add cape normal calculation and uv conversion

This commit is contained in:
2023-06-30 23:27:43 +02:00
parent a831211c2d
commit 25d9814b70
2 changed files with 591 additions and 3 deletions
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import os
import sys
import glob
import tqdm
import math
import time
import random
import shutil
import collections
import argparse
import pickle
import numpy as np
import scipy as sp
import trimesh as tm
# import cmapy as cm
import tables as tb
import scipy.io as sio
import scipy.interpolate as spi
import matplotlib.pyplot as plt
import scipy.stats as stat
import cv2
import plotly.express as ex
import plotly.graph_objects as go
sys.path.append(os.path.dirname(os.path.abspath(__file__)) + '/..')
from data.cloth3d_io import read_garment_mask, read_garment_template, read_posed_garment_frame, loadInfo, read_posed_body_frame, read_posed_body, read_posed_garment, read_curvatures
from data.cloth3d_io import readPC2
os.environ["CUDA_VISIBLE_DEVICES"] = "6"
def convert_to_uv(res, m2uv, uv_map, verts, neighbours=10, mask=None, method='rbf', garment_uv_mask=None):
verts_uv = np.zeros((res * 2, res, 3))
uv_values = np.zeros((uv_map.shape[0], 3))
uv_values[m2uv[:, 0]] = verts
uv_values[m2uv[:, 1]] += verts
uv_values = uv_values[uv_map_mask[type], :] # add garment mask
uv_values /= uv_counter[type][:, np.newaxis]
return_garment_uv_mask = False
if mask is not None:
garment_mask = np.zeros((uv_map.shape[0]), dtype=bool)
garment_mask[m2uv[:, 0]] = mask
garment_mask[m2uv[:, 1]] += mask
garment_mask = garment_mask[uv_map_mask[type]] # add garment mask
else:
garment_mask = np.sum(uv_values, axis=-1) != 0
# test
verts_uv[uv_map_discreet_unique[type][:, 0], uv_map_discreet_unique[type][:, 1], :] = uv_values
# verts_uv_save = verts_uv.copy()
# garment_mask = np.sum(uv_values, axis=-1) != 0
unique_uv_values = uv_values[garment_mask, :]
uv_map_discreet_unique_unique = uv_map_discreet_unique[type][garment_mask, :]
rbf_dest_current = rbf_dest[type]
if garment_uv_mask is None and mask is not None:
garment_uv_mask = np.zeros((res * 2, res))
garment_uv_mask[uv_map_discreet_unique_unique[:, 0], uv_map_discreet_unique_unique[:, 1]] = 255
garment_uv_mask = cv2.morphologyEx(garment_uv_mask, cv2.MORPH_CLOSE, cv2.getStructuringElement(cv2.MORPH_RECT, (4 * 2 + 1, 4 * 2 + 1), (4, 4)), iterations=4)
garment_uv_mask_border = garment_uv_mask.astype(bool)
garment_uv_mask = cv2.dilate(garment_uv_mask, cv2.getStructuringElement(cv2.MORPH_RECT, (2 * 2 + 1, 2 * 2 + 1), (2, 2)), iterations=2).astype(bool)
garment_uv_mask_border = ~garment_uv_mask_border & garment_uv_mask
garment_uv_mask = garment_uv_mask * uv_mask[type][:,:,0]
rbf_dest_current = rbf_dest[type] * garment_uv_mask
return_garment_uv_mask = True
rbf_dest_current = np.nonzero(rbf_dest_current)
rbf_dest_current = np.array(rbf_dest_current).T
# uv_verts_uniq = np.array(np.nonzero(np.sum(verts_uv, axis=-1))).T
if method == 'rbf':
interpolator = spi.RBFInterpolator(y=uv_map_discreet_unique_unique, d=unique_uv_values, neighbors=neighbours, kernel='linear')
