 'serialized')
mitsuba_tri_mesh = redner.load_serialized(filename,
serialized_shape_id)
vertices = torch.from_numpy(mitsuba_tri_mesh.vertices)
indices = torch.from_numpy(mitsuba_tri_mesh.indices)
uvs = torch.from_numpy(mitsuba_tri_mesh.uvs)
normals = torch.from_numpy(mitsuba_tri_mesh.normals)
if uvs.shape[0] == 0:
uvs = None
if normals.shape[0] == 0:
normals = None
# Transform the vertices and normals
vertices = torch.cat((vertices, torch.ones(vertices.shape[0], 1)),
dim=1)
vertices = vertices @ torch.transpose(to_world, 0, 1)
vertices = vertices / vertices[:, 3:4]
vertices = vertices[:, 0:3].contiguous()
if normals is not None:
normals = normals @ (torch.inverse(
torch.transpose(to_world, 0, 1))[:3, :3])
normals = normals.contiguous()
assert (vertices is not None)
assert (indices is not None)
lgt = None
if light_intensity is not None:
lgt = pyredner.AreaLight(shape_id, light_intensity)
if pyredner.get_use_gpu():
# Copy to GPU
vertices = vertices.cuda()
indices = indices.cuda()
if uvs is not None:
uvs = uvs.cuda()
if normals is not None:
normals = normals.cuda()
return pyredner.Shape(vertices, indices, uvs, normals, mat_id), lgt
elif node.attrib['type'] == 'rectangle':
indices = torch.tensor([[0, 2, 1], [1, 2, 3]], dtype=torch.int32)
vertices = torch.tensor([[-1.0, -1.0, 0.0], [-1.0, 1.0, 0.0],
[1.0, -1.0, 0.0], [1.0, 1.0, 0.0]])
uvs = None
normals = None
to_world = torch.eye(4)
mat_id = -1
light_intensity = None
for child in node:
if 'name' in child.attrib:
if child.attrib['name'] == 'toWorld':
to_world = parse_transform(child)
if child.tag == 'ref':
mat_id = material_dict[child.attrib['id']]
elif child.tag == 'emitter':
for grandchild in child:
if grandchild.attrib['name'] == 'radiance':
light_intensity = parse_vector(
grandchild.attrib['value'])
if light_intensity.shape[0] == 1:
light_intensity = torch.tensor(\
[light_intensity[0],
light_intensity[0],
light_intensity[0]])
# Transform the vertices
# Transform the vertices and normals
vertices = torch.cat((vertices, torch.ones(vertices.shape[0], 1)),
dim=1)
vertices = vertices @ torch.transpose(to_world, 0, 1)
vertices = vertices / vertices[:, 3:4]
vertices = vertices[:, 0:3].contiguous()
if normals is not None:
normals = normals @ (torch.inverse(torch.transpose(to_world, 0,
1))[:3, :3])
normals = normals.contiguous()
assert (vertices is not None)
assert (indices is not None)
lgt = None
if light_intensity is not None:
lgt = pyredner.AreaLight(shape_id, light_intensity)
if pyredner.get_use_gpu():
# Copy to GPU
vertices = vertices.cuda()
indices = indices.cuda()
if uvs is not None:
uvs = uvs.cuda()
if normals is not None:
normals = normals.cuda()
return pyredner.Shape(vertices, indices, uvs, normals, mat_id), lgt
# Add instance support
# TODO (simply transform & create a new shape now)
elif node.attrib['type'] == 'instance':
shape = None
for child in node:
if 'name' in child.attrib:
if child.attrib['name'] == 'toWorld':
to_world = parse_transform(child)
if pyredner.get_use_gpu():
to_world = to_world.cuda()
if child.tag == 'ref':
shape_ = shape_group_dict[child.attrib['id']]
shape_list = []
for shape in list(shape_):
# transform instance
vertices = shape.vertices
normals = shape.normals
vector1 = torch.ones(vertices.shape[0], 1)
vertices = torch.cat(
(vertices,
vector1.cuda() if pyredner.get_use_gpu() else vector1),
dim=1)
vertices = vertices @ torch.transpose(to_world, 0, 1)
vertices = vertices / vertices[:, 3:4]
vertices = vertices[:, 0:3].contiguous()
if normals is not None:
normals = normals @ (torch.inverse(
torch.transpose(to_world, 0, 1))[:3, :3])
normals = normals.contiguous()
# assert(vertices is not None)
# assert(indices is not None)
# lgt = None
# if light_intensity is not None:
# lgt = pyredner.AreaLight(shape_id, light_intensity)
shape_list.append(
pyredner.Shape(vertices, shape.indices, shape.uvs, normals,
