import os import sys import glob import tqdm import math import time import random import shutil import collections import argparse import threading 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 scipy.stats as stat import cv2 import plotly.express as ex import plotly.graph_objects as go from custom_utils.custom_utils import m2uv_array def dilate(img): uv_mask_2 = img != 0 m = img.min() # norm = img.max() - img.min() img = (img - m) * uv_mask_2 #* (np.invert(uv_mask_2) * -1 + uv_mask_2) size = 1 shape = cv2.MORPH_CROSS # cv.MORPH_CROSS cv.MORPH_ELLIPSE MORPH_RECT element = cv2.getStructuringElement(shape, (2 * size + 1, 2 * size + 1), (size, size)) result = cv2.dilate(img, element, iterations=1) result = (result + m) * uv_mask return result def erode(img): # m = img.min() # norm = img.max() - img.min() # img = (img - m) size = 1 shape = cv2.MORPH_CROSS # cv.MORPH_CROSS cv.MORPH_ELLIPSE MORPH_RECT element = cv2.getStructuringElement(shape, (2 * size + 1, 2 * size + 1), (size, size)) result = cv2.erode(img, element, iterations=2) # result = result + m return result def chunks(lst, n): """Yield successive n-sized chunks from lst.""" for i in range(0, len(lst), n): yield lst[i:i + n] def convert_to_uv(res, m2uv, uv_map, verts, neighbours=10, mask=None, method='rbf', garment_uv_mask=None, uv_map_mask=None, uv_counter=None, uv_map_discreet_unique=None, rbf_dest=None, 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), np.float32) 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, uv_map_mask=None, uv_counter=None, uv_map_discreet_unique=None, rbf_dest=None, uv_mask=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] return result assert False 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 # test # verts_uv_save = verts_uv.copy() # unique_uv_values_mask = np.sum(uv_values[0, :, :], axis=-1) != 0 # unique_uv_values = uv_values[:, unique_uv_values_mask, :] # uv_map_discreet_unique_unique = uv_map_discreet_unique[unique_uv_values_mask, :] 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 # uv_values = uv_values * garment_mask # 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 # 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, uv_res): 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 convert_to_uv_api(to_convert, mask, is_skirt=False, uv_res=256): print("skirt" if is_skirt == 1 else "not skirt") F = np.load("custom_utils/smpl_faces" + ("_skirt" if is_skirt == 1 else "") + ".npy") uv_map = np.load('custom_utils/stretched_uv_map_' + ("skirt" if is_skirt == 1 else "3") + '.npy') m2uv = np.load('custom_utils/m2uv' + ("_skirt" if is_skirt == 1 else "") + '.npy', allow_pickle=True).item() m2uv = m2uv_array(m2uv) uv_mask = np.load('custom_utils/mask_256x512' + ("_skirt" if is_skirt == 1 else "") + '.npy') uv_mask = (cv2.resize(uv_mask * 255.0, (uv_res, uv_res * 2)) / 255).astype(bool)[:, :, np.newaxis] 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_res) 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 _, garment_uv_mask, garment_uv_mask_border = convert_to_uv(uv_res, m2uv, uv_map, to_convert, neighbours=3, mask=mask, method='rbf', garment_uv_mask=None, uv_map_mask=uv_map_mask, uv_counter=uv_counter, uv_map_discreet_unique=uv_map_discreet_unique, rbf_dest=rbf_dest, uv_mask=uv_mask) uv = convert_to_uv_batch(uv_res, m2uv, uv_map, to_convert[np.newaxis,:,:], neighbours=3, mask=mask, method='rbf', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border, uv_map_mask=uv_map_mask, uv_counter=uv_counter, uv_map_discreet_unique=uv_map_discreet_unique, rbf_dest=rbf_dest, uv_mask=uv_mask) return uv if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument("-n", "--name", help = "end of range", default='lhunor') args = parser.parse_args() start = time.perf_counter() uv = convert_to_uv_api(np.random.random((14475, 3)) - 0.5, np.ones((14475), bool), is_skirt=False) print(time.perf_counter() - start) print()