elif method == 'nearest':
interpolator = spi.NearestNDInterpolator(x=uv_map_discreet_unique_unique, y=unique_uv_values)
else:
raise NotImplementedError
final = interpolator(rbf_dest_current)
result = np.zeros((res * 2, res, 3))
# not sure, shouldn't be needed
# rbf_dest[:, [0,1]] = rbf_dest[:, [1, 0]]
result[rbf_dest_current[:, 0], rbf_dest_current[:, 1], :] = final
result[uv_map_discreet_unique[type][:, 0], uv_map_discreet_unique[type][:, 1], :] = uv_values
if garment_uv_mask is not None:
result = result * garment_uv_mask[:,:,np.newaxis]
if return_garment_uv_mask:
return result, garment_uv_mask, garment_uv_mask_border
else:
return result
def convert_to_uv_batch_body(res, m2uv, uv_map, verts, neighbours=15, mask=None, method='rbf', garment_uv_mask=None, garment_uv_mask_border=None):
batch = verts.shape[0]
verts_uv = np.zeros((batch, res * 2, res, 3))
uv_values = np.zeros((batch, uv_map.shape[0], 3))
uv_values[:, m2uv[:, 0]] = verts
uv_values[:, m2uv[:, 1]] += verts
uv_values = uv_values[:, uv_map_mask['non-skirt'], :]
uv_values /= uv_counter['non-skirt'][np.newaxis, :, np.newaxis]
return_garment_uv_mask = False
# test
verts_uv[:, uv_map_discreet_unique['non-skirt'][:, 0], uv_map_discreet_unique['non-skirt'][:, 1], :] = uv_values
if mask is not None:
garment_mask = np.zeros((uv_map.shape[0]), dtype=bool)
garment_mask[m2uv[:, 0]] = mask
garment_mask[m2uv[:, 1]] += mask
garment_mask = garment_mask[uv_map_mask['non-skirt']] # add garment mask
else:
garment_mask = np.sum(uv_values[0,:,:], axis=-1) != 0
unique_uv_values = uv_values[:, garment_mask, :]
uv_map_discreet_unique_unique = uv_map_discreet_unique['non-skirt'][garment_mask, :]
rbf_dest_current = rbf_dest['non-skirt']
# add back mesh vertices that are not part of the garment
uv_map_discreet_unique_unique_inv = uv_map_discreet_unique['non-skirt'][np.invert(garment_mask), :]
rbf_dest_fill = np.zeros((res * 2, res), dtype=bool)
rbf_dest_fill[uv_map_discreet_unique_unique_inv[:, 0], uv_map_discreet_unique_unique_inv[:, 1]] = True
if garment_uv_mask is None and mask is not None:
garment_uv_mask = np.zeros((res * 2, res))
garment_uv_mask[uv_map_discreet_unique_unique[:, 0], uv_map_discreet_unique_unique[:, 1]] = 255
garment_uv_mask = cv2.morphologyEx(garment_uv_mask, cv2.MORPH_CLOSE, cv2.getStructuringElement(cv2.MORPH_RECT, (2 * 2 + 1, 2 * 2 + 1), (2, 2)), iterations=4)
garment_uv_mask = cv2.dilate(garment_uv_mask, cv2.getStructuringElement(cv2.MORPH_RECT, (2 * 2 + 1, 2 * 2 + 1), (2, 2)), iterations=2).astype(bool)
return_garment_uv_mask = True
if garment_uv_mask is not None:
rbf_dest_current = (rbf_dest['non-skirt'] + rbf_dest_fill) * garment_uv_mask + garment_uv_mask_border
rbf_dest_current = np.nonzero(rbf_dest_current)
rbf_dest_current = np.array(rbf_dest_current).T
final = []
for i in range(batch):
print('processing frame: ' + str(i))
if method == 'rbf':
interpolator = spi.RBFInterpolator(y=uv_map_discreet_unique_unique, d=unique_uv_values[i,:,:], neighbors=neighbours, kernel='linear')
