# Copyright (c) 2020-2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# NVIDIA CORPORATION, its affiliates and licensors retain all intellectual
# property and proprietary rights in and to this material, related
# documentation and any modifications thereto. Any use, reproduction,
# disclosure or distribution of this material and related documentation
# without an express license agreement from NVIDIA CORPORATION or
# its affiliates is strictly prohibited.
import torch
import nvdiffrast.torch as dr
from . import util
from . import renderutils as ru
from . import light
from .texture import Texture2D
# ==============================================================================================
# Helper functions
# ==============================================================================================
def interpolate(attr, rast, attr_idx, rast_db=None):
return dr.interpolate(attr.contiguous(), rast, attr_idx, rast_db=rast_db, diff_attrs=None if rast_db is None else 'all')
# ==============================================================================================
# pixel shader
# ==============================================================================================
def shade(
gb_pos,
gb_geometric_normal,
gb_normal,
gb_tangent,
gb_tex_pos,
gb_texc,
gb_texc_deriv,
w2c,
view_pos,
lgt,
material,
bsdf,
feat,
two_sided_shading,
delta_xy_interp=None,
dino_pred=None,
class_vector=None,
im_features_map=None,
mvp=None
):
################################################################################
# Texture lookups
################################################################################
perturbed_nrm = None
# Combined texture, used for MLPs because lookups are expensive
# all_tex_jitter = material.sample(gb_tex_pos + torch.normal(mean=0, std=0.01, size=gb_tex_pos.shape, device="cuda"), feat=feat)
if isinstance(material, Texture2D):
all_tex = material.sample(gb_texc, gb_texc_deriv)
elif material is not None:
if im_features_map is None:
all_tex = material.sample(gb_tex_pos, feat=feat)
else:
all_tex = material.sample(gb_tex_pos, feat=feat, feat_map=im_features_map, mvp=mvp, w2c=w2c, deform_xyz=gb_pos)
else:
all_tex = torch.ones(*gb_pos.shape[:-1], 9, device=gb_pos.device)
kd, ks, perturbed_nrm = all_tex[..., :3], all_tex[..., 3:6], all_tex[..., 6:9]
# Compute albedo (kd) gradient, used for material regularizer
# kd_grad = torch.sum(torch.abs(all_tex_jitter[..., :-6] - all_tex[..., :-6]), dim=-1, keepdim=True) /
if dino_pred is not None and class_vector is None:
# DOR: predive the dino value using x,y,z, we would concatenate the label vector.
# trained together, generated image as the supervision for the one-hot-vector.
dino_feat_im_pred = dino_pred.sample(gb_tex_pos)
# dino_feat_im_pred = dino_pred.sample(gb_tex_pos.detach())
if dino_pred is not None and class_vector is not None:
dino_feat_im_pred = dino_pred.sample(gb_tex_pos, feat=class_vector)
# else:
# kd_jitter = material['kd'].sample(gb_texc + torch.normal(mean=0, std=0.005, size=gb_texc.shape, device="cuda"), gb_texc_deriv)
# kd = material['kd'].sample(gb_texc, gb_texc_deriv)
# ks = material['ks'].sample(gb_texc, gb_texc_deriv)[..., 0:3] # skip alpha
# if 'normal' in material:
# perturbed_nrm = material['normal'].sample(gb_texc, gb_texc_deriv)
# kd_grad = torch.sum(torch.abs(kd_jitter[..., 0:3] - kd[..., 0:3]), dim=-1, keepdim=True) / 3
# Separate kd into alpha and color, default alpha = 1
# alpha = kd[..., 3:4] if kd.shape[-1] == 4 else torch.ones_like(kd[..., 0:1])
# kd = kd[..., 0:3]
alpha = torch.ones_like(kd[..., 0:1])
