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|
| | import math |
| | import torch |
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|
| | NORMAL_THRESHOLD = 0.1 |
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|
| | def _dot(x, y): |
| | return torch.sum(x*y, -1, keepdim=True) |
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|
| | def _reflect(x, n): |
| | return 2*_dot(x, n)*n - x |
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|
| | def _safe_normalize(x): |
| | return torch.nn.functional.normalize(x, dim = -1) |
| |
|
| | def _bend_normal(view_vec, smooth_nrm, geom_nrm, two_sided_shading): |
| | |
| | if two_sided_shading: |
| | smooth_nrm = torch.where(_dot(geom_nrm, view_vec) > 0, smooth_nrm, -smooth_nrm) |
| | geom_nrm = torch.where(_dot(geom_nrm, view_vec) > 0, geom_nrm, -geom_nrm) |
| |
|
| | t = torch.clamp(_dot(view_vec, smooth_nrm) / NORMAL_THRESHOLD, min=0, max=1) |
| | return torch.lerp(geom_nrm, smooth_nrm, t) |
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|
| | def _perturb_normal(perturbed_nrm, smooth_nrm, smooth_tng, opengl): |
| | smooth_bitang = _safe_normalize(torch.cross(smooth_tng, smooth_nrm)) |
| | if opengl: |
| | shading_nrm = smooth_tng * perturbed_nrm[..., 0:1] - smooth_bitang * perturbed_nrm[..., 1:2] + smooth_nrm * torch.clamp(perturbed_nrm[..., 2:3], min=0.0) |
| | else: |
| | shading_nrm = smooth_tng * perturbed_nrm[..., 0:1] + smooth_bitang * perturbed_nrm[..., 1:2] + smooth_nrm * torch.clamp(perturbed_nrm[..., 2:3], min=0.0) |
| | return _safe_normalize(shading_nrm) |
| |
|
| | def bsdf_prepare_shading_normal(pos, view_pos, perturbed_nrm, smooth_nrm, smooth_tng, geom_nrm, two_sided_shading, opengl): |
| | smooth_nrm = _safe_normalize(smooth_nrm) |
| | smooth_tng = _safe_normalize(smooth_tng) |
| | view_vec = _safe_normalize(view_pos - pos) |
| | shading_nrm = _perturb_normal(perturbed_nrm, smooth_nrm, smooth_tng, opengl) |
| | return _bend_normal(view_vec, shading_nrm, geom_nrm, two_sided_shading) |
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|
| | def bsdf_lambert(nrm, wi): |
| | return torch.clamp(_dot(nrm, wi), min=0.0) / math.pi |
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|
| | def bsdf_frostbite(nrm, wi, wo, linearRoughness): |
| | wiDotN = _dot(wi, nrm) |
| | woDotN = _dot(wo, nrm) |
| |
|
| | h = _safe_normalize(wo + wi) |
| | wiDotH = _dot(wi, h) |
| |
|
| | energyBias = 0.5 * linearRoughness |
| | energyFactor = 1.0 - (0.51 / 1.51) * linearRoughness |
| | f90 = energyBias + 2.0 * wiDotH * wiDotH * linearRoughness |
| | f0 = 1.0 |
| |
|
| | wiScatter = bsdf_fresnel_shlick(f0, f90, wiDotN) |
| | woScatter = bsdf_fresnel_shlick(f0, f90, woDotN) |
| | res = wiScatter * woScatter * energyFactor |
| | return torch.where((wiDotN > 0.0) & (woDotN > 0.0), res, torch.zeros_like(res)) |
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|
| | def bsdf_phong(nrm, wo, wi, N): |
| | dp_r = torch.clamp(_dot(_reflect(wo, nrm), wi), min=0.0, max=1.0) |
| | dp_l = torch.clamp(_dot(nrm, wi), min=0.0, max=1.0) |
| | return (dp_r ** N) * dp_l * (N + 2) / (2 * math.pi) |
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|
| | specular_epsilon = 1e-4 |
| |
|
| | def bsdf_fresnel_shlick(f0, f90, cosTheta): |
| | _cosTheta = torch.clamp(cosTheta, min=specular_epsilon, max=1.0 - specular_epsilon) |
| | return f0 + (f90 - f0) * (1.0 - _cosTheta) ** 5.0 |
| |
|
| | def bsdf_ndf_ggx(alphaSqr, cosTheta): |
| | _cosTheta = torch.clamp(cosTheta, min=specular_epsilon, max=1.0 - specular_epsilon) |
| | d = (_cosTheta * alphaSqr - _cosTheta) * _cosTheta + 1 |
| | return alphaSqr / (d * d * math.pi) |
| |
|
| | def bsdf_lambda_ggx(alphaSqr, cosTheta): |
| | _cosTheta = torch.clamp(cosTheta, min=specular_epsilon, max=1.0 - specular_epsilon) |
| | cosThetaSqr = _cosTheta * _cosTheta |
| | tanThetaSqr = (1.0 - cosThetaSqr) / cosThetaSqr |
| | res = 0.5 * (torch.sqrt(1 + alphaSqr * tanThetaSqr) - 1.0) |
| | return res |
| |
|
| | def bsdf_masking_smith_ggx_correlated(alphaSqr, cosThetaI, cosThetaO): |
| | lambdaI = bsdf_lambda_ggx(alphaSqr, cosThetaI) |
| | lambdaO = bsdf_lambda_ggx(alphaSqr, cosThetaO) |
| | return 1 / (1 + lambdaI + lambdaO) |
| |
|
| | def bsdf_pbr_specular(col, nrm, wo, wi, alpha, min_roughness=0.08): |
| | _alpha = torch.clamp(alpha, min=min_roughness*min_roughness, max=1.0) |
| | alphaSqr = _alpha * _alpha |
| |
|
| | h = _safe_normalize(wo + wi) |
| | woDotN = _dot(wo, nrm) |
| | wiDotN = _dot(wi, nrm) |
| | woDotH = _dot(wo, h) |
| | nDotH = _dot(nrm, h) |
| |
|
| | D = bsdf_ndf_ggx(alphaSqr, nDotH) |
| | G = bsdf_masking_smith_ggx_correlated(alphaSqr, woDotN, wiDotN) |
| | F = bsdf_fresnel_shlick(col, 1, woDotH) |
| |
|
| | w = F * D * G * 0.25 / torch.clamp(woDotN, min=specular_epsilon) |
| |
|
| | frontfacing = (woDotN > specular_epsilon) & (wiDotN > specular_epsilon) |
| | return torch.where(frontfacing, w, torch.zeros_like(w)) |
| |
|
| | def bsdf_pbr(kd, arm, pos, nrm, view_pos, light_pos, min_roughness, BSDF): |
| | wo = _safe_normalize(view_pos - pos) |
| | wi = _safe_normalize(light_pos - pos) |
| |
|
| | spec_str = arm[..., 0:1] |
| | roughness = arm[..., 1:2] |
| | metallic = arm[..., 2:3] |
| | ks = (0.04 * (1.0 - metallic) + kd * metallic) * (1 - spec_str) |
| | kd = kd * (1.0 - metallic) |
| |
|
| | if BSDF == 0: |
| | diffuse = kd * bsdf_lambert(nrm, wi) |
| | else: |
| | diffuse = kd * bsdf_frostbite(nrm, wi, wo, roughness) |
| | specular = bsdf_pbr_specular(ks, nrm, wo, wi, roughness*roughness, min_roughness=min_roughness) |
| | return diffuse + specular |
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