elif method == 'nearest':
interpolator = spi.NearestNDInterpolator(x=uv_map_discreet_unique_unique, y=unique_uv_values[i,:,:])
else:
raise NotImplementedError
result = np.zeros((res * 2, res, 3), np.float32)
result[rbf_dest_current[:, 0], rbf_dest_current[:, 1], :] = interpolator(rbf_dest_current)
result[uv_map_discreet_unique_unique[:, 0], uv_map_discreet_unique_unique[:, 1], :] = unique_uv_values[i,:,:]
if garment_uv_mask is not None:
result *= garment_uv_mask[:,:,np.newaxis]
final.append(result)
if return_garment_uv_mask:
return final, garment_uv_mask
else:
return final
def convert_to_uv_batch(res, m2uv, uv_map, verts, neighbours=15, mask=None, method='rbf', garment_uv_mask=None, garment_uv_mask_border=None, id=None):
batch = len(verts)
assert method == 'rbf'
assert mask is not None
garment_mask = np.zeros((uv_map.shape[0]), dtype=bool)
garment_mask[m2uv[:, 0]] = mask
garment_mask[m2uv[:, 1]] += mask
garment_mask = garment_mask[uv_map_mask[type]] # add garment mask
rbf_dest_current = rbf_dest[type]
# add back mesh vertices that are not part of the garment
uv_map_discreet_unique_unique_inv = uv_map_discreet_unique[type][np.invert(garment_mask), :]
rbf_dest_fill = np.zeros((res * 2, res), dtype=bool)
rbf_dest_fill[uv_map_discreet_unique_unique_inv[:, 0], uv_map_discreet_unique_unique_inv[:, 1]] = True
assert not (garment_uv_mask is None and mask is not None)
assert garment_uv_mask is not None
rbf_dest_current = (rbf_dest[type] + rbf_dest_fill) * garment_uv_mask + garment_uv_mask_border
rbf_dest_current = np.nonzero(rbf_dest_current)
rbf_dest_current = np.array(rbf_dest_current).T
out = []
for i in range(batch):
print('processing frame: ' + str(i))
uv_values = np.zeros((uv_map.shape[0], 3))
uv_values[m2uv[:, 0]] = verts[i]
uv_values[m2uv[:, 1]] += verts[i]
uv_values = uv_values[uv_map_mask[type], :]
uv_values /= uv_counter[type][:, np.newaxis]
unique_uv_values = uv_values[garment_mask, :]
uv_map_discreet_unique_unique = uv_map_discreet_unique[type][garment_mask, :]
interpolator = spi.RBFInterpolator(y=uv_map_discreet_unique_unique, d=unique_uv_values[:,:], neighbors=neighbours, kernel='linear')
result = np.zeros((res * 2, res, 3), np.float32)
result[rbf_dest_current[:, 0], rbf_dest_current[:, 1], :] = interpolator(rbf_dest_current)
result[uv_map_discreet_unique_unique[:, 0], uv_map_discreet_unique_unique[:, 1], :] = unique_uv_values[:,:]
if garment_uv_mask is not None:
result *= garment_uv_mask[:,:,np.newaxis]
out.append(result)
return out
def convert_to_uv_batch_label(res, m2uv, uv_map, values, neighbours=15, mask=None, method='rbf', garment_uv_mask=None, garment_uv_mask_border=None):
batch = values.shape[0]
values = (values + 1) * mask
values_uv = np.zeros((batch, res * 2, res))
missing = np.zeros((res * 2, res))
uv_values = np.zeros((batch, uv_map.shape[0]))
uv_values[:, m2uv[:, 0]] = values
uv_values[:, m2uv[:, 1]] = values
uv_values = uv_values[:, uv_map_mask]
return_garment_uv_mask = False
if mask is not None:
garment_mask = np.zeros((uv_map.shape[0]), dtype=bool)