################################################################################
# Normal perturbation & normal bend
################################################################################
if material is None or isinstance(material, Texture2D) or not material.perturb_normal:
perturbed_nrm = None
gb_normal = ru.prepare_shading_normal(gb_pos, view_pos, perturbed_nrm, gb_normal, gb_tangent, gb_geometric_normal, two_sided_shading=two_sided_shading, opengl=True, use_python=True)
# if two_sided_shading:
# view_vec = util.safe_normalize(view_pos - gb_pos, -1)
# gb_normal = torch.where(torch.sum(gb_geometric_normal * view_vec, -1, keepdim=True) > 0, gb_geometric_normal, -gb_geometric_normal)
# else:
# gb_normal = gb_geometric_normal
b, h, w, _ = gb_normal.shape
cam_normal = util.safe_normalize(torch.matmul(gb_normal.view(b, -1, 3), w2c[:,:3,:3].transpose(2,1))).view(b, h, w, 3)
################################################################################
# Evaluate BSDF
################################################################################
assert bsdf is not None or material.bsdf is not None, "Material must specify a BSDF type"
bsdf = bsdf if bsdf is not None else material.bsdf
shading = None
if bsdf == 'pbr':
if isinstance(lgt, light.EnvironmentLight):
shaded_col = lgt.shade(gb_pos, gb_normal, kd, ks, view_pos, specular=True)
else:
assert False, "Invalid light type"
elif bsdf == 'diffuse':
if lgt is None:
shaded_col = kd
elif isinstance(lgt, light.EnvironmentLight):
shaded_col = lgt.shade(gb_pos, gb_normal, kd, ks, view_pos, specular=False)
# elif isinstance(lgt, light.DirectionalLight):
# shaded_col, shading = lgt.shade(feat, kd, cam_normal)
# else:
# assert False, "Invalid light type"
else:
shaded_col, shading = lgt.shade(feat, kd, cam_normal)
elif bsdf == 'normal':
shaded_col = (gb_normal + 1.0) * 0.5
elif bsdf == 'geo_normal':
shaded_col = (gb_geometric_normal + 1.0) * 0.5
elif bsdf == 'tangent':
shaded_col = (gb_tangent + 1.0) * 0.5
elif bsdf == 'kd':
shaded_col = kd
elif bsdf == 'ks':
shaded_col = ks
else:
assert False, "Invalid BSDF '%s'" % bsdf
# Return multiple buffers
buffers = {
'kd' : torch.cat((kd, alpha), dim=-1),
'shaded' : torch.cat((shaded_col, alpha), dim=-1),
# 'kd_grad' : torch.cat((kd_grad, alpha), dim=-1),
# 'occlusion' : torch.cat((ks[..., :1], alpha), dim=-1),
}
if dino_pred is not None:
buffers['dino_feat_im_pred'] = torch.cat((dino_feat_im_pred, alpha), dim=-1)
if delta_xy_interp is not None:
buffers['flow'] = torch.cat((delta_xy_interp, alpha), dim=-1)
if shading is not None:
buffers['shading'] = torch.cat((shading, alpha), dim=-1)
return buffers
# ==============================================================================================
# Render a depth slice of the mesh (scene), some limitations:
# - Single light
# - Single material
# ==============================================================================================
def render_layer(
rast,
rast_deriv,
mesh,
w2c,
view_pos,
material,
lgt,
resolution,
spp,
msaa,
bsdf,
feat,
prior_mesh,
two_sided_shading,
render_flow,
delta_xy=None,
dino_pred=None,
class_vector=None,
im_features_map=None,
mvp=None
):
full_res = [resolution[0]*spp, resolution[1]*spp]
if prior_mesh is None:
prior_mesh = mesh
################################################################################
# Rasterize
################################################################################
# Scale down to shading resolution when MSAA is enabled, otherwise shade at full resolution
if spp > 1 and msaa:
