def random_shape_sample():
for i in range(5, 10):
in_path = random_shape_net_object()
out_path_ori = r"/home/zgong8/data_out/base-" + str(i) + "-ori.obj"
out_path1 = r"/home/zgong8/data_out/base-" + str(i) + "-1.obj"
file_path1 = r"/home/zgong8/data_out/base-" + str(i) + "-1.txt"
out_path2 = r"/home/zgong8/data_out/base-" + str(i) + "-2.obj"
file_path2 = r"/home/zgong8/data_out/base-" + str(i) + "-2.txt"
empty_pipeline = Pipeline(0)
empty_pipeline.process_shape_file(in_path, out_path_ori)
deformation_level = i % 3 + 1
status = False
while not status:
ppl, status = run_leveled_pipeline(3, in_path, out_path1)
with open(file_path1, 'w') as f:
f.write(in_path)
f.write("\n")
f.write(str(ppl))
f.write("\n")
f.write("status: ")
f.write(str(status))
f.write("\n")
f.write("score: ")
f.write(str(ppl.estimate_deform_score()))
if status:
f.write("\n")
f.write("manifold: ")
f.write(str(is_manifold(file=out_path1)))
f.write("\n")
f.write("cut_at: ")
f.write(str(ppl.cut_by_point_cloud))
f.close()
status = False
while not status:
ppl, status = run_leveled_pipeline(1, in_path, out_path2)
with open(file_path2, 'w') as f:
f.write(in_path)
f.write("\n")
f.write(str(ppl))
f.write("\n")
f.write("status: ")
f.write(str(status))
f.write("\n")
f.write("score: ")
f.write(str(ppl.estimate_deform_score()))
if status:
f.write("\n")
f.write("manifold: ")
f.write(str(is_manifold(file=out_path2)))
f.write("\n")
f.write("cut_at: ")
f.write(str(ppl.cut_by_point_cloud))
f.close()
print("{} done!".format(str(i)))
def validate_for_examples():
f_name = r"/home/zgong8/PerceptualMetric/examples/data_out/bi_high_{}.obj"
for i in range(10):
_f_name = f_name.format(i)
print(_f_name)
print(is_manifold(file=_f_name))
def shape_net_test():
yes = 0
no = 0
for file in iterate_shape_net():
if is_manifold(file=file):
yes += 1
else:
no += 1
print(yes, no)
def random_shape_net_object():
res = None
while res is None:
lv1 = _get_lv1()
f1 = np.random.choice(lv1)
full_f1 = join(root, f1)
lv2 = listdir(full_f1)
f2 = np.random.choice(lv2)
full_f2 = join(full_f1, f2, MODEL_FOLDER)
lv3 = listdir(full_f2)
for f3 in lv3:
if f3.endswith(OBJECT_EXT):
res = join(full_f2, f3)
if res is not None:
if not is_manifold(res):
res = None
return res
def random_shape_net_test():
file = random_shape_net_object()
print(file)
print(is_manifold(file=file))
def single_test():
in_path = os.path.join(curr_dir, data_in_dir, file_name)
print(is_manifold(file=in_path))