garment_mask[m2uv[:, 0]] = mask
garment_mask[m2uv[:, 1]] += mask
garment_mask = garment_mask[uv_map_mask] # add garment mask
else:
raise Exception
# test
values_uv[:, uv_map_discreet_unique[:, 0], uv_map_discreet_unique[:, 1]] = uv_values
missing[uv_map_discreet_unique[:, 0], uv_map_discreet_unique[:, 1]] = (uv_values[0,:] == 0)
unique_uv_values = uv_values[:, garment_mask]
uv_map_discreet_unique_unique = uv_map_discreet_unique[garment_mask, :]
# rbf_dest_current = rbf_dest.astype(bool) + garment_uv_mask_border * uv_mask[:,:,0]
if garment_uv_mask is None and mask is not None:
garment_uv_mask = np.zeros((res * 2, res))
garment_uv_mask[uv_map_discreet_unique_unique[:, 0], uv_map_discreet_unique_unique[:, 1]] = 255
garment_uv_mask = cv2.morphologyEx(garment_uv_mask, cv2.MORPH_CLOSE, cv2.getStructuringElement(cv2.MORPH_RECT, (2 * 2 + 1, 2 * 2 + 1), (2, 2)), iterations=4)
garment_uv_mask = cv2.dilate(garment_uv_mask, cv2.getStructuringElement(cv2.MORPH_RECT, (2 * 2 + 1, 2 * 2 + 1), (2, 2)), iterations=2).astype(bool)
return_garment_uv_mask = True
rbf_dest_current = rbf_dest * garment_uv_mask + missing * garment_uv_mask
rbf_dest_current = np.nonzero(rbf_dest_current)
rbf_dest_current = np.array(rbf_dest_current).T
# uv_verts_uniq = np.array(np.nonzero(np.sum(verts_uv, axis=-1))).T
final = []
for i in range(batch):
print('processing frame: ' + str(i))
interpolator = spi.NearestNDInterpolator(x=uv_map_discreet_unique_unique, y=unique_uv_values[i,:])
final.append(interpolator(rbf_dest_current))
final = np.asarray(final)
result = np.zeros((batch, res * 2, res))
result[:, uv_map_discreet_unique[:, 0], uv_map_discreet_unique[:, 1]] = uv_values
result[:, rbf_dest_current[:, 0], rbf_dest_current[:, 1]] = final
if garment_uv_mask is not None:
result = result * garment_uv_mask[np.newaxis,:,:]
if return_garment_uv_mask:
return result, garment_uv_mask
else:
return result
def m2uv_array(m2uv):
if m2uv is None:
return None
result = np.zeros((3638, 2), dtype=np.int32)
for k, v in m2uv.items():
if len(v) == 2:
result[k] = list(v)
elif len(v) == 1:
x = v.pop()
result[k] = [x, x]
else:
assert False
return result
def uv_to_mesh(uv, m2uv):
res = uv.shape[0]
mesh = np.zeros((14475, 3))
uv_pixels = uv_map_discreet[m2uv]
# counter = np.ones((14475))
# counter[m2uv[:, 0] == m2uv[:, 1]] = 2
mesh = np.mean(uv[uv_pixels[:, :, 0], uv_pixels[:, :, 1], :], axis=1) # / counter[:, np.newaxis]
return mesh
pass
def verify_reconstruction(orig, reconstructed):
error = np.sqrt(np.sum((orig - reconstructed) ** 2, axis=-1))
colors = np.array([cm.color('jet', 1 - i) for i in error])
error_sum = np.sum(error)
verts_uv = np.zeros((uv_res * 2, uv_res, 3))
uv_values = np.zeros((uv_map.shape[0], 3))
uv_values[m2uv[:, 0]] = colors
uv_values[m2uv[:, 1]] += colors
uv_counter = np.zeros((uv_map.shape[0]))
uv_counter[m2uv[:, 0]] = 1
uv_counter[m2uv[:, 1]] += 1
uv_values /= uv_counter[:, np.newaxis]
verts_uv[uv_map_discreet[:, 0], uv_map_discreet[:, 1], :] = uv_values
fig = plt.figure(figsize=(15, 15))