shape.material_id))
return shape_list, None
else:
print('Shape type {} is not supported!'.format(node.attrib['type']))
assert (False)
def parse_shape(node, material_dict, shape_id, device, shape_group_dict=None):
if node.attrib['type'] == 'obj' or node.attrib['type'] == 'serialized':
to_world = torch.eye(4)
serialized_shape_id = 0
mat_id = -1
light_intensity = None
filename = ''
max_smooth_angle = -1
for child in node:
if 'name' in child.attrib:
if child.attrib['name'] == 'filename':
filename = child.attrib['value']
elif child.attrib['name'] == 'toWorld':
to_world = parse_transform(child)
elif child.attrib['name'] == 'shapeIndex':
serialized_shape_id = int(child.attrib['value'])
elif child.attrib['name'] == 'maxSmoothAngle':
max_smooth_angle = float(child.attrib['value'])
if child.tag == 'ref':
mat_id = material_dict[child.attrib['id']]
elif child.tag == 'emitter':
for grandchild in child:
if grandchild.attrib['name'] == 'radiance':
light_intensity = parse_vector(
grandchild.attrib['value'])
if light_intensity.shape[0] == 1:
light_intensity = torch.tensor(\
[light_intensity[0],
light_intensity[0],
light_intensity[0]])
if node.attrib['type'] == 'obj':
# Load in CPU for rebuild_topology
_, mesh_list, _ = pyredner.load_obj(filename,
obj_group=False,
device=torch.device('cpu'))
vertices = mesh_list[0][1].vertices
indices = mesh_list[0][1].indices
uvs = mesh_list[0][1].uvs
normals = mesh_list[0][1].normals
uv_indices = mesh_list[0][1].uv_indices
normal_indices = mesh_list[0][1].normal_indices
else:
assert (node.attrib['type'] == 'serialized')
mitsuba_tri_mesh = redner.load_serialized(filename,
serialized_shape_id)
vertices = torch.from_numpy(mitsuba_tri_mesh.vertices)
indices = torch.from_numpy(mitsuba_tri_mesh.indices)
uvs = torch.from_numpy(mitsuba_tri_mesh.uvs)
normals = torch.from_numpy(mitsuba_tri_mesh.normals)
if uvs.shape[0] == 0:
uvs = None
if normals.shape[0] == 0:
normals = None
uv_indices = None # Serialized doesn't use different indices for UV & normal
normal_indices = None
# Transform the vertices and normals
vertices = torch.cat((vertices, torch.ones(vertices.shape[0], 1)),
dim=1)
vertices = vertices @ torch.transpose(to_world, 0, 1)
vertices = vertices / vertices[:, 3:4]
vertices = vertices[:, 0:3].contiguous()
if normals is not None:
normals = normals @ (torch.inverse(torch.transpose(to_world, 0,
1))[:3, :3])
normals = normals.contiguous()
assert (vertices is not None)
assert (indices is not None)
if max_smooth_angle >= 0:
if normals is None:
normals = torch.zeros_like(vertices)
new_num_vertices = redner.rebuild_topology(\
redner.float_ptr(vertices.data_ptr()),
redner.int_ptr(indices.data_ptr()),
redner.float_ptr(uvs.data_ptr() if uvs is not None else 0),
redner.float_ptr(normals.data_ptr() if normals is not None else 0),
redner.int_ptr(uv_indices.data_ptr() if uv_indices is not None else 0),
int(vertices.shape[0]),
int(indices.shape[0]),
max_smooth_angle)
print('Rebuilt topology, original vertices size: {}, new vertices size: {}'.format(\
int(vertices.shape[0]), new_num_vertices))
vertices.resize_(new_num_vertices, 3)
if uvs is not None:
uvs.resize_(new_num_vertices, 2)
if normals is not None:
normals.resize_(new_num_vertices, 3)
lgt = None
if light_intensity is not None:
lgt = pyredner.AreaLight(shape_id, light_intensity)
vertices = vertices.to(device)
indices = indices.to(device)
if uvs is not None:
uvs = uvs.to(device)
if normals is not None:
normals = normals.to(device)
if uv_indices is not None:
uv_indices = uv_indices.to(device)
if normal_indices is not None:
normal_indices = normal_indices.to(device)
return pyredner.Shape(vertices,
indices,
uvs=uvs,
normals=normals,
uv_indices=uv_indices,
normal_indices=normal_indices,
material_id=mat_id), lgt
elif node.attrib['type'] == 'rectangle':
