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.utils import save_to_h5file 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, :] # add garment mask uv_values /= uv_counter[:, 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] # add garment mask else: garment_mask = np.sum(uv_values, axis=-1) != 0 # test verts_uv[uv_map_discreet_unique[:, 0], uv_map_discreet_unique[:, 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[garment_mask, :] rbf_dest_current = rbf_dest 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[:,:,0] rbf_dest_current = rbf_dest * 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[:, 0], uv_map_discreet_unique[:, 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, :] uv_values /= uv_counter[np.newaxis, :, np.newaxis] return_garment_uv_mask = False # test verts_uv[:, uv_map_discreet_unique[:, 0], uv_map_discreet_unique[:, 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] # 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[garment_mask, :] rbf_dest_current = rbf_dest # add back mesh vertices that are not part of the garment uv_map_discreet_unique_unique_inv = uv_map_discreet_unique[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 + 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] # add garment mask rbf_dest_current = rbf_dest # add back mesh vertices that are not part of the garment uv_map_discreet_unique_unique_inv = uv_map_discreet_unique[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 + 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, :] uv_values /= uv_counter[:, np.newaxis] unique_uv_values = uv_values[garment_mask, :] uv_map_discreet_unique_unique = uv_map_discreet_unique[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): result = np.zeros((14475, 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('custom_utils/keep_remove.mat'))['keep'].reshape(-1) shapedirs = [] with open(os.path.join('custom_utils/super_model_f.pkl'), 'rb') as f: female = pickle.load(f, encoding="latin1") shapedirs.append(female['shapedirs'][to_keep, :]) with open(os.path.join('custom_utils/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='/home/workspace/data/dataset/cloth3d/train') parser.add_argument("-s", "--start", help = "start of range", default=70500) parser.add_argument("-e", "--end", help = "end of range", default=90000) parser.add_argument("-n", "--name", help = "end of range", default='lhunor') parser.add_argument("-sk", "--skirt", help = "end of range", default=0) args = parser.parse_args() F = np.load("custom_utils/smpl_faces" + ("_skirt" if args.skirt == 1 else "") + ".npy") uv_map = np.load('custom_utils/stretched_uv_map_' + ("skirt" if args.skirt == 1 else "3") + '.npy') m2uv = np.load('custom_utils/m2uv' + ("_skirt" if args.skirt == 1 else "") + '.npy', allow_pickle=True).item() m2uv = m2uv_array(m2uv) uv_mask = np.load('custom_utils/mask_256x512' + ("_skirt" if args.skirt == 1 else "") + '.npy') curvature_label_type = '6_25 ' uv_res = 256 uv_mask = (cv2.resize(uv_mask * 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 = cv2.dilate(uv_mask.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 = np.floor(uv_map * uv_res).astype(np.int32) uv_map_mask = unique_uv_map_mask(uv_map_discreet) uv_counter = np.zeros((uv_map.shape[0])) uv_counter[m2uv[:, 0]] = 1 uv_counter[m2uv[:, 1]] += 1 uv_counter = uv_counter[uv_map_mask] uv_map_discreet_unique = uv_map_discreet[uv_map_mask, :] rbf_dest = np.ones((uv_res * 2, uv_res)) rbf_dest[uv_map_discreet_unique[:, 0], uv_map_discreet_unique[:, 1]] = 0 rbf_dest[np.invert(uv_mask[:,:,0])] = 0 ######################################################################################### use_no_orient = False no_shape = False is_skirt = True if args.skirt == 1 else False folder = args.folder neighbourhood = 25 frames_file = 'frames_all.txt' data_to_convert = ['mesh_posed', 'mesh_static', 'mesh_curvature', 'body_posed'] # 'mesh_unposed', print("skirt" if args.skirt == 1 else "not skirt") print(f'params: -f {args.folder} -s {args.start} -e {args.end} -n {args.name} -skirt {args.skirt}') skirt_modifier = '_skirt' if is_skirt else '' orient_mod = '_no_orient' if use_no_orient else '' shape_mod = '_no_shape' if no_shape else '' frames = [] with open(os.path.join(folder, frames_file), 'r') as f: lines = f.readlines() lines = [line.strip() for line in lines] frames = lines[int(args.start):int(args.end)] ids = [frame.split()[0] for frame in frames] ids = sorted(list(set(ids))) shapedirs = get_shapedirs() root = '/'.join(folder.split('/')[:-1]) type = folder.split('/')[-1] # h5file_curv = tb.open_file(os.path.join(root, f'{type}_extras.h5'), mode='r') # h5file = tb.open_file(os.path.join(root, f'{type}_extras_uv.h5'), mode='a') extras_folder = os.path.join(root, f'{type}_extras') os.makedirs(extras_folder, exist_ok=True) os.makedirs(os.path.join(extras_folder, 'uv_posed' + orient_mod), exist_ok=True) os.makedirs(os.path.join(extras_folder, 'uv_static'), exist_ok=True) os.makedirs(os.path.join(extras_folder, 'uv_curvature'), exist_ok=True) os.makedirs(os.path.join(extras_folder, 'uv_unposed'), exist_ok=True) os.makedirs(os.path.join(extras_folder, 'uv_body_posed' + orient_mod), exist_ok=True) os.makedirs(os.path.join(extras_folder, 'uv_mask'), exist_ok=True) for id in tqdm.tqdm(ids): info = loadInfo(os.path.join(folder, id, 'info.mat')) garments = list(info['outfit'].keys()) assert info['poses'].shape[1] <= 300 # put all this in a function and call for all garments # also masking is not the same as just filling the empty values with neighbouring # values, at least the plots are different for garment in garments: # garment = garments[0] # if all the uv maps have been generated, skip this id # if all([os.path.exists(os.path.join(extras_folder, 'uv_body_posed' + orient_mod, f'{id}_{i}_{garment}.npz')) for i in range(info['poses'].shape[1])]): # continue mask = read_garment_mask(folder, id, garment) if 'mesh_posed' in data_to_convert: # mesh_posed_frame = read_posed_garment_frame(folder, id, garment, 0, mask=mask, shape=info['shape'], pose=info['poses'][:,0], deorient=use_no_orient, unshape=no_shape) mesh_posed = read_posed_garment(folder, id, garment, mask=mask, shape=info['shape'], poses=info['poses'], deorient=use_no_orient, unshape=no_shape) if 'mesh_unposed' in data_to_convert: raise NotImplementedError() mesh_unposed = read_unposed_garment(folder, id, garment, mask=mask, shape=info['shape'], unshape=no_shape) if 'mesh_static' in data_to_convert: mesh_static = read_garment_template(folder, id, garment, mask) if 'mesh_curvature' in data_to_convert: mesh_curvature = read_curvatures(folder + '_extras', id, garment, count=info['poses'].shape[1]) if 'body_posed' in data_to_convert: body_posed = read_posed_body(folder, id, info['poses'], use_no_orient) start = time.perf_counter() uv_static, uv_mask_local, garment_uv_mask_border = convert_to_uv(uv_res, m2uv, uv_map, mesh_static, neighbours=3, mask=mask, method='rbf', garment_uv_mask=None) uv_static = convert_to_uv_batch(uv_res, m2uv, uv_map, 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.astype(np.float32) if 'mesh_posed' in data_to_convert: uv_posed = convert_to_uv_batch(uv_res, m2uv, uv_map, 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: raise NotImplementedError() uv_unposed = convert_to_uv_batch(uv_res, m2uv, uv_map, mesh_unposed[:, :, :], neighbours=3, mask=mask, method='rbf', garment_uv_mask=uv_mask_local, garment_uv_mask_border=garment_uv_mask_border) if 'mesh_curvature' in data_to_convert: uv_curvature = convert_to_uv_batch_label(uv_res, m2uv, uv_map, mesh_curvature[:, :], neighbours=3, mask=mask, method='nearest', garment_uv_mask=uv_mask_local, garment_uv_mask_border=garment_uv_mask_border) if 'body_posed' in data_to_convert: uv_body_posed = convert_to_uv_batch_body(uv_res, m2uv, uv_map, 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) # mesh_static # save_to_h5file(h5file, id, 0, garment, uv_static, 'uv_static', 'float32') # save_to_h5file(h5file, id, 0, garment, uv_mask, 'uv_mask', 'float32') np.savez_compressed(os.path.join(extras_folder, 'uv_static', f'{id}_{garment}.npz'), uv_static=uv_static) np.savez_compressed(os.path.join(extras_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(extras_folder, 'uv_posed' + orient_mod, f'{id}_{i}_{garment}.npz'), uv_posed=uv_posed[i]) # save_to_h5file(h5file, id, i, garment, uv_posed[i, :, :, :], 'uv_posed' + orient_mod + shape_mod, 'float32') if 'mesh_unposed' in data_to_convert: raise NotImplementedError() for i in range(uv_unposed.shape[0]): save_to_h5file(h5file, id, i, garment, uv_unposed[i, :, :, :], 'uv_unposed' + orient_mod + shape_mod, 'float32') if 'mesh_curvature' in data_to_convert: for i in range(len(uv_curvature)): np.savez_compressed(os.path.join(extras_folder, 'uv_curvature', f'{id}_{i}_{garment}.npz'), uv_curvature=uv_curvature[i].astype(np.uint8)) # save_to_h5file(h5file, id, i, garment, uv_curvature[i, :, :, :], 'uv_curvature', 'uint8') if 'body_posed' in data_to_convert: for i in range(len(uv_body_posed)): np.savez_compressed(os.path.join(extras_folder, 'uv_body_posed' + orient_mod, f'{id}_{i}_{garment}.npz'), uv_body_posed=uv_body_posed[i]) # save_to_h5file(h5file, id, i, garment, uv_body_posed[i, :, :, :], 'uv_body_posed', 'float32') pass h5file_curv.close()