ax = fig.add_subplot(111)
ax.scatter(uv_map[:, 0], uv_map[:, 1], s=5, c=uv_values/255)
plt.show()
fig = plt.figure(figsize=(15, 15))
ax = fig.add_subplot(121, projection='3d')
x = orig
ax.set_xlim3d(-1, 1)
ax.set_ylim3d(-1, 1)
ax.set_zlim3d(-1, 1)
ax.set_xlabel("X")
ax.set_ylabel("Y")
ax.set_zlabel("Z")
ax.scatter(x[:, 0], x[:, 1], x[:, 2], s=5)
ax = fig.add_subplot(122, projection='3d')
x = reconstructed#[error > 0.1, :]
ax.set_xlim3d(-1, 1)
ax.set_ylim3d(-1, 1)
ax.set_zlim3d(-1, 1)
ax.set_xlabel("X")
ax.set_ylabel("Y")
ax.set_zlabel("Z")
ax.scatter(x[:, 0], x[:, 1], x[:, 2], s=5, c=colors/255) #[error > 0.1, :]
plt.show()
pass
# https://stackoverflow.com/questions/38187286/find-unique-pairs-in-list-of-pairs
def unique_pairs(a):
a.sort(axis=1)
b = np.ascontiguousarray(a).view(
np.dtype((np.void, a.dtype.itemsize * a.shape[1]))
)
_, inv, ct = np.unique(b, return_inverse=True, return_counts=True)
return ct[inv] == 1
def unique_uv_map_mask(uv_map_discreet):
mask = np.zeros((uv_map_discreet.shape[0]), dtype=bool)
temp = np.zeros((uv_res * 2, uv_res))
for p in uv_map_discreet:
temp[p[0], p[1]] += 1
# temp = temp == 1
for i, p in enumerate(uv_map_discreet):
if temp[p[0], p[1]] == 1:
mask[i] = True
elif temp[p[0], p[1]] == 2:
mask[i] = True
temp[p[0], p[1]] = 0
return mask
def test(verts, faces, values):
uv_values = np.zeros((uv_map.shape[0], 3))
uv_values[m2uv[:, 0]] = values
uv_values[m2uv[:, 1]] += values
uv_counter = np.zeros((uv_map.shape[0]))
uv_counter[m2uv[:, 0]] = 1
uv_counter[m2uv[:, 1]] += 1
uv_values /= uv_counter[:, np.newaxis]
x = uv_values
verts = np.concatenate((verts, np.zeros((15068, 1))), axis=-1)
im = ((x - x.min()) / (x.max() - x.min())) * 255
tm.Trimesh(verts, faces, vertex_colors=im.astype(np.int32)).show()
def get_shapedirs():
to_keep = sio.loadmat(os.path.join('smpl/keep_remove.mat'))['keep'].reshape(-1)
shapedirs = []
with open(os.path.join('smpl/super_model_f.pkl'), 'rb') as f:
female = pickle.load(f, encoding="latin1")
shapedirs.append(female['shapedirs'][to_keep, :])
with open(os.path.join('smpl/super_model_m.pkl'), 'rb') as f:
male = pickle.load(f, encoding="latin1")
shapedirs.append(male['shapedirs'][to_keep, :])
return shapedirs
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("-f", "--folder", help = "end of range", default='/data-local/127_2/cape_processed/test/female')
parser.add_argument("-s", "--start", help = "start of range", default=0, type=int)
parser.add_argument("-e", "--end", help = "end of range", default=100, type=int)
parser.add_argument("-n", "--name", help = "end of range", default='lhunor')
parser.add_argument("-d", "--debug", help = "end of range", default=False, action='store_true')
args = parser.parse_args()
F = {'non-skirt': np.load("smpl/smpl_faces_orig.npy"), 'skirt': None}
uv_map = {'non-skirt': np.load('custom_utils/stretched_uv_map_3_orig.npy'), 'skirt': None}
m2uv = {'non-skirt': np.load('custom_utils/m2uv_orig.npy', allow_pickle=True).item(), 'skirt': None}
m2uv = {k: m2uv_array(v) for k, v in m2uv.items()}
