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optimizing curvature generation

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luni
2023-01-27 17:17:36 +00:00
parent 8c0436cea8
commit 80381df65a
2 changed files with 61 additions and 54 deletions
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curvature_label_parallel.py
+5 -5
View File
@@ -4,15 +4,15 @@ import os
if __name__ == '__main__': if __name__ == '__main__':
folder = '/home/workspace/local-data/cape/train/male' folder = '/home/workspace/local-data/train'
out_folder = '/home/workspace/local-data/cape_processed/train/male' out_folder = '/home/workspace/local-data/train'
ids = os.listdir(folder) ids = os.listdir(folder + '/mesh_posed')
count = 0 count = 0
step = 1 step = 15000
while count < len(ids): while count < len(ids):
# os.system('nohup python MeshUtils/curvature_labels.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'curv_train_' + str(count) + '_' + str(count+step) + ' > curv_train_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &') # os.system('nohup python MeshUtils/curvature_labels.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'curv_train_' + str(count) + '_' + str(count+step) + ' > curv_train_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
os.system('nohup python curvature_labels_cape.py -if ' + folder + ' -of ' + out_folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'curv_gen_2_cape_train_male_' + str(count) + '_' + str(count+step) + ' > nohup/curv_gen_2_cape_train_male_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &') os.system('nohup python curvature_labels.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'curv_gen_50_train_nons_' + str(count) + '_' + str(count+step) + ' > nohup/curv_gen_50_train_nons_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
# os.system('python Data/convert_to_uv.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + '') # os.system('python Data/convert_to_uv.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + '')
count += step count += step
curvature_labels.py
+56 -49
View File
@@ -4,6 +4,7 @@ import tqdm
import argparse import argparse
import random import random
import string import string
import time
import numpy as np import numpy as np
import trimesh as tm import trimesh as tm
import cmapy as cm import cmapy as cm
@@ -40,6 +41,8 @@ def export_to_ply(mesh, file):
output_file.close() output_file.close()
def get_closest_n_points(verts, idx, n): def get_closest_n_points(verts, idx, n):
dist = sp.spatial.distance.cdist(verts[idx, :], verts) dist = sp.spatial.distance.cdist(verts[idx, :], verts)
dist[dist == 0] = 1e9 dist[dist == 0] = 1e9
@@ -80,35 +83,40 @@ def k_neighbours(k):
pass pass
def calculate_dist(folder, neighbourhood):
out = dict()
frames = sorted(os.listdir(os.path.join(folder, 'mesh_posed')))[int(args.start):int(args.end)]
for frame in tqdm.tqdm(frames):
id = frame.split('_')[0]
if id in out.keys():
continue
mask = np.load(os.path.join(folder, 'mesh_mask', f'{id}.npy')).astype(bool)
k_neighbors = np.argsort(dist[mask, :][:, mask], axis=-1)[:, :neighbourhood] #cloud.get_neighbors(k=neighbourhood)
out[id] = k_neighbors
return out
def generate_curvatures(folder, neighbourhood): def generate_curvatures(folder, neighbourhood):
ids = os.listdir(folder)[int(args.start):int(args.end)] # ids = os.listdir(folder)[int(args.start):int(args.end)]
frames = sorted(os.listdir(os.path.join(folder, 'mesh_posed')))[int(args.start):int(args.end)]
os.makedirs(os.path.join(folder, f'mesh_curvature_raw_{neighbourhood}'), exist_ok=True)
curvatures_all = [] k_neighbors_cache = calculate_dist(folder, neighbourhood)
for id in tqdm.tqdm(ids): for frame in tqdm.tqdm(frames):
garment_dir = os.path.join(folder, id)
if not os.path.isdir(garment_dir): id = frame.split('_')[0]
continue frame_nr = frame.split('_')[1].split('.')[0]
# if os.path.exists(garment_dir + '/curvature_25_raw.npy'):
# continue
curvatures_garment = []
garments = [f.replace('.pc16','') for f in os.listdir(garment_dir) if f.find('_') == -1 and f != 'info.mat' and not f.endswith('.obj')]
# assert len (garments) == 1
if len (garments) != 1:
continue
garment = garments[0]
bodies = readPC2(os.path.join(folder, id, 'Body_posed.pc16'), True)['V'] # bodies = readPC2(os.path.join(folder, id, 'Body_posed.pc16'), True)['V']
offsetss = readPC2(os.path.join(folder, id, garment + '_registered.pc16'), True)['V'] # offsetss = readPC2(os.path.join(folder, id, garment + '_registered.pc16'), True)['V']