indices = torch.tensor([[0, 2, 1], [1, 2, 3]], dtype=torch.int32)
vertices = torch.tensor([[-1.0, -1.0, 0.0], [-1.0, 1.0, 0.0],
[1.0, -1.0, 0.0], [1.0, 1.0, 0.0]])
uvs = None
normals = None
to_world = torch.eye(4)
mat_id = -1
light_intensity = None
for child in node:
if 'name' in child.attrib:
if child.attrib['name'] == 'toWorld':
to_world = parse_transform(child)
if child.tag == 'ref':
mat_id = material_dict[child.attrib['id']]
elif child.tag == 'emitter':
for grandchild in child:
if grandchild.attrib['name'] == 'radiance':
light_intensity = parse_vector(
grandchild.attrib['value'])
if light_intensity.shape[0] == 1:
light_intensity = torch.tensor(\
[light_intensity[0],
light_intensity[0],
light_intensity[0]])
# Transform the vertices
# Transform the vertices and normals
vertices = torch.cat((vertices, torch.ones(vertices.shape[0], 1)),
dim=1)
vertices = vertices @ torch.transpose(to_world, 0, 1)
vertices = vertices / vertices[:, 3:4]
vertices = vertices[:, 0:3].contiguous()
if normals is not None:
normals = normals @ (torch.inverse(torch.transpose(to_world, 0,
1))[:3, :3])
normals = normals.contiguous()
assert (vertices is not None)
assert (indices is not None)
lgt = None
if light_intensity is not None:
lgt = pyredner.AreaLight(shape_id, light_intensity)
vertices = vertices.to(device)
indices = indices.to(device)
if uvs is not None:
uvs = uvs.to(device)
if normals is not None:
normals = normals.to(device)
return pyredner.Shape(vertices,
indices,
uvs=uvs,
normals=normals,
material_id=mat_id), lgt
# Add instance support
# TODO (simply transform & create a new shape now)
elif node.attrib['type'] == 'instance':
shape = None
for child in node:
if 'name' in child.attrib:
if child.attrib['name'] == 'toWorld':
to_world = parse_transform(child)
if child.tag == 'ref':
shape = shape_group_dict[child.attrib['id']]
# transform instance
vertices = shape.vertices
normals = shape.normals
vector1 = torch.ones(vertices.shape[0], 1, device=vertices.device)
to_world = to_world.to(vertices.device)
vertices = torch.cat((vertices, vector1), dim=1)
vertices = vertices @ torch.transpose(to_world, 0, 1)
vertices = vertices / vertices[:, 3:4]
vertices = vertices[:, 0:3].contiguous()
if normals is not None:
normals = normals @ (torch.inverse(torch.transpose(to_world, 0,
1))[:3, :3])
normals = normals.contiguous()
# assert(vertices is not None)
# assert(indices is not None)
# lgt = None
# if light_intensity is not None:
# lgt = pyredner.AreaLight(shape_id, light_intensity)
return pyredner.Shape(vertices,
shape.indices,
uvs=shape.uvs,
normals=normals,
material_ids=shape.material_id), None
else:
print('Shape type {} is not supported!'.format(node.attrib['type']))
assert (False)
blocker_vertices = torch.tensor(\
[[-0.5,10.0,-0.5],[-0.5,10.0,0.5],[0.5,10.0,-0.5],[0.5,10.0,0.5]],
device = pyredner.get_device())
blocker_indices = torch.tensor([[0,1,2], [1,3,2]],
device = pyredner.get_device(), dtype = torch.int32)
shape_blocker = pyredner.Shape(blocker_vertices, blocker_indices, 0)
light_vertices = torch.tensor(\
[[-0.1,15,-0.1],[-0.1,15,0.1],[0.1,15,-0.1],[0.1,15,0.1]],
device = pyredner.get_device())
light_indices = torch.tensor([[0,2,1], [1,2,3]],
device = pyredner.get_device(), dtype = torch.int32)
shape_light = pyredner.Shape(light_vertices, light_indices, 1)
shapes = [shape_floor, shape_blocker, shape_light]
light_intensity = torch.tensor([5000.0, 5000.0, 5000.0])
# The first argument is the shape id of the light
light = pyredner.AreaLight(2, light_intensity)
area_lights = [light]
scene = pyredner.Scene(cam, shapes, materials, area_lights)
args = pyredner.RenderFunction.serialize_scene(\
scene = scene,
num_samples = 256,
max_bounces = 1)
# Alias of the render function
render = pyredner.RenderFunction.apply
# Render our target
img = render(0, *args)
pyredner.imwrite(img.cpu(), 'results/test_shadow_camera/target.exr')