uv_mask = {'non-skirt': np.load('custom_utils/mask_256x512.npy'), 'skirt': np.load('custom_utils/mask_256x512_skirt.npy')}
uv_res = 256
uv_map_discreet = dict()
uv_map_discreet_unique = dict()
uv_counter = dict()
rbf_dest = dict()
uv_map_mask = dict()
for k,v in uv_mask.items():
if k == 'skirt':
continue
uv_mask[k] = (cv2.resize(v * 255.0, (uv_res, uv_res * 2)) / 255).astype(bool)[:, :, np.newaxis]
# uv_mask_dilate = cv2.erode(uv_mask.astype(np.float32), cv2.getStructuringElement(cv2.MORPH_CROSS, (2 * 2 + 1, 2 * 2 + 1), (2, 2)), iterations=1).astype(bool)[:, :, np.newaxis]
# uv_mask_border = uv_mask * np.invert(uv_mask_dilate)
uv_mask[k] = cv2.dilate(v.astype(np.float32), cv2.getStructuringElement(cv2.MORPH_RECT, (2 * 2 + 1, 2 * 2 + 1), (2, 2)), iterations=2).astype(bool)[:, :, np.newaxis]
uv_map_discreet[k] = np.floor(uv_map[k] * uv_res).astype(np.int32)
uv_map_mask[k] = unique_uv_map_mask(uv_map_discreet[k])
uv_counter[k] = np.zeros((uv_map[k].shape[0]))
uv_counter[k][m2uv[k][:, 0]] = 1
uv_counter[k][m2uv[k][:, 1]] += 1
uv_counter[k] = uv_counter[k][uv_map_mask[k]]
uv_map_discreet_unique[k] = uv_map_discreet[k][uv_map_mask[k], :]
rbf_dest[k] = np.ones((uv_res * 2, uv_res))
rbf_dest[k][uv_map_discreet_unique[k][:, 0], uv_map_discreet_unique[k][:, 1]] = 0
rbf_dest[k][np.invert(uv_mask[k][:,:,0])] = 0
#########################################################################################
folder = args.folder
# data_to_convert = ['mesh_posed', 'mesh_static', 'mesh_normals', 'body_posed', 'mesh_unposed'] # 'mesh_unposed',
data_to_convert = ['mesh_static', 'mesh_normals'] # 'mesh_unposed',
frames = sorted(os.listdir(folder + '/mesh_posed_body_no_orient'))#[args.start:args.end]
frames = [[frame.split('.')[0], frame.split('.')[1]] for frame in frames]
ids = list(set([frame[0] for frame in frames]))
frames_by_id = {id: [frame[1] for frame in frames if frame[0] == id] for id in ids}
shapedirs = get_shapedirs()
root = '/'.join(folder.split('/')[:-1])
type = 'non-skirt'
os.makedirs(folder, exist_ok=True)
os.makedirs(os.path.join(folder, 'uv_posed_no_orient'), exist_ok=True)
os.makedirs(os.path.join(folder, 'uv_static'), exist_ok=True)
os.makedirs(os.path.join(folder, 'uv_normals'), exist_ok=True)
os.makedirs(os.path.join(folder, 'uv_unposed_no_shape'), exist_ok=True)
os.makedirs(os.path.join(folder, 'uv_body_posed_no_orient'), exist_ok=True)
os.makedirs(os.path.join(folder, 'uv_mask'), exist_ok=True)
mask = np.ones((3638), dtype=bool)
for id in tqdm.tqdm(ids):
# x = readPC2(os.path.join(folder, 'mesh_posed_no_orient', f'{id}_{garment}.pc16'), True)['V']
# mesh_posed = np.zeros((x.shape[0], 14475, 3), dtype=np.float32)
# mesh_posed[:,mask, :] = x
if 'mesh_unposed' in data_to_convert:
mesh_unposed = np.zeros((x.shape[0], 14475, 3), dtype=np.float32)
mesh_unposed[:,mask, :] = readPC2(os.path.join(folder, 'mesh_unposed_no_shape' ,f'{id}_{garment}.pc16'), True)['V']
if 'mesh_static' in data_to_convert:
mesh_static = np.load(os.path.join(folder, 'mesh_static', f'{id}.npz'))['mesh_static']