mask = np.squeeze(sio.loadmat(os.path.join(garment_dir, garment + '_mask.mat'))['mask'].astype(bool)) mask = np.load(os.path.join(folder, 'mesh_mask', f'{id}.npy')).astype(bool)
faces = np.load(os.path.join(folder, 'faces', f'{id}.npy'))
v = np.load(os.path.join(folder, 'mesh_posed', f'{id}_{frame_nr}.npz'))['mesh_posed'][mask,:]
_, faces = _maskFaces(bodies[0, :, :], F, mask)
v = bodies[0, mask, :] + offsetss[0, mask, :]
m = tm.Trimesh(v, faces, process=False, validate=False) m = tm.Trimesh(v, faces, process=False, validate=False)
outliers = np.array([len(v) for v in m.vertex_neighbors]) == 0 outliers = np.array([len(v) for v in m.vertex_neighbors]) == 0
@@ -117,30 +125,23 @@ def generate_curvatures(folder, neighbourhood):
outliers_faces = np.concatenate((outliers[:, np.newaxis], outliers_n_neighbours), axis=-1) outliers_faces = np.concatenate((outliers[:, np.newaxis], outliers_n_neighbours), axis=-1)
faces = np.concatenate((faces, outliers_faces), axis=0) faces = np.concatenate((faces, outliers_faces), axis=0)
step = 0 verts = v
for body, offsets in zip(bodies, offsetss):
verts = body + offsets
verts = verts[mask, :]
m = tm.Trimesh(verts, faces, process=False, validate=False) m = tm.Trimesh(verts, faces, process=False, validate=False)
export_to_ply(m, temp_file) export_to_ply(m, temp_file)
cloud = PyntCloud.from_file(temp_file) cloud = PyntCloud.from_file(temp_file)
# cloud.plot(mesh=True)
k_neighbors = np.argsort(dist[mask, :][:, mask], axis=-1)[:, :neighbourhood] #cloud.get_neighbors(k=neighbourhood) k_neighbors = k_neighbors_cache[id] # np.argsort(dist[mask, :][:, mask], axis=-1)[:, :neighbourhood] #cloud.get_neighbors(k=neighbourhood)
ev = cloud.add_scalar_field("eigen_values", k_neighbors=k_neighbors) ev = cloud.add_scalar_field("eigen_values", k_neighbors=k_neighbors)
cloud.add_scalar_field("curvature", ev=ev) cloud.add_scalar_field("curvature", ev=ev)
curvature = np.array(cloud.points["curvature(" + str(neighbourhood+1) + ")"]) curvature = np.array(cloud.points["curvature(" + str(neighbourhood+1) + ")"])
curvatures_garment.append(curvature) out = np.zeros((14475), dtype=np.float32)
out[mask] = curvature
np.savez_compressed(os.path.join(folder, f'mesh_curvature_raw_{neighbourhood}', f'{id}_{frame_nr}.npz'), mesh_curvature_raw=out)
print(step) return None
step += 1
# curvatures_all.append(np.array(curvatures_garment))
np.save(garment_dir + '/curvature_25_raw.npy', np.array(curvatures_garment))
return curvatures_all
def get_bins(values, nr_of_bins): def get_bins(values, nr_of_bins):
@@ -282,21 +283,27 @@ def read_raw_curvatures(folder):
if __name__ == '__main__': if __name__ == '__main__':
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser()
parser.add_argument("-f", "--folder", help = "process the given folder", default=r'/home/workspace/data/dataset/test') parser.add_argument("-f", "--folder", help = "process the given folder", default=r'/home/workspace/local-data/train')
parser.add_argument("-s", "--start", help = "start of range", default=0) parser.add_argument("-s", "--start", help = "start of range", default=0)
parser.add_argument("-e", "--end", help = "end of range", default=1500) parser.add_argument("-e", "--end", help = "end of range", default=10)
parser.add_argument("-n", "--name", help = "end of range", default="lhunor") parser.add_argument("-n", "--name", help = "end of range", default="lhunor")
args = parser.parse_args() args = parser.parse_args()
F = np.load("FeatureLines/superSMPL/smpl_faces.npy") is_skirt = False
skirt_modifier = '_skirt' if is_skirt else ''
F = np.load("custom_utils/smpl_faces" + skirt_modifier + ".npy").astype(np.int32)
# k_neighbours(k=25) # k_neighbours(k=25)
folder = args.folder folder = args.folder
nr_of_labels = 6 nr_of_labels = 6
neighbourhood = 25 neighbourhood = 50
temp_file = 'temp/' + ''.join(random.choice(string.ascii_lowercase) for i in range(10)) + '.ply' temp_file = '/home/workspace/local-data/temp/' + ''.join(random.choice(string.ascii_lowercase) for i in range(10)) + '.ply'
dist = np.load('MeshUtils/dijsktra.npy') if not is_skirt:
# dist = np.load('MeshUtils/dijkstra_skirt.npy') dist = np.load('custom_data/dijkstra.npy')
else:
dist = np.load('custom_data/dijkstra_skirt.npy')
print('SKIRT' if is_skirt else 'NOT SKIRT')
generate_curvatures(folder, neighbourhood) generate_curvatures(folder, neighbourhood)
# curvatures = read_raw_curvatures(folder) # curvatures = read_raw_curvatures(folder)