Spaces:
Running
on
L40S
Running
on
L40S
# -*- coding: utf-8 -*- | |
# Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. (MPG) is | |
# holder of all proprietary rights on this computer program. | |
# You can only use this computer program if you have closed | |
# a license agreement with MPG or you get the right to use the computer | |
# program from someone who is authorized to grant you that right. | |
# Any use of the computer program without a valid license is prohibited and | |
# liable to prosecution. | |
# | |
# Copyright©2019 Max-Planck-Gesellschaft zur Förderung | |
# der Wissenschaften e.V. (MPG). acting on behalf of its Max Planck Institute | |
# for Intelligent Systems. All rights reserved. | |
# | |
# Contact: ps-license@tuebingen.mpg.de | |
from lib.dataset.mesh_util import SMPLX | |
from lib.common.render_utils import face_vertices | |
import numpy as np | |
import lib.smplx as smplx | |
import trimesh | |
import torch | |
import torch.nn.functional as F | |
model_init_params = dict(gender='male', | |
model_type='smplx', | |
model_path=SMPLX().model_dir, | |
create_global_orient=False, | |
create_body_pose=False, | |
create_betas=False, | |
create_left_hand_pose=False, | |
create_right_hand_pose=False, | |
create_expression=False, | |
create_jaw_pose=False, | |
create_leye_pose=False, | |
create_reye_pose=False, | |
create_transl=False, | |
num_pca_comps=12) | |
def get_smpl_model(model_type, gender): | |
return smplx.create(**model_init_params) | |
def normalization(data): | |
_range = np.max(data) - np.min(data) | |
return ((data - np.min(data)) / _range) | |
def sigmoid(x): | |
z = 1 / (1 + np.exp(-x)) | |
return z | |
def load_fit_body(fitted_path, | |
scale, | |
smpl_type='smplx', | |
smpl_gender='neutral', | |
noise_dict=None): | |
param = np.load(fitted_path, allow_pickle=True) | |
for key in param.keys(): | |
param[key] = torch.as_tensor(param[key]) | |
smpl_model = get_smpl_model(smpl_type, smpl_gender) | |
model_forward_params = dict(betas=param['betas'], | |
global_orient=param['global_orient'], | |
body_pose=param['body_pose'], | |
left_hand_pose=param['left_hand_pose'], | |
right_hand_pose=param['right_hand_pose'], | |
jaw_pose=param['jaw_pose'], | |
leye_pose=param['leye_pose'], | |
reye_pose=param['reye_pose'], | |
expression=param['expression'], | |
return_verts=True) | |
if noise_dict is not None: | |
model_forward_params.update(noise_dict) | |
smpl_out = smpl_model(**model_forward_params) | |
smpl_verts = ( | |
(smpl_out.vertices[0] * param['scale'] + param['translation']) * | |
scale).detach() | |
smpl_joints = ( | |
(smpl_out.joints[0] * param['scale'] + param['translation']) * | |
scale).detach() | |
smpl_mesh = trimesh.Trimesh(smpl_verts, | |
smpl_model.faces, | |
process=False, | |
maintain_order=True) | |
return smpl_mesh, smpl_joints | |
def load_ori_fit_body(fitted_path, smpl_type='smplx', smpl_gender='neutral'): | |
param = np.load(fitted_path, allow_pickle=True) | |
for key in param.keys(): | |
param[key] = torch.as_tensor(param[key]) | |
smpl_model = get_smpl_model(smpl_type, smpl_gender) | |
model_forward_params = dict(betas=param['betas'], | |
global_orient=param['global_orient'], | |
body_pose=param['body_pose'], | |
left_hand_pose=param['left_hand_pose'], | |
right_hand_pose=param['right_hand_pose'], | |
jaw_pose=param['jaw_pose'], | |
leye_pose=param['leye_pose'], | |
reye_pose=param['reye_pose'], | |
expression=param['expression'], | |
return_verts=True) | |
smpl_out = smpl_model(**model_forward_params) | |
smpl_verts = smpl_out.vertices[0].detach() | |
smpl_mesh = trimesh.Trimesh(smpl_verts, | |
smpl_model.faces, | |
process=False, | |
maintain_order=True) | |
return smpl_mesh | |
def save_obj_mesh(mesh_path, verts, faces): | |
file = open(mesh_path, 'w') | |
for v in verts: | |
file.write('v %.4f %.4f %.4f\n' % (v[0], v[1], v[2])) | |
for f in faces: | |
f_plus = f + 1 | |
