Author SHA1 Message Date
luni 25c108fe83 get error 2023-01-27 14:08:39 +00:00
luni 970aeaf5b9 calculate error 2023-01-26 19:23:37 +00:00
luni bda4582c3c run evaluation 2023-01-26 16:20:39 +00:00
luni 0bc5633b6c retraining original abl_all_post 2023-01-25 22:30:46 +00:00
8 changed files with 25 additions and 21 deletions
+4
View File
@@ -1,3 +1,7 @@
nohup python cvae.py --name="lhunor_abl_all_post_r7" > nohup/post/abl_all_post_r7.out 2>&1 &
nohup python evaluate_ae.py --name lhunor_abl_all_post_r7_70k > nohup/evaluate/abl_all_post_r7_70k.out 2>&1 &
nohup python calculate_error.py --name error_abl_all_post_r7_70k > nohup/error/abl_all_post_r7_70k.out 2>&1 &
one final convolutional layer for smoothing, on the final coordinates one final convolutional layer for smoothing, on the final coordinates
skirts!!!! skirts!!!!
+1 -1
View File
@@ -59,7 +59,7 @@ if __name__ == '__main__':
folder = config['test_dir'] folder = config['test_dir']
checkpoint_name = config['name'] checkpoint_name = config['name']
iteration = '' iteration = '70000'
F = np.load("custom_utils/smpl_faces" + skirt_modifier + ".npy").astype(np.int32) F = np.load("custom_utils/smpl_faces" + skirt_modifier + ".npy").astype(np.int32)
garment_type_table = np.load('custom_data/garment_type_table_test.npy', allow_pickle=True).item() garment_type_table = np.load('custom_data/garment_type_table_test.npy', allow_pickle=True).item()
+2 -2
View File
@@ -19,8 +19,8 @@ config['only_curvatures'] = False
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False) ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
assert ablation_count == 1 or ablation_count == 0 assert ablation_count == 1 or ablation_count == 0
config['gpu'] = '1' config['gpu'] = '0'
config['name'] = 'al_all_post' config['name'] = 'abl_all_post_r7'
config['notes'] = '' config['notes'] = ''
config['avg_garment_path'] = 'custom_data/train_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv config['avg_garment_path'] = 'custom_data/train_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
+3 -3
View File
@@ -1,9 +1,9 @@
config = dict() config = dict()
config['gpu'] = '6' config['gpu'] = '2'
config['name'] = 'abl_pyr_32' config['name'] = 'abl_pyr_32'
config['notes'] = '' config['notes'] = 'fixed noise handling'
config['tags'] = ['review_1'] config['tags'] = ['pyr_post']
# DON'T FORGET TO RESET SSIM LOSS USAGE # DON'T FORGET TO RESET SSIM LOSS USAGE
# DON'T FORGET TO CHECK MODEL LOADING # DON'T FORGET TO CHECK MODEL LOADING
+2 -2
View File
@@ -73,7 +73,7 @@ def kl_loss(mean, logvar):
# 3d loss on posed !!!!!!!!!!!! # 3d loss on posed !!!!!!!!!!!!
# @tf.function @tf.function
def train_step(batch): def train_step(batch):
with tf.GradientTape() as tape: with tf.GradientTape() as tape:
@@ -476,7 +476,7 @@ def test():
if __name__ == '__main__': if __name__ == '__main__':
# init_wandb() init_wandb()
parser = argparse.ArgumentParser(description='') parser = argparse.ArgumentParser(description='')
parser.add_argument('--name', type=str) parser.add_argument('--name', type=str)
args = vars(parser.parse_args()) args = vars(parser.parse_args())
+1 -1
View File
@@ -102,7 +102,7 @@ if __name__ == '__main__':
ids = [id.split('_')[0] for id in ids] ids = [id.split('_')[0] for id in ids]
ids = set(ids) ids = set(ids)
iteration = '' iteration = '70000'
load_model(model, 'checkpoints/post/' + checkpoint_name, iteration=iteration) load_model(model, 'checkpoints/post/' + checkpoint_name, iteration=iteration)
# load_model(model, 'checkpoints/' + 'abl_all_120k') # load_model(model, 'checkpoints/' + 'abl_all_120k')
+4 -4
View File
@@ -7,10 +7,10 @@ if __name__ == '__main__':
garment_type_table = np.load('custom_data/garment_type_table_test.npy', allow_pickle=True).item() garment_type_table = np.load('custom_data/garment_type_table_test.npy', allow_pickle=True).item()
folder = '/home/workspace/data/results/errors' folder = '/home/workspace/data/results/errors'
checkpoint_name = 'abl_2_pyr_32_64_128_256_512' checkpoint_name = 'abl_all_post_r7'
checkpoint_name_skirt = 'abl_2_pyr_32_64_128_256_512_skirt' checkpoint_name_skirt = ''
iteration = '50000' iteration = '70000'
iteration_skirt : str = '50000' iteration_skirt : str = ''
# checkpoint_name = 'abl_skin' # checkpoint_name = 'abl_skin'
# checkpoint_name_skirt = checkpoint_name + '_skirt' # checkpoint_name_skirt = checkpoint_name + '_skirt'
+8 -8
View File
@@ -232,17 +232,17 @@ def generate_frames_file(folder, ratio=0.1):
selected = [] selected = []
for id in tqdm.tqdm(sub_ids): for id in tqdm.tqdm(sub_ids):
# if garment_type_table[id] != 'Dress': if garment_type_table[id] != 'Dress':
# continue continue
# if len(selected) > 30000: if len(selected) > 30000:
# break break
# frames = glob.glob(os.path.join(folder, 'pose_shape', id + '_*')) # frames = glob.glob(os.path.join(folder, 'pose_shape', id + '_*'))
frames = [frame for frame in all_frames if frame.startswith(id + '_')] frames = [frame for frame in all_frames if frame.startswith(id + '_')]
frames = [frame.split('/')[-1].split('.')[0] for frame in frames] frames = [frame.split('/')[-1].split('.')[0] for frame in frames]
selected.extend(frames) selected.extend(frames)
with open(os.path.join(folder, 'frames_skirt_10p.txt'), 'w') as f: with open(os.path.join(folder, 'frames_dress_30k.txt'), 'w') as f:
for i, frame in enumerate(selected): for i, frame in enumerate(selected):
f.write(frame + '\n') f.write(frame + '\n')
@@ -293,9 +293,9 @@ def generate_frames_file_filtered_cape():
if __name__ == '__main__': if __name__ == '__main__':
src_folder = '/home/workspace/local-data/valid_skirt' #cloth3d_skirt src_folder = '/home/workspace/local-data/train_skirt' #cloth3d_skirt
# src_folder = r'D:\Work\Dataset\validation_2' # src_folder = r'D:\Work\Dataset\validation_2'
dest_folder = '/home/workspace/data/dataset/local-cache/train_skirt' dest_folder = '/home/workspace/data/dataset/validation'
# create_no_orient_body(src_folder) # create_no_orient_body(src_folder)
@@ -306,5 +306,5 @@ if __name__ == '__main__':
# verify_poses(src_folder) # verify_poses(src_folder)
# create_garment_type_table() # create_garment_type_table()
# generate_faces() # generate_faces()
generate_frames_file(src_folder, ratio=0.1) generate_frames_file(src_folder, ratio=1)
# generate_frames_file_filtered_cape() # generate_frames_file_filtered_cape()