rast_out_s = util.scale_img_nhwc(rast, resolution, mag='nearest', min='nearest')
rast_out_deriv_s = util.scale_img_nhwc(rast_deriv, resolution, mag='nearest', min='nearest') * spp
else:
rast_out_s = rast
rast_out_deriv_s = rast_deriv
if render_flow:
delta_xy_interp, _ = interpolate(delta_xy, rast_out_s, mesh.t_pos_idx[0].int())
else:
delta_xy_interp = None
################################################################################
# Interpolate attributes
################################################################################
# Interpolate world space position
gb_pos, _ = interpolate(mesh.v_pos, rast_out_s, mesh.t_pos_idx[0].int())
# Compute geometric normals. We need those because of bent normals trick (for bump mapping)
v0 = mesh.v_pos[:, mesh.t_pos_idx[0, :, 0], :]
v1 = mesh.v_pos[:, mesh.t_pos_idx[0, :, 1], :]
v2 = mesh.v_pos[:, mesh.t_pos_idx[0, :, 2], :]
face_normals = util.safe_normalize(torch.cross(v1 - v0, v2 - v0, dim=-1))
num_faces = face_normals.shape[1]
face_normal_indices = (torch.arange(0, num_faces, dtype=torch.int64, device='cuda')[:, None]).repeat(1, 3)
gb_geometric_normal, _ = interpolate(face_normals, rast_out_s, face_normal_indices.int())
# Compute tangent space
assert mesh.v_nrm is not None and mesh.v_tng is not None
gb_normal, _ = interpolate(mesh.v_nrm, rast_out_s, mesh.t_nrm_idx[0].int())
gb_tangent, _ = interpolate(mesh.v_tng, rast_out_s, mesh.t_tng_idx[0].int()) # Interpolate tangents
# Texture coordinate
assert mesh.v_tex is not None
gb_texc, gb_texc_deriv = interpolate(mesh.v_tex, rast_out_s, mesh.t_tex_idx[0].int(), rast_db=rast_out_deriv_s)
################################################################################
# Shade
################################################################################
gb_tex_pos, _ = interpolate(prior_mesh.v_pos, rast_out_s, mesh.t_pos_idx[0].int())
buffers = shade(gb_pos, gb_geometric_normal, gb_normal, gb_tangent, gb_tex_pos, gb_texc, gb_texc_deriv, w2c, view_pos, lgt, material, bsdf, feat=feat, two_sided_shading=two_sided_shading, delta_xy_interp=delta_xy_interp, dino_pred=dino_pred, class_vector=class_vector, im_features_map=im_features_map, mvp=mvp)
################################################################################
# Prepare output
################################################################################
# Scale back up to visibility resolution if using MSAA
if spp > 1 and msaa:
for key in buffers.keys():
buffers[key] = util.scale_img_nhwc(buffers[key], full_res, mag='nearest', min='nearest')
# Return buffers
return buffers
# ==============================================================================================
# Render a depth peeled mesh (scene), some limitations:
# - Single light
# - Single material
# ==============================================================================================
def render_mesh(
ctx,
mesh,
mtx_in,
w2c,
view_pos,
material,
lgt,
resolution,
spp = 1,
num_layers = 1,
msaa = False,
background = None,
bsdf = None,
feat = None,
prior_mesh = None,
two_sided_shading = True,
render_flow = False,
dino_pred = None,
class_vector = None,
num_frames = None,
im_features_map = None
):
def prepare_input_vector(x):
x = torch.tensor(x, dtype=torch.float32, device='cuda') if not torch.is_tensor(x) else x
return x[:, None, None, :] if len(x.shape) == 2 else x
def composite_buffer(key, layers, background, antialias):
accum = background
for buffers, rast in reversed(layers):
alpha = (rast[..., -1:] > 0).float() * buffers[key][..., -1:]