file.write('f %d %d %d\n' % (f_plus[0], f_plus[1], f_plus[2])) | |
file.close() | |
# https://github.com/ratcave/wavefront_reader | |
def read_mtlfile(fname): | |
materials = {} | |
with open(fname) as f: | |
lines = f.read().splitlines() | |
for line in lines: | |
if line: | |
split_line = line.strip().split(' ', 1) | |
if len(split_line) < 2: | |
continue | |
prefix, data = split_line[0], split_line[1] | |
if 'newmtl' in prefix: | |
material = {} | |
materials[data] = material | |
elif materials: | |
if data: | |
split_data = data.strip().split(' ') | |
# assume texture maps are in the same level | |
# WARNING: do not include space in your filename!! | |
if 'map' in prefix: | |
material[prefix] = split_data[-1].split('\\')[-1] | |
elif len(split_data) > 1: | |
material[prefix] = tuple(float(d) for d in split_data) | |
else: | |
try: | |
material[prefix] = int(data) | |
except ValueError: | |
material[prefix] = float(data) | |
return materials | |
def load_obj_mesh_mtl(mesh_file): | |
vertex_data = [] | |
norm_data = [] | |
uv_data = [] | |
face_data = [] | |
face_norm_data = [] | |
face_uv_data = [] | |
# face per material | |
face_data_mat = {} | |
face_norm_data_mat = {} | |
face_uv_data_mat = {} | |
# current material name | |
mtl_data = None | |
cur_mat = None | |
if isinstance(mesh_file, str): | |
f = open(mesh_file, "r") | |
else: | |
f = mesh_file | |
for line in f: | |
if isinstance(line, bytes): | |
line = line.decode("utf-8") | |
if line.startswith('#'): | |
continue | |
values = line.split() | |
if not values: | |
continue | |
if values[0] == 'v': | |
v = list(map(float, values[1:4])) | |
vertex_data.append(v) | |
elif values[0] == 'vn': | |
vn = list(map(float, values[1:4])) | |
norm_data.append(vn) | |
elif values[0] == 'vt': | |
vt = list(map(float, values[1:3])) | |
uv_data.append(vt) | |
elif values[0] == 'mtllib': | |
mtl_data = read_mtlfile( | |
mesh_file.replace(mesh_file.split('/')[-1], values[1])) | |
elif values[0] == 'usemtl': | |
cur_mat = values[1] | |
elif values[0] == 'f': | |
# local triangle data | |
l_face_data = [] | |
l_face_uv_data = [] | |
l_face_norm_data = [] | |
# quad mesh | |
if len(values) > 4: | |
f = list( | |
map( | |
lambda x: int(x.split('/')[0]) if int(x.split('/')[0]) | |
< 0 else int(x.split('/')[0]) - 1, values[1:4])) | |
l_face_data.append(f) | |
f = list( | |
map( | |
lambda x: int(x.split('/')[0]) | |
if int(x.split('/')[0]) < 0 else int(x.split('/')[0]) - | |
1, [values[3], values[4], values[1]])) | |
l_face_data.append(f) | |
# tri mesh | |
else: | |
f = list( | |
map( | |
lambda x: int(x.split('/')[0]) if int(x.split('/')[0]) | |
< 0 else int(x.split('/')[0]) - 1, values[1:4])) | |
l_face_data.append(f) | |
# deal with texture | |
if len(values[1].split('/')) >= 2: | |
# quad mesh | |
if len(values) > 4: | |
f = list( | |
map( | |
lambda x: int(x.split('/')[1]) | |
if int(x.split('/')[1]) < 0 else int( | |
x.split('/')[1]) - 1, values[1:4])) | |
l_face_uv_data.append(f) | |
f = list( | |
map( | |
lambda x: int(x.split('/')[1]) | |
if int(x.split('/')[1]) < 0 else int( | |
x.split('/')[1]) - 1, | |
[values[3], values[4], values[1]])) | |
l_face_uv_data.append(f) | |
# tri mesh | |
elif len(values[1].split('/')[1]) != 0: | |
f = list( | |
map( | |
lambda x: int(x.split('/')[1]) | |
if int(x.split('/')[1]) < 0 else int( | |
x.split('/')[1]) - 1, values[1:4])) | |
l_face_uv_data.append(f) | |
# deal with normal | |
if len(values[1].split('/')) == 3: | |
# quad mesh | |
if len(values) > 4: | |
f = list( | |
map( | |
lambda x: int(x.split('/')[2]) | |
if int(x.split('/')[2]) < 0 else int( | |
x.split('/')[2]) - 1, values[1:4])) | |
l_face_norm_data.append(f) | |
f = list( | |
map( | |
lambda x: int(x.split('/')[2]) | |
if int(x.split('/')[2]) < 0 else int( | |
x.split('/')[2]) - 1, | |
[values[3], values[4], values[1]])) | |
l_face_norm_data.append(f) | |
