luni/cvpr
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

save

Browse Source
This commit is contained in:
luni
2023-03-14 14:08:03 +00:00
parent abecb2d20a
commit d92a18e212
5 changed files with 32 additions and 31 deletions
Download Patch File Download Diff File Expand all files Collapse all files
aaa_helpers.txt
+1
View File
@@ -165,6 +165,7 @@ nohup python evaluate_ae_pyramid.py --name evaluate_ae_iccv_pyr_32_64_128_curv >
nohup python evaluate_ae_pyramid.py --name evaluate_ae_iccv_pyr_32_64_128_curv_skirt > nohup/iccv/evaluate/iccv_pyr_32_64_128_curv_skirt.out 2>&1 &
nohup python evaluate_ae_pyramid.py --name evaluate_ae_iccv_pyr_32_64_128_256 > nohup/iccv/evaluate/iccv_pyr_32_64_128_256.out 2>&1 &
nohup python evaluate_ae_pyramid.py --name evaluate_ae_iccv_pyr_32_64_128_256_seq > nohup/iccv/evaluate/iccv_pyr_32_64_128_256_seq.out 2>&1 &
nohup python evaluate_ae_pyramid.py --name evaluate_ae_iccv_pyr_32_64_128_256_skirt > nohup/iccv/evaluate/iccv_pyr_32_64_128_256_skirt.out 2>&1 &
nohup python evaluate_ae_pyramid.py --name evaluate_ae_iccv_pyr_32_64_128_256_skin > nohup/iccv/evaluate/iccv_pyr_32_64_128_256_skin.out 2>&1 &
nohup python evaluate_ae_pyramid.py --name evaluate_ae_iccv_pyr_32_64_128_256_curv > nohup/iccv/evaluate/iccv_pyr_32_64_128_256_curv.out 2>&1 &
calculate_error.py
+5 -5
View File
@@ -1,6 +1,6 @@
import os
import sys
from configs.iccv.config_abl_pyr_32_64_128_skin_skirt import config
from configs.iccv.config_abl_pyr_32_64_128_256_seq import config
os.environ["CUDA_VISIBLE_DEVICES"] = config['gpu']
import tensorflow as tf
@@ -58,7 +58,7 @@ if __name__ == '__main__':
# smpl = SMPL(use_one_hot=config['use_one_hot'])
skirt_modifier = '_skirt' if config['is_skirt'] else ''
error_type = 'collision' # 'euclidean' 'collision' edge normal
error_type = 'euclidean' # 'euclidean' 'collision' edge normal
folder = config['test_dir']
@@ -92,9 +92,9 @@ if __name__ == '__main__':
frames = [frame for frame in frames if not frame.endswith('_fixed_coll.npy')]
# frames = frames[:100]
print('Reading bodies...')
bodies_folder = '/home/workspace/local-data' + ('' if config['is_skirt'] else '_127') + '/test' + ('_skirt' if config['is_skirt'] else '') + '_ready' + ('_2' if config['is_skirt'] else '') + '/mesh_posed_body_no_orient'
bodies = {frame : np.load(bodies_folder + '/' + frame[:-1] + 'z')['mesh_posed_body_no_orient'] for frame in tqdm(frames) }
