new files

make_super.py

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+import sys
+
+import numpy as np
+import pickle as pkl
+from scipy import sparse
+
+from time import time
+
+from custom_utils.supersmpl_io import writeOBJ, readOBJ
+
+
+def makeGraph(F):
+	G = {}
+	for f in F:
+		N = len(f)
+		for i,v in enumerate(f):
+			if not v in G: G[v] = {}
+			G[v][f[(i+1) % N]] = 1
+	return G
+
+def extrapolateMissings(M, G):
+	for i in range(6890, M.shape[0]):
+		if np.isnan(M[i]).all():
+			M[i] = neighAvg(M, G, i)
+		elif np.isnan(M[i]).any():
+			print("HOW?")
+			print(M[i])
+	if np.isnan(M).any(): extrapolateMissings(M, G)
+
+def neighAvg(M, G, i):
+	neigh = set(G[i].keys())
+	avg = 0
+	count = 0
+	for n in neigh:
+		if not np.isnan(M[n]).any():
+			avg += M[n]
+			count += 1
+	if count: return avg / count
+	return np.nan
+
+
+if __name__ == '__main__':
+
+	g = 'f'
+	# Read Super topology
+	V, F, Vt, Ft = readOBJ('super_f_avg.obj')
+	N = V.shape[0]
+	G = makeGraph(F)
+
+	# Read PKL
+	print("Loading .pkl file")
+	with open('custom_data/model_' + g + '.pkl', 'rb') as f:
+		M = pkl.load(f, encoding='latin1')
+		
+	# Fields
+	# print("Checking fields and shapes")
+	# for k in M:
+	# 	print(k, M[k].shape)
+	# Faces
+	print("New faces...")
+	M['f'] = F
+	# J_regressor (24, 6890)
+	# Sparse matrix, just change shape to add zeros
+	print("New regressor")
+	A = np.zeros((24, N), np.float32)
+	A[:,:6890] = M['J_regressor'].todense()
+	M['J_regressor'] = sparse.csr_matrix(A)
+
+	# Weights (6890, 24)
+	print("New weights")
+	start = time()
+	A = np.empty((N, 24), np.float32)
+	A[:] = np.nan
+	A[:6890] = M['weights'][:6890]
+	extrapolateMissings(A, G)
+	M['weights'] = A
+	print(time() - start)
+
+	# Posedirs (6890, 3, 207)
+	print("New posedirs")
+	start = time()
+	A = np.empty((N, 3, 207), np.float32)
+	A[:] = np.nan
+	A[:6890] = M['posedirs'][:6890]
+	extrapolateMissings(A, G)
+	M['posedirs'] = A
+	print(time() - start)
+
+	# v_tempalte (6890, 3)
+	print("New template")
+	start = time()
+	A = np.empty((N, 3), np.float32)
+	A[:] = np.nan
+	A[:6890] = M['v_template'][:6890]
+	extrapolateMissings(A, G)
+	M['v_template'] = A
+	print(time() - start)
+
+	# Shapedirs (6890, 3, 10)
+	print("New shapedirs")
+	start = time()
+	A = np.empty((N, 3, 10), np.float32)
+	A[:] = np.nan
+	A[:6890] = M['shapedirs'][:6890]
+	extrapolateMissings(A, G)
+	M['shapedirs'] = A
+	print(time() - start)
+
+	# Dump
+	print("Saving new model")
+	with open('super_model_' + g + '.pkl', 'wb') as f:
+		pkl.dump(M, f)