# tri mesh | |
elif len(values[1].split('/')[2]) != 0: | |
f = list( | |
map( | |
lambda x: int(x.split('/')[2]) | |
if int(x.split('/')[2]) < 0 else int( | |
x.split('/')[2]) - 1, values[1:4])) | |
l_face_norm_data.append(f) | |
face_data += l_face_data | |
face_uv_data += l_face_uv_data | |
face_norm_data += l_face_norm_data | |
if cur_mat is not None: | |
if cur_mat not in face_data_mat.keys(): | |
face_data_mat[cur_mat] = [] | |
if cur_mat not in face_uv_data_mat.keys(): | |
face_uv_data_mat[cur_mat] = [] | |
if cur_mat not in face_norm_data_mat.keys(): | |
face_norm_data_mat[cur_mat] = [] | |
face_data_mat[cur_mat] += l_face_data | |
face_uv_data_mat[cur_mat] += l_face_uv_data | |
face_norm_data_mat[cur_mat] += l_face_norm_data | |
vertices = np.array(vertex_data) | |
faces = np.array(face_data) | |
norms = np.array(norm_data) | |
norms = normalize_v3(norms) | |
face_normals = np.array(face_norm_data) | |
uvs = np.array(uv_data) | |
face_uvs = np.array(face_uv_data) | |
out_tuple = (vertices, faces, norms, face_normals, uvs, face_uvs) | |
if cur_mat is not None and mtl_data is not None: | |
for key in face_data_mat: | |
face_data_mat[key] = np.array(face_data_mat[key]) | |
face_uv_data_mat[key] = np.array(face_uv_data_mat[key]) | |
face_norm_data_mat[key] = np.array(face_norm_data_mat[key]) | |
out_tuple += (face_data_mat, face_norm_data_mat, face_uv_data_mat, | |
mtl_data) | |
return out_tuple | |
def load_scan(mesh_file, with_normal=False, with_texture=False): | |
vertex_data = [] | |
norm_data = [] | |
uv_data = [] | |
face_data = [] | |
face_norm_data = [] | |
face_uv_data = [] | |
if isinstance(mesh_file, str): | |
f = open(mesh_file, "r") | |
else: | |
f = mesh_file | |
for line in f: | |
if isinstance(line, bytes): | |
line = line.decode("utf-8") | |
if line.startswith('#'): | |
continue | |
values = line.split() | |
if not values: | |
continue | |
if values[0] == 'v': | |
v = list(map(float, values[1:4])) | |
vertex_data.append(v) | |
elif values[0] == 'vn': | |
vn = list(map(float, values[1:4])) | |
norm_data.append(vn) | |
elif values[0] == 'vt': | |
vt = list(map(float, values[1:3])) | |
uv_data.append(vt) | |
elif values[0] == 'f': | |
# quad mesh | |
if len(values) > 4: | |
f = list(map(lambda x: int(x.split('/')[0]), values[1:4])) | |
face_data.append(f) | |
f = list( | |
map(lambda x: int(x.split('/')[0]), | |
[values[3], values[4], values[1]])) | |
face_data.append(f) | |
# tri mesh | |
else: | |
f = list(map(lambda x: int(x.split('/')[0]), values[1:4])) | |
face_data.append(f) | |
# deal with texture | |
if len(values[1].split('/')) >= 2: | |
# quad mesh | |
if len(values) > 4: | |
f = list(map(lambda x: int(x.split('/')[1]), values[1:4])) | |
face_uv_data.append(f) | |
f = list( | |
map(lambda x: int(x.split('/')[1]), | |
[values[3], values[4], values[1]])) | |
face_uv_data.append(f) | |
# tri mesh | |
elif len(values[1].split('/')[1]) != 0: | |
f = list(map(lambda x: int(x.split('/')[1]), values[1:4])) | |
face_uv_data.append(f) | |
# deal with normal | |
if len(values[1].split('/')) == 3: | |
# quad mesh | |
if len(values) > 4: | |
f = list(map(lambda x: int(x.split('/')[2]), values[1:4])) | |
face_norm_data.append(f) | |
f = list( | |
map(lambda x: int(x.split('/')[2]), | |
[values[3], values[4], values[1]])) | |
face_norm_data.append(f) | |
# tri mesh | |
elif len(values[1].split('/')[2]) != 0: | |
f = list(map(lambda x: int(x.split('/')[2]), values[1:4])) | |
face_norm_data.append(f) | |
vertices = np.array(vertex_data) | |
faces = np.array(face_data) - 1 | |
if with_texture and with_normal: | |
uvs = np.array(uv_data) | |
face_uvs = np.array(face_uv_data) - 1 | |
norms = np.array(norm_data) | |
if norms.shape[0] == 0: | |
norms = compute_normal(vertices, faces) | |
face_normals = faces | |
else: | |
norms = normalize_v3(norms) | |
face_normals = np.array(face_norm_data) - 1 | |
return vertices, faces, norms, face_normals, uvs, face_uvs | |
