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test_shapenet.py
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test_shapenet.py
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# Author: Wentao Yuan ([email protected]) 05/31/2018
import argparse
import csv
import importlib
import models
import numpy as np
import os
import tensorflow as tf
import time
from io_util import read_pcd, save_pcd
from tf_util import chamfer, earth_mover
from visu_util import plot_pcd_three_views
def test(args):
inputs = tf.placeholder(tf.float32, (1, None, 3))
gt = tf.placeholder(tf.float32, (1, args.num_gt_points, 3))
model_module = importlib.import_module('.%s' % args.model_type, 'models')
model = model_module.Model(inputs, gt, tf.constant(1.0))
output = tf.placeholder(tf.float32, (1, args.num_gt_points, 3))
cd_op = chamfer(output, gt)
emd_op = earth_mover(output, gt)
config = tf.ConfigProto()
config.gpu_options.allow_growth = True
config.allow_soft_placement = True
sess = tf.Session(config=config)
saver = tf.train.Saver()
saver.restore(sess, args.checkpoint)
os.makedirs(args.results_dir, exist_ok=True)
csv_file = open(os.path.join(args.results_dir, 'results.csv'), 'w')
writer = csv.writer(csv_file)
writer.writerow(['id', 'cd', 'emd'])
with open(args.list_path) as file:
model_list = file.read().splitlines()
total_time = 0
total_cd = 0
total_emd = 0
cd_per_cat = {}
emd_per_cat = {}
for i, model_id in enumerate(model_list):
partial = read_pcd(os.path.join(args.data_dir, 'partial', '%s.pcd' % model_id))
complete = read_pcd(os.path.join(args.data_dir, 'complete', '%s.pcd' % model_id))
start = time.time()
completion = sess.run(model.outputs, feed_dict={inputs: [partial]})
total_time += time.time() - start
cd, emd = sess.run([cd_op, emd_op], feed_dict={output: completion, gt: [complete]})
total_cd += cd
total_emd += emd
writer.writerow([model_id, cd, emd])
synset_id, model_id = model_id.split('/')
if not cd_per_cat.get(synset_id):
cd_per_cat[synset_id] = []
if not emd_per_cat.get(synset_id):
emd_per_cat[synset_id] = []
cd_per_cat[synset_id].append(cd)
emd_per_cat[synset_id].append(emd)
if i % args.plot_freq == 0:
os.makedirs(os.path.join(args.results_dir, 'plots', synset_id), exist_ok=True)
plot_path = os.path.join(args.results_dir, 'plots', synset_id, '%s.png' % model_id)
plot_pcd_three_views(plot_path, [partial, completion[0], complete],
['input', 'output', 'ground truth'],
'CD %.4f EMD %.4f' % (cd, emd),
[5, 0.5, 0.5])
if args.save_pcd:
os.makedirs(os.path.join(args.results_dir, 'pcds', synset_id), exist_ok=True)
save_pcd(os.path.join(args.results_dir, 'pcds', '%s.pcd' % model_id), completion[0])
csv_file.close()
sess.close()
print('Average time: %f' % (total_time / len(model_list)))
print('Average Chamfer distance: %f' % (total_cd / len(model_list)))
print('Average Earth mover distance: %f' % (total_emd / len(model_list)))
print('Chamfer distance per category')
for synset_id in cd_per_cat.keys():
print(synset_id, '%f' % np.mean(cd_per_cat[synset_id]))
print('Earth mover distance per category')
for synset_id in emd_per_cat.keys():
print(synset_id, '%f' % np.mean(emd_per_cat[synset_id]))
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--list_path', default='data/shapenet/test.list')
parser.add_argument('--data_dir', default='data/shapenet/test')
parser.add_argument('--model_type', default='pcn_cd')
parser.add_argument('--checkpoint', default='data/trained_models/pcn_cd')
parser.add_argument('--results_dir', default='data/shapenet_test_pcn_cd')
parser.add_argument('--num_gt_points', type=int, default=16384)
parser.add_argument('--plot_freq', type=int, default=100)
parser.add_argument('--save_pcd', action='store_true')
args = parser.parse_args()
test(args)