if 'mesh_normals' in data_to_convert:
mesh_normals = np.stack([np.load(os.path.join(folder, 'mesh_normals', f'{id}.{int(i):06d}.npz'))['mesh_normals'] for i in frames_by_id[id]], axis=0)
if 'body_posed' in data_to_convert and k != 1:
body_posed = readPC2(os.path.join(folder, 'mesh_body_posed_no_orient', f'{id}.pc16'), True)['V']
start = time.perf_counter()
uv_static, uv_mask_local, garment_uv_mask_border = convert_to_uv(uv_res, m2uv[type], uv_map[type], mesh_static, neighbours=3, mask=mask, method='rbf', garment_uv_mask=None)
uv_static = convert_to_uv_batch(uv_res, m2uv[type], uv_map[type], mesh_static[None, :, :], neighbours=3, mask=mask, method='rbf', garment_uv_mask=uv_mask_local, garment_uv_mask_border=garment_uv_mask_border)
uv_static = uv_static[0].astype(np.float32)
if 'mesh_posed' in data_to_convert:
uv_posed = convert_to_uv_batch(uv_res, m2uv[type], uv_map[type], mesh_posed[:, :, :], neighbours=3, mask=mask, method='rbf', garment_uv_mask=uv_mask_local, garment_uv_mask_border=garment_uv_mask_border)
if 'mesh_unposed' in data_to_convert:
uv_unposed = convert_to_uv_batch(uv_res, m2uv[type], uv_map[type], mesh_unposed[:, :, :], neighbours=3, mask=mask, method='rbf', garment_uv_mask=uv_mask_local, garment_uv_mask_border=garment_uv_mask_border)
if 'mesh_normals' in data_to_convert:
uv_normals = convert_to_uv_batch(uv_res, m2uv[type], uv_map[type], mesh_normals[:, :, :], neighbours=3, mask=mask, method='rbf', garment_uv_mask=uv_mask_local, garment_uv_mask_border=garment_uv_mask_border)
if 'body_posed' in data_to_convert and k != 1:
uv_body_posed = convert_to_uv_batch_body(uv_res, m2uv['non-skirt'], uv_map['non-skirt'], body_posed[:, :, :], neighbours=3, mask=None, method='rbf', garment_uv_mask=None, garment_uv_mask_border=garment_uv_mask_border)
print(time.perf_counter() - start)
# ex.imshow(uv_mask_local).show()
# ex.imshow((uv_static+1)/2).show()
# ex.imshow((uv_posed[0]+1)/2).show()
# ex.imshow((uv_unposed[0]+1)/2).show()
# ex.imshow((uv_normals[0]+1.5)/3).show()
# ex.imshow((uv_body_posed[0]+1)/2).show()
# pass
# np.savez_compressed(os.path.join(folder, 'uv_static', f'{id}_{garment}.npz'), uv_static=uv_static)
# np.savez_compressed(os.path.join(folder, 'uv_mask', f'{id}_{garment}.npz'), uv_mask=uv_mask_local)
if 'mesh_posed' in data_to_convert:
for i in range(len(uv_posed)):
np.savez_compressed(os.path.join(folder, 'uv_posed_no_orient', f'{id}_{i}_{garment}.npz'), uv_posed=uv_posed[i])
if 'mesh_unposed' in data_to_convert:
for i in range(len(uv_unposed)):
np.savez_compressed(os.path.join(folder, 'uv_unposed_no_shape', f'{id}_{i}_{garment}.npz'), uv_unposed=uv_unposed[i])
if 'mesh_normals' in data_to_convert:
for i, frame_nr in enumerate(frames_by_id[id]):
np.savez_compressed(os.path.join(folder, 'uv_normals', f'{id}.{frame_nr}.npz'), uv_normals=uv_normals[i])
if 'body_posed' in data_to_convert and k != 1:
for i in range(len(uv_body_posed)):
np.savez_compressed(os.path.join(folder, 'uv_body_posed_no_orient', f'{id}_{i}.npz'), uv_body_posed=uv_body_posed[i])
# pass