if with_texture: | |
uvs = np.array(uv_data) | |
face_uvs = np.array(face_uv_data) - 1 | |
return vertices, faces, uvs, face_uvs | |
if with_normal: | |
norms = np.array(norm_data) | |
norms = normalize_v3(norms) | |
face_normals = np.array(face_norm_data) - 1 | |
return vertices, faces, norms, face_normals | |
return vertices, faces | |
def normalize_v3(arr): | |
''' Normalize a numpy array of 3 component vectors shape=(n,3) ''' | |
lens = np.sqrt(arr[:, 0]**2 + arr[:, 1]**2 + arr[:, 2]**2) | |
eps = 0.00000001 | |
lens[lens < eps] = eps | |
arr[:, 0] /= lens | |
arr[:, 1] /= lens | |
arr[:, 2] /= lens | |
return arr | |
def compute_normal(vertices, faces): | |
# Create a zeroed array with the same type and shape as our vertices i.e., per vertex normal | |
norm = np.zeros(vertices.shape, dtype=vertices.dtype) | |
# Create an indexed view into the vertex array using the array of three indices for triangles | |
tris = vertices[faces] | |
# Calculate the normal for all the triangles, by taking the cross product of the vectors v1-v0, and v2-v0 in each triangle | |
n = np.cross(tris[::, 1] - tris[::, 0], tris[::, 2] - tris[::, 0]) | |
# n is now an array of normals per triangle. The length of each normal is dependent the vertices, | |
# we need to normalize these, so that our next step weights each normal equally. | |
normalize_v3(n) | |
# now we have a normalized array of normals, one per triangle, i.e., per triangle normals. | |
# But instead of one per triangle (i.e., flat shading), we add to each vertex in that triangle, | |
# the triangles' normal. Multiple triangles would then contribute to every vertex, so we need to normalize again afterwards. | |
# The cool part, we can actually add the normals through an indexed view of our (zeroed) per vertex normal array | |
norm[faces[:, 0]] += n | |
norm[faces[:, 1]] += n | |
norm[faces[:, 2]] += n | |
normalize_v3(norm) | |
return norm | |
def compute_normal_batch(vertices, faces): | |
bs, nv = vertices.shape[:2] | |
bs, nf = faces.shape[:2] | |
vert_norm = torch.zeros(bs * nv, 3).type_as(vertices) | |
tris = face_vertices(vertices, faces) | |
face_norm = F.normalize(torch.cross(tris[:, :, 1] - tris[:, :, 0], | |
tris[:, :, 2] - tris[:, :, 0]), | |
dim=-1) | |
faces = (faces + | |
(torch.arange(bs).type_as(faces) * nv)[:, None, None]).view( | |
-1, 3) | |
vert_norm[faces[:, 0]] += face_norm.view(-1, 3) | |
vert_norm[faces[:, 1]] += face_norm.view(-1, 3) | |
vert_norm[faces[:, 2]] += face_norm.view(-1, 3) | |
vert_norm = F.normalize(vert_norm, dim=-1).view(bs, nv, 3) | |
return vert_norm | |
# compute tangent and bitangent | |
def compute_tangent(vertices, faces, normals, uvs, faceuvs): | |
# NOTE: this could be numerically unstable around [0,0,1] | |
# but other current solutions are pretty freaky somehow | |
c1 = np.cross(normals, np.array([0, 1, 0.0])) | |
tan = c1 | |
normalize_v3(tan) | |
btan = np.cross(normals, tan) | |
# NOTE: traditional version is below | |
# pts_tris = vertices[faces] | |
# uv_tris = uvs[faceuvs] | |
# W = np.stack([pts_tris[::, 1] - pts_tris[::, 0], pts_tris[::, 2] - pts_tris[::, 0]],2) | |
# UV = np.stack([uv_tris[::, 1] - uv_tris[::, 0], uv_tris[::, 2] - uv_tris[::, 0]], 1) | |
# for i in range(W.shape[0]): | |
# W[i,::] = W[i,::].dot(np.linalg.inv(UV[i,::])) | |
# tan = np.zeros(vertices.shape, dtype=vertices.dtype) | |
# tan[faces[:,0]] += W[:,:,0] | |
# tan[faces[:,1]] += W[:,:,0] | |
# tan[faces[:,2]] += W[:,:,0] | |
# btan = np.zeros(vertices.shape, dtype=vertices.dtype) | |
# btan[faces[:,0]] += W[:,:,1] | |
# btan[faces[:,1]] += W[:,:,1] | |
# btan[faces[:,2]] += W[:,:,1] | |
# normalize_v3(tan) | |
# ndott = np.sum(normals*tan, 1, keepdims=True) | |
# tan = tan - ndott * normals | |
# normalize_v3(btan) | |
# normalize_v3(tan) | |
# tan[np.sum(np.cross(normals, tan) * btan, 1) < 0,:] *= -1.0 | |
return tan, btan | |