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 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 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(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 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] np.savez_compressed(os.path.join(folder, 'uv_posed_no_orient', id + '_' + str(i) + '.npz'), uv_posed_no_orient=result) 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/test_skirt_ready_2') parser.add_argument("-x", "--extras", help = "end of range", default='/home/workspace/data/dataset/test_skirt_ready_2_extras') parser.add_argument("-s", "--start", help = "start of range", default=0) parser.add_argument("-e", "--end", help = "end of range", default=30000) parser.add_argument("-n", "--name", help = "end of range", default='lhunor') parser.add_argument("-sk", "--skirt", help = "end of range", default=1) args = parser.parse_args() # smpl = SMPL('FeatureLines/superSMPL') folder = args.folder extras_folder = args.extras os.makedirs(extras_folder, exist_ok=True) print("skirt" if args.skirt == 1 else "not skirt") 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 is_skirt = True if args.skirt == 1 else False skirt_modifier = '_skirt' if is_skirt else '' folder = args.folder frames_file = 'frames_all.txt' 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] print(f'params: -f {args.folder} -s {args.start} -e {args.end} -n {args.name} -skirt {args.skirt}') # ids = os.listdir(os.path.join(local_folder, 'pose_shape')) # ids = [id.split('_')[0] for id in ids] ids = sorted(list(set(ids)))[int(args.start):int(args.end)] shapedirs = get_shapedirs() use_no_orient = True no_shape = False data_to_convert = ['mesh_posed', 'mesh_unposed', 'mesh_static', 'mesh_curvature', 'body_posed'] for id in tqdm.tqdm(ids): info = loadInfo(os.path.join(folder, id, 'info.mat')) garments = info['outfit'] assert info['poses'].shape[1] <= 300 garment = garments[0] mask = read_garment_mask(folder, id, garment) if 'mesh_posed' in data_to_convert: mesh_posed = read_posed_garment(folder, id, garment, mask=mask, shape=info['shape'], poses=info['poses'], use_no_orient=use_no_orient, no_shape=no_shape) if 'mesh_unposed' in data_to_convert: mesh_unposed = read_unposed_garment(folder, id, garment, mask=mask, shape=info['shape'], no_shape=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 = compute_curvature(mesh_posed, F) if 'body_posed' in data_to_convert: body_posed = read_posed_body(folder, id, info['poses'], use_no_orient) # verts_static = read_garment_template(folder, id, garment, mask) # body = read_posed_body(folder, id, info['poses'], use_no_orient) # gt = read_posed_garment(folder, id, garment, mask=mask, shape=info['shape'], ...) # gt = readPC2(os.path.join(folder, id, garment + '_registered.pc16'), True)['V'] # curvature = np.stack([np.load(os.path.join(folder, f'mesh_curvature_{neighbourhood}_2', f'{id}_{i}.npz'))['mesh_curvature'] for i in range(frames_len)]) # mesh_unposed = [np.load(os.path.join(folder, id, 'mesh_unposed', id + '_' + str(i) + '.npz')) for i in range(gt.shape[0])] # mesh_unposed = np.stack([mesh_unposed[i]['mesh_unposed'] for i in range(gt.shape[0])]) # mesh_unposed_no_shape = [np.load(os.path.join(folder, id, 'mesh_unposed_no_shape', id + '_' + str(i) + '.npz')) for i in range(gt.shape[0])] # mesh_unposed_no_shape = np.stack([mesh_unposed_no_shape[i]['mesh_unposed_no_shape'] for i in range(gt.shape[0])]) # body_no_orient = [np.load(os.path.join(folder, id, 'mesh_posed_body_no_orient', id + '_' + str(i) + '.npz')) for i in range(gt.shape[0])] # body_no_orient = np.stack([body_no_orient[i]['mesh_posed_body_no_orient'] for i in range(gt.shape[0])]) # mesh_unposed_no_shape_one_hot = [np.load(os.path.join(local_folder, 'mesh_unposed_no_shape_one_hot', id + '_' + str(i) + '.npz')) for i in range(frames)] # mesh_unposed_no_shape_one_hot = [mesh_unposed_no_shape_one_hot[i]['mesh_unposed_no_shape'] for i in range(frames)] # mesh_posed_no_orient = [np.load(os.path.join(local_folder, 'mesh_posed_no_orient', id + '_' + str(i) + '.npz')) for i in range(frames)] # mesh_posed_no_orient = [mesh_posed_no_orient[i]['mesh_posed_no_orient'] for i in range(frames)] # verts_dynamic = gt # TODO: check if have to mask out non garment vertices or not? are they the same vertices erpeated many times? if remove, have to interpolate from almost nothing? # test(data.f.Vt, data.f.Ft, verts) # test(uv_map, data.f.Ft, verts) start = time.perf_counter() uv_verts_static, garment_uv_mask, garment_uv_mask_border = convert_to_uv(uv_res, m2uv, uv_map, verts_static, neighbours=3, mask=mask, method='rbf', garment_uv_mask=None) uv_verts_static = uv_verts_static.astype(np.float32) if 'mesh_posed' in data_to_convert: uv_posed = convert_to_uv_batch(uv_res, m2uv, uv_map, gt[:, :, :], neighbours=3, mask=mask, method='rbf', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border).astype(np.float32) if 'mesh_unposed' in data_to_convert: uv_unposed = convert_to_uv_batch(uv_res, m2uv, uv_map, mesh_unposed[:, :, :], neighbours=3, mask=mask, method='rbf', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border).astype(np.float32) if 'mesh_curvature' in data_to_convert: uv_curvature = convert_to_uv_batch_label(uv_res, m2uv, uv_map, curvature[:, :], neighbours=3, mask=mask, method='nearest', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border).astype(np.float32) if 'body_posed' in data_to_convert: uv_body_posed = convert_to_uv_batch(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).astype(np.float32) print(time.perf_counter() - start) if 'mesh_static' in data_to_convert: # np.save(os.path.join(folder, id, garment + '_offsets_static_uv.npy'), uv_verts_static) # np.save(os.path.join(folder, id, 'mask_uv.npy'), garment_uv_mask) if 'mesh_posed' in data_to_convert: mesh_posed = read_posed_garment(folder, id, garment, mask=mask, shape=info['shape'], poses=info['poses'], use_no_orient=use_no_orient, no_shape=no_shape) if 'mesh_unposed' in data_to_convert: mesh_unposed = read_unposed_garment(folder, id, garment, mask=mask, shape=info['shape'], no_shape=no_shape) if 'mesh_curvature' in data_to_convert: mesh_curvature = compute_curvature(mesh_posed, F) if 'body_posed' in data_to_convert: # for i in range(uv_body_posed.shape[0]): # np.savez_compressed(os.path.join(folder, id, 'uv_body_posed', garment + '_' + str(i) + '.npz'), uv_body=uv_body[i, :, :, :]) # start = time.perf_counter() # np.save(os.path.join(folder, id, 'body_static_uv.npy'), uv_body_static) # os.makedirs(os.path.join(folder, id, 'body_posed_uv'), exist_ok=True) # for i in range(uv_body.shape[0]): # np.savez_compressed(os.path.join(folder, id, 'body_posed_uv', garment + '_' + str(i) + '.npz'), uv_body=uv_body[i, :, :, :]) # os.makedirs(os.path.join(folder, id, 'uv_posed_body_no_orient'), exist_ok=True) # for i in range(uv_posed_body_no_orient.shape[0]): # np.savez_compressed(os.path.join(folder, id, 'uv_posed_body_no_orient', garment + '_' + str(i) + '.npz'), uv_posed_body_no_orient=uv_posed_body_no_orient[i, :, :, :]) # os.makedirs(os.path.join(folder, id, 'gt_uv'), exist_ok=True) # for i in range(uv_gt.shape[0]): # np.savez_compressed(os.path.join(folder, id, 'gt_uv', garment + '_' + str(i) + '.npz'), uv_gt=uv_gt[i, :, :, :]) os.makedirs(os.path.join(folder, f'uv_curvature_{neighbourhood}_2'), exist_ok=True) for i in range(uv_curvature.shape[0]): np.savez_compressed(os.path.join(folder, f'uv_curvature_{neighbourhood}_2', id + '_' + str(i) + '.npz'), curvature_uv=uv_curvature[i, :, :]) # os.makedirs(os.path.join(folder, id, 'uv_unposed'), exist_ok=True) # for i in range(uv_unposed.shape[0]): # np.savez_compressed(os.path.join(folder, id, 'uv_unposed', garment + '_' + str(i) + '.npz'), uv_unposed=uv_unposed[i, :, :, :]) # os.makedirs(os.path.join(folder, id, 'uv_unposed_no_shape'), exist_ok=True) # for i in range(uv_unposed_no_shape.shape[0]): # np.savez_compressed(os.path.join(folder, id, 'uv_unposed_no_shape', garment + '_' + str(i) + '.npz'), uv_unposed_no_shape=uv_unposed_no_shape[i, :, :, :]) # os.makedirs(os.path.join(folder, id, 'uv_unposed_no_shape_one_hot'), exist_ok=True) # for i in range(uv_unposed_no_shape_one_hot.shape[0]): # np.savez_compressed(os.path.join(folder, id, 'uv_unposed_no_shape_one_hot', garment + '_' + str(i) + '.npz'), uv_unposed_no_shape=uv_unposed_no_shape_one_hot[i, :, :, :]) # os.makedirs(os.path.join(folder, id, 'uv_shaped_body'), exist_ok=True) # np.savez_compressed(os.path.join(folder, id, 'uv_shaped_body.npz'), uv_shaped_body=uv_shaped_body) # print(time.perf_counter() - start) # mesh = uv_to_mesh(uv_verts_static, m2uv) # verify_reconstruction(verts_static * mask[:, np.newaxis], mesh * mask[:, np.newaxis]) # mesh = uv_to_mesh(uv_body[0,:,:], m2uv) # verify_reconstruction(body[0,:,:] * mask[:, np.newaxis], mesh * mask[:, np.newaxis]) pass