accum = torch.lerp(accum, torch.cat((buffers[key][..., :-1], torch.ones_like(buffers[key][..., -1:])), dim=-1), alpha)
if antialias:
accum = dr.antialias(accum.contiguous(), rast, v_pos_clip, mesh.t_pos_idx[0].int())
return accum
assert mesh.t_pos_idx.shape[1] > 0, "Got empty training triangle mesh (unrecoverable discontinuity)"
assert background is None or (background.shape[1] == resolution[0] and background.shape[2] == resolution[1])
full_res = [resolution[0] * spp, resolution[1] * spp]
# Convert numpy arrays to torch tensors
mtx_in = torch.tensor(mtx_in, dtype=torch.float32, device='cuda') if not torch.is_tensor(mtx_in) else mtx_in
view_pos = prepare_input_vector(view_pos) # Shape: (B, 1, 1, 3)
# clip space transform
v_pos_clip = ru.xfm_points(mesh.v_pos, mtx_in, use_python=True)
# render flow
if render_flow:
v_pos_clip2 = v_pos_clip[..., :2] / v_pos_clip[..., -1:]
v_pos_clip2 = v_pos_clip2.view(-1, num_frames, *v_pos_clip2.shape[1:])
delta_xy = v_pos_clip2[:, 1:] - v_pos_clip2[:, :-1]
delta_xy = torch.cat([delta_xy, torch.zeros_like(delta_xy[:, :1])], dim=1)
delta_xy = delta_xy.view(-1, *delta_xy.shape[2:])
else:
delta_xy = None
# Render all layers front-to-back
layers = []
with dr.DepthPeeler(ctx, v_pos_clip, mesh.t_pos_idx[0].int(), full_res) as peeler:
for _ in range(num_layers):
rast, db = peeler.rasterize_next_layer()
rendered = render_layer(rast, db, mesh, w2c, view_pos, material, lgt, resolution, spp, msaa, bsdf, feat=feat, prior_mesh=prior_mesh, two_sided_shading=two_sided_shading, render_flow=render_flow, delta_xy=delta_xy, dino_pred=dino_pred, class_vector=class_vector, im_features_map=im_features_map, mvp=mtx_in)
layers += [(rendered, rast)]
# Setup background
if background is not None:
if spp > 1:
background = util.scale_img_nhwc(background, full_res, mag='nearest', min='nearest')
background = torch.cat((background, torch.zeros_like(background[..., 0:1])), dim=-1)
else:
background = torch.zeros(1, full_res[0], full_res[1], 4, dtype=torch.float32, device='cuda')
# Composite layers front-to-back
out_buffers = {}
for key in layers[0][0].keys():
antialias = key in ['shaded', 'dino_feat_im_pred', 'flow']
bg = background if key in ['shaded'] else torch.zeros_like(layers[0][0][key])
accum = composite_buffer(key, layers, bg, antialias)
# Downscale to framebuffer resolution. Use avg pooling
out_buffers[key] = util.avg_pool_nhwc(accum, spp) if spp > 1 else accum
return out_buffers
# ==============================================================================================
# Render UVs
# ==============================================================================================
def render_uv(ctx, mesh, resolution, mlp_texture, feat=None, prior_shape=None):
# clip space transform
uv_clip = mesh.v_tex * 2.0 - 1.0
# pad to four component coordinate
uv_clip4 = torch.cat((uv_clip, torch.zeros_like(uv_clip[...,0:1]), torch.ones_like(uv_clip[...,0:1])), dim = -1)
# rasterize
rast, _ = dr.rasterize(ctx, uv_clip4, mesh.t_tex_idx[0].int(), resolution)
# Interpolate world space position
if prior_shape is not None:
gb_pos, _ = interpolate(prior_shape.v_pos, rast, mesh.t_pos_idx[0].int())
else:
gb_pos, _ = interpolate(mesh.v_pos, rast, mesh.t_pos_idx[0].int())
# Sample out textures from MLP
all_tex = mlp_texture.sample(gb_pos, feat=feat)
assert all_tex.shape[-1] == 9 or all_tex.shape[-1] == 10, "Combined kd_ks_normal must be 9 or 10 channels"
perturbed_nrm = all_tex[..., -3:]
return (rast[..., -1:] > 0).float(), all_tex[..., :-6], all_tex[..., -6:-3], util.safe_normalize(perturbed_nrm)