pyredner.imwrite(img.cpu(), 'results/test_shadow_camera/target.png')
target = pyredner.imread('results/test_shadow_camera/target.exr')
if pyredner.get_use_gpu():
def parse_shape(node, material_dict, shape_id, shape_group_dict=None):
if node.attrib['type'] == 'obj' or node.attrib['type'] == 'serialized':
to_world = torch.eye(4)
serialized_shape_id = 0
mat_id = -1
light_intensity = None
filename = ''
for child in node:
if 'name' in child.attrib:
if child.attrib['name'] == 'filename':
filename = child.attrib['value']
elif child.attrib['name'] == 'toWorld':
to_world = parse_transform(child)
elif child.attrib['name'] == 'shapeIndex':
serialized_shape_id = int(child.attrib['value'])
if child.tag == 'ref':
mat_id = material_dict[child.attrib['id']]
elif child.tag == 'emitter':
for grandchild in child:
if grandchild.attrib['name'] == 'radiance':
light_intensity = parse_vector(
grandchild.attrib['value'])
if light_intensity.shape[0] == 1:
light_intensity = torch.tensor(\
[light_intensity[0],
light_intensity[0],
light_intensity[0]])
if node.attrib['type'] == 'obj':
_, mesh_list, _ = pyredner.load_obj(filename)
vertices = mesh_list[0][1].vertices.cpu()
indices = mesh_list[0][1].indices.cpu()
uvs = mesh_list[0][1].uvs
normals = mesh_list[0][1].normals
if uvs is not None:
uvs = uvs.cpu()
if normals is not None:
normals = normals.cpu()
else:
assert (node.attrib['type'] == 'serialized')
mitsuba_tri_mesh = redner.load_serialized(filename,
serialized_shape_id)
vertices = torch.from_numpy(mitsuba_tri_mesh.vertices)
indices = torch.from_numpy(mitsuba_tri_mesh.indices)
uvs = torch.from_numpy(mitsuba_tri_mesh.uvs)
normals = torch.from_numpy(mitsuba_tri_mesh.normals)
if uvs.shape[0] == 0:
uvs = None
if normals.shape[0] == 0:
normals = None
# Transform the vertices and normals
vertices = torch.cat((vertices, torch.ones(vertices.shape[0], 1)),
dim=1)
vertices = vertices @ torch.transpose(to_world, 0, 1)
vertices = vertices / vertices[:, 3:4]
vertices = vertices[:, 0:3].contiguous()
if normals is not None:
normals = normals @ (torch.inverse(torch.transpose(to_world, 0,
1))[:3, :3])
normals = normals.contiguous()
assert (vertices is not None)
assert (indices is not None)
lgt = None
if light_intensity is not None:
lgt = pyredner.AreaLight(shape_id, light_intensity)
if pyredner.get_use_gpu():
# Copy to GPU
vertices = vertices.cuda()
indices = indices.cuda()
if uvs is not None:
uvs = uvs.cuda()
if normals is not None:
normals = normals.cuda()
return pyredner.Shape(vertices, indices, uvs, normals, mat_id), lgt
elif node.attrib['type'] == 'rectangle':
indices = torch.tensor([[0, 2, 1], [1, 2, 3]], dtype=torch.int32)
vertices = torch.tensor([[-1.0, -1.0, 0.0], [-1.0, 1.0, 0.0],
[1.0, -1.0, 0.0], [1.0, 1.0, 0.0]])
uvs = None
normals = None
to_world = torch.eye(4)
mat_id = -1
light_intensity = None
for child in node:
if 'name' in child.attrib:
if child.attrib['name'] == 'toWorld':
to_world = parse_transform(child)
if child.tag == 'ref':
mat_id = material_dict[child.attrib['id']]
elif child.tag == 'emitter':
for grandchild in child:
if grandchild.attrib['name'] == 'radiance':
light_intensity = parse_vector(
grandchild.attrib['value'])
if light_intensity.shape[0] == 1:
light_intensity = torch.tensor(\
[light_intensity[0],
light_intensity[0],
light_intensity[0]])
# Transform the vertices
# Transform the vertices and normals
vertices = torch.cat((vertices, torch.ones(vertices.shape[0], 1)),
dim=1)
vertices = vertices @ torch.transpose(to_world, 0, 1)
vertices = vertices / vertices[:, 3:4]
vertices = vertices[:, 0:3].contiguous()
if normals is not None:
normals = normals @ (torch.inverse(torch.transpose(to_world, 0,
1))[:3, :3])
normals = normals.contiguous()
assert (vertices is not None)
assert (indices is not None)
lgt = None
if light_intensity is not None:
lgt = pyredner.AreaLight(shape_id, light_intensity)