# print('Reading bodies...')
# bodies_folder = '/home/workspace/local-data' + ('' if config['is_skirt'] else '_127') + '/test' + ('_skirt' if config['is_skirt'] else '') + '_ready' + ('_2' if config['is_skirt'] else '') + '/mesh_posed_body_no_orient'
# bodies = {frame : np.load(bodies_folder + '/' + frame[:-1] + 'z')['mesh_posed_body_no_orient'] for frame in tqdm(frames) }
if config['remove_global_orientation']:
gt_name = 'mesh_posed_no_orient'
configs/iccv/config_abl_pyr_32_64_128_256_seq.py
+2 -2
View File
@@ -1,6 +1,6 @@
config = dict()
config['gpu'] = '4'
config['gpu'] = '3'
config['name'] = 'iccv_pyr_32_64_128_256_seq_2'
config['notes'] = ''
config['tags'] = ['pyr', 'iccv']
@@ -32,7 +32,7 @@ config['pyramid']['final_upscale_enhancer'] = ''
config['train_dir'] = '/home/workspace/local-data/train'
config['valid_dir'] = '/home/workspace/local-data/valid'
config['test_dir'] = '/home/workspace/local-data_127/test_ready'
config['test_dir'] = '/home/workspace/local-data/test_ready'
config['batch_size'] = 4
config['is_skirt'] = False
evaluate_ae_pyramid.py
+1 -1
View File
@@ -1,6 +1,6 @@
import os
import sys
from configs.iccv.config_abl_pyr_32_64_128_skin_skirt import config
from configs.iccv.config_abl_pyr_32_64_128_256_seq import config
os.environ["CUDA_VISIBLE_DEVICES"] = config['gpu']
import tensorflow as tf
get_error.py
+23 -23
View File
@@ -8,11 +8,11 @@ if __name__ == '__main__':
garment_type_table = np.load('custom_data/garment_type_table_test.npy', allow_pickle=True).item()
folder = '/home/workspace/data/results/errors/iccv'
checkpoint_name = 'iccv_pyr_32_64_128_skin'
checkpoint_name = 'iccv_pyr_32_64_128_256_seq_2'
checkpoint_name_skirt = 'iccv_pyr_32_64_128_skin_skirt'
iteration = '75' + '000'
iteration = '185' + '000'
iteration_skirt : str = '155' + '000'
error_type = 'collision' # 'euclidean' 'collision' edge normal
error_type = 'euclidean' # 'euclidean' 'collision' edge normal
errors = []
@@ -21,31 +21,31 @@ if __name__ == '__main__':
per_garment_errors_skirt = { 'Tshirt': [], 'Dress': [], 'Skirt': [], 'Top': [] }
# with open(os.path.join(folder, f'{checkpoint_name}-{iteration}-{error_type}.csv'), 'r') as f:
# csv_reader = csv.reader(f, delimiter=',')
# for row in csv_reader:
# per_garment_errors[garment_type_table[row[0].split('_')[0]]].append(float(row[1]))
# print('\nNon-skirt:')
# for key in per_garment_errors.keys():
# avg = np.mean(per_garment_errors[key])
# errors.append(avg)
# print(key + ': ' + str(avg))
# print('\nAvg non-skirt: ' + str(np.mean(errors)))
with open(os.path.join(folder, f'{checkpoint_name_skirt}-{iteration_skirt}-{error_type}.csv'), 'r') as f:
with open(os.path.join(folder, f'{checkpoint_name}-{iteration}-{error_type}.csv'), 'r') as f:
csv_reader = csv.reader(f, delimiter=',')
for row in csv_reader:
per_garment_errors_skirt[garment_type_table[row[0].split('_')[0]]].append(float(row[1]))
per_garment_errors[garment_type_table[row[0].split('_')[0]]].append(float(row[1]))
print('\nSkirt:')
for key in per_garment_errors_skirt.keys():
avg = np.mean(per_garment_errors_skirt[key])
errors_skirt.append(avg)
print('\nNon-skirt:')
for key in per_garment_errors.keys():
avg = np.mean(per_garment_errors[key])
errors.append(avg)
print(key + ': ' + str(avg))
print('Avg skirt: ' + str(np.mean(errors_skirt)))
print('\nAvg non-skirt: ' + str(np.mean(errors)))
# with open(os.path.join(folder, f'{checkpoint_name_skirt}-{iteration_skirt}-{error_type}.csv'), 'r') as f:
# csv_reader = csv.reader(f, delimiter=',')
# for row in csv_reader:
# per_garment_errors_skirt[garment_type_table[row[0].split('_')[0]]].append(float(row[1]))
# print('\nSkirt:')
# for key in per_garment_errors_skirt.keys():
# avg = np.mean(per_garment_errors_skirt[key])
# errors_skirt.append(avg)
# print(key + ': ' + str(avg))
# print('Avg skirt: ' + str(np.mean(errors_skirt)))
# cum_avg_shirt = np.mean(per_garment_errors['Tshirt'] + per_garment_errors_skirt['Tshirt'])
# cum_avg_top = np.mean(per_garment_errors['Top'] + per_garment_errors_skirt['Top'])