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| import os |
| import numpy as np |
| import torch |
|
|
| from src.models.geometry.rep_3d import util |
| from . import texture |
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| |
| |
| class Material(torch.nn.Module): |
| def __init__(self, mat_dict): |
| super(Material, self).__init__() |
| self.mat_keys = set() |
| for key in mat_dict.keys(): |
| self.mat_keys.add(key) |
| self[key] = mat_dict[key] |
|
|
| def __contains__(self, key): |
| return hasattr(self, key) |
|
|
| def __getitem__(self, key): |
| return getattr(self, key) |
| |
| def __setitem__(self, key, val): |
| self.mat_keys.add(key) |
| setattr(self, key, val) |
|
|
| def __delitem__(self, key): |
| self.mat_keys.remove(key) |
| delattr(self, key) |
|
|
| def keys(self): |
| return self.mat_keys |
|
|
| |
| |
| |
| @torch.no_grad() |
| def load_mtl(fn, clear_ks=True): |
| import re |
| mtl_path = os.path.dirname(fn) |
|
|
| |
| with open(fn, 'r') as f: |
| lines = f.readlines() |
|
|
| |
| materials = [] |
| for line in lines: |
| split_line = re.split(' +|\t+|\n+', line.strip()) |
| prefix = split_line[0].lower() |
| data = split_line[1:] |
| if 'newmtl' in prefix: |
| material = Material({'name' : data[0]}) |
| materials += [material] |
| elif materials: |
| if 'map_d' in prefix: |
| |
| material['d'] = torch.tensor(1.0, dtype=torch.float32, device='cuda') |
| elif 'map_ke' in prefix: |
| |
| material['Ke'] = torch.tensor([0.0, 0.0, 0.0], dtype=torch.float32, device='cuda') |
| elif 'bsdf' in prefix or 'map_kd' in prefix or 'map_ks' in prefix or 'bump' in prefix: |
| material[prefix] = data[0] |
| else: |
| material[prefix] = torch.tensor(tuple(float(d) for d in data), dtype=torch.float32, device='cuda') |
|
|
| |
| for mat in materials: |
| if not 'bsdf' in mat: |
| mat['bsdf'] = 'pbr' |
|
|
| if 'map_kd' in mat: |
| mat['kd'] = texture.load_texture2D(os.path.join(mtl_path, mat['map_kd'])) |
| else: |
| mat['kd'] = texture.Texture2D(mat['kd']) |
| |
| if 'map_ks' in mat: |
| mat['ks'] = texture.load_texture2D(os.path.join(mtl_path, mat['map_ks']), channels=3) |
| else: |
| mat['ks'] = texture.Texture2D(mat['ks']) |
|
|
| if 'bump' in mat: |
| mat['normal'] = texture.load_texture2D(os.path.join(mtl_path, mat['bump']), lambda_fn=lambda x: x * 2 - 1, channels=3) |
|
|
| |
| mat['kd'] = texture.srgb_to_rgb(mat['kd']) |
|
|
| if clear_ks: |
| |
| for mip in mat['ks'].getMips(): |
| mip[..., 0] = 0.0 |
|
|
| return materials |
|
|
| @torch.no_grad() |
| def save_mtl(fn, material): |
| folder = os.path.dirname(fn) |
| with open(fn, "w") as f: |
| f.write('newmtl defaultMat\n') |
| if material is not None: |
| f.write('bsdf %s\n' % material['bsdf']) |
| if 'kd' in material.keys(): |
| f.write('map_Kd texture_kd.png\n') |
| texture.save_texture2D(os.path.join(folder, 'texture_kd.png'), texture.rgb_to_srgb(material['kd'])) |
| if 'ks' in material.keys(): |
| f.write('map_Ks texture_ks.png\n') |
| texture.save_texture2D(os.path.join(folder, 'texture_ks.png'), material['ks']) |
| if 'normal' in material.keys(): |
| f.write('bump texture_n.png\n') |
| texture.save_texture2D(os.path.join(folder, 'texture_n.png'), material['normal'], lambda_fn=lambda x:(util.safe_normalize(x)+1)*0.5) |
| else: |
| f.write('Kd 1 1 1\n') |
| f.write('Ks 0 0 0\n') |
| f.write('Ka 0 0 0\n') |
| f.write('Tf 1 1 1\n') |
| f.write('Ni 1\n') |
| f.write('Ns 0\n') |
|
|
| |
| |
| |
|
|
| def _upscale_replicate(x, full_res): |
| x = x.permute(0, 3, 1, 2) |
| x = torch.nn.functional.pad(x, (0, full_res[1] - x.shape[3], 0, full_res[0] - x.shape[2]), 'replicate') |
| return x.permute(0, 2, 3, 1).contiguous() |
|
|
| def merge_materials(materials, texcoords, tfaces, mfaces): |
| assert len(materials) > 0 |
| for mat in materials: |
| assert mat['bsdf'] == materials[0]['bsdf'], "All materials must have the same BSDF (uber shader)" |
| assert ('normal' in mat) is ('normal' in materials[0]), "All materials must have either normal map enabled or disabled" |
|
|
| uber_material = Material({ |
| 'name' : 'uber_material', |
| 'bsdf' : materials[0]['bsdf'], |
| }) |
|
|
| textures = ['kd', 'ks', 'normal'] |
|
|
| |
| max_res = None |
| for mat in materials: |
| for tex in textures: |
| tex_res = np.array(mat[tex].getRes()) if tex in mat else np.array([1, 1]) |
| max_res = np.maximum(max_res, tex_res) if max_res is not None else tex_res |
| |
| |
| full_res = 2**np.ceil(np.log2(max_res * np.array([1, len(materials)]))).astype(int) |
|
|
| |
| for tex in textures: |
| if tex in materials[0]: |
| |
| tex_data_list = [] |
| for mat in materials: |
| if tex in mat: |
| scaled_tex = util.scale_img_nhwc(mat[tex].data, tuple(max_res)) |
| if scaled_tex.shape[-1] != 3: |
| scaled_tex = scaled_tex[:, :, :, :3] |
| tex_data_list.append(scaled_tex) |
| |
| tex_data = torch.cat(tuple(tex_data_list), dim=2) |
| tex_data = _upscale_replicate(tex_data, full_res) |
| uber_material[tex] = texture.Texture2D(tex_data) |
|
|
| |
| s_coeff = [full_res[0] / max_res[0], full_res[1] / max_res[1]] |
|
|
| |
| new_tverts = {} |
| new_tverts_data = [] |
| for fi in range(len(tfaces)): |
| matIdx = mfaces[fi] |
| for vi in range(3): |
| ti = tfaces[fi][vi] |
| if not (ti in new_tverts): |
| new_tverts[ti] = {} |
| if not (matIdx in new_tverts[ti]): |
| new_tverts_data.append([(matIdx + texcoords[ti][0]) / s_coeff[1], texcoords[ti][1] / s_coeff[0]]) |
| new_tverts[ti][matIdx] = len(new_tverts_data) - 1 |
| tfaces[fi][vi] = new_tverts[ti][matIdx] |
|
|
| return uber_material, new_tverts_data, tfaces |
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