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
6 changed files with 13 additions and 11 deletions
+3 -1
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@@ -1,4 +1,6 @@
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
+1 -1
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@@ -59,7 +59,7 @@ if __name__ == '__main__':
folder = config['test_dir']
checkpoint_name = config['name']
iteration = ''
iteration = '70000'
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()
+2 -2
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@@ -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)
assert ablation_count == 1 or ablation_count == 0
config['gpu'] = '1'
config['name'] = 'al_all_post'
config['gpu'] = '0'
config['name'] = 'abl_all_post_r7'
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
+2 -2
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@@ -73,7 +73,7 @@ def kl_loss(mean, logvar):
# 3d loss on posed !!!!!!!!!!!!
# @tf.function
@tf.function
def train_step(batch):
with tf.GradientTape() as tape:
@@ -476,7 +476,7 @@ def test():
if __name__ == '__main__':
# init_wandb()
init_wandb()
parser = argparse.ArgumentParser(description='')
parser.add_argument('--name', type=str)
args = vars(parser.parse_args())
+1 -1
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@@ -102,7 +102,7 @@ if __name__ == '__main__':
ids = [id.split('_')[0] for id in ids]
ids = set(ids)
iteration = ''
iteration = '70000'
load_model(model, 'checkpoints/post/' + checkpoint_name, iteration=iteration)
# load_model(model, 'checkpoints/' + 'abl_all_120k')
+4 -4
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@@ -7,10 +7,10 @@ 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'
checkpoint_name = 'abl_2_pyr_32_64_128_256_512'
checkpoint_name_skirt = 'abl_2_pyr_32_64_128_256_512_skirt'
iteration = '50000'
iteration_skirt : str = '50000'
checkpoint_name = 'abl_all_post_r7'
checkpoint_name_skirt = ''
iteration = '70000'
iteration_skirt : str = ''
# checkpoint_name = 'abl_skin'
# checkpoint_name_skirt = checkpoint_name + '_skirt'