if pyredner.get_use_gpu():
# Copy to GPU
vertices = vertices.cuda()
indices = indices.cuda()
if uvs is not None:
uvs = uvs.cuda()
if normals is not None:
normals = normals.cuda()
return pyredner.Shape(vertices, indices, uvs, normals, mat_id), lgt
# Add instance support
# TODO (simply transform & create a new shape now)
elif node.attrib['type'] == 'instance':
shape = None
for child in node:
if 'name' in child.attrib:
if child.attrib['name'] == 'toWorld':
to_world = parse_transform(child)
if pyredner.get_use_gpu():
to_world = to_world.cuda()
if child.tag == 'ref':
shape = shape_group_dict[child.attrib['id']]
# transform instance
vertices = shape.vertices
normals = shape.normals
vector1 = torch.ones(vertices.shape[0], 1)
vertices = torch.cat(
(vertices, vector1.cuda() if pyredner.get_use_gpu() else vector1),
dim=1)
vertices = vertices @ torch.transpose(to_world, 0, 1)
vertices = vertices / vertices[:, 3:4]
vertices = vertices[:, 0:3].contiguous()
if normals is not None:
normals = normals @ (torch.inverse(torch.transpose(to_world, 0,
1))[:3, :3])
normals = normals.contiguous()
# assert(vertices is not None)
# assert(indices is not None)
# lgt = None
# if light_intensity is not None:
# lgt = pyredner.AreaLight(shape_id, light_intensity)
return pyredner.Shape(vertices, shape.indices, shape.uvs, normals,
shape.material_id), None
else:
print('Shape type {} is not supported!'.format(node.attrib['type']))
assert (False)
for obj in range(1, num_iters):
target_obj1 = pyredner.load_obj('results/shadow_art/multitarget/' + step + '/iter_' + str(obj) + '.obj', return_objects=True)
target_obj1[0].material = pyredner.Material(diffuse_reflectance=torch.tensor([1.0, 1.0, 1.0]), two_sided=True)
target_obj1[0].normals = pyredner.compute_vertex_normal(target_obj1[0].vertices, target_obj1[0].indices)
shapes = []
shapes.append(target_obj1[0])
numShapes = len(shapes)
shapes.extend(lights)
area_lights = []
for i in range(numShapes, len(shapes)):
area_lights.append(pyredner.AreaLight(shape_id = numShapes, intensity = torch.tensor([light_intensity, light_intensity, light_intensity])))
area_lights.append(pyredner.AreaLight(shape_id = numShapes, intensity = torch.tensor([light_intensity*10, light_intensity*10, light_intensity*10])))
scene = pyredner.Scene(cam, objects = [shapes[0], shapes[1]],area_lights = [area_lights[0]], envmap = None)
scene_intense = pyredner.Scene(cam, objects = [shapes[0], shapes[1]], area_lights = [area_lights[1]], envmap = None)
target = pyredner.render_pathtracing(scene = [scene], num_samples=(512, 0), max_bounces=1)[0]
pyredner.imwrite(target.cpu(), 'results/shadow_art/high_res/' + step + '/' + str(obj) + '_0.png')
area_lights = []
for i in range(numShapes, len(shapes)):
area_lights.append(pyredner.AreaLight(shape_id = numShapes, intensity = torch.tensor([light_intensity, light_intensity, light_intensity])))
area_lights.append(pyredner.AreaLight(shape_id = numShapes, intensity = torch.tensor([light_intensity*10, light_intensity*10, light_intensity*10])))
shape0_vertices = shapes[0].vertices.clone()
shapes[0].vertices = \
vertices = mesh.vertices,
indices = mesh.indices,
material_id = 0,
uvs = mesh.uvs,
normals = mesh.normals,
uv_indices = mesh.uv_indices))
numShapes = len(shapes)
print("NUM SHAPES", numShapes)
shapes.extend(lights)
area_lights = []
for i in range(numShapes, len(shapes)):
area_lights.append(
pyredner.AreaLight(shape_id=numShapes,
intensity=torch.tensor([
lightIntensity, lightIntensity, lightIntensity
])))
area_lights.append(
pyredner.AreaLight(shape_id=numShapes,
intensity=torch.tensor([
lightIntensity * 10, lightIntensity * 10,
lightIntensity * 10
])))
# FOR SCENE DEBUGGING
envmap = pyredner.imread('sunsky.exr')
if pyredner.get_use_gpu():
envmap = envmap.cuda()
envmap = pyredner.EnvironmentMap(envmap)
envmap = None