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prepare to train

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luni
2023-01-28 12:40:28 +00:00
parent 8c0436cea8
commit 0543657e4e
3 changed files with 138 additions and 6 deletions
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configs/config_abl_all_10p_curv_10_r2.py
+129
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@@ -0,0 +1,129 @@
config = dict()
# DON'T FORGET TO RESET SSIM LOSS USAGE
# DON'T FORGET TO CHECK MODEL LOADING
# DON'T FORGET TO CHECK IF STORE IN MEMORY
# DON'T FORGET TO CHECK REG LOSS COEFF
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
# DON'T FORGET TO CHECK AVG GARMENT USED
config['use_skinning'] = True # and deshaping
config['remove_global_orientation'] = True
config['use_curvature'] = True
config['use_extra_losses'] = True # edge, collision, 3d mesh
config['use_offsets'] = True
config['use_norm_loss'] = True
config['only_curvatures'] = False
config['curv_neighbourhood'] = 10
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'] = '6'
config['name'] = 'abl_all_10p_curv_10_r2'
config['notes'] = ''
config['tags'] = ['review_2']
config['avg_garment_path'] = 'custom_data/train_no_shape_skirt_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
if config['use_skinning']:
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
config['batch_size'] = 4
config['resolution'] = 512
config['is_skirt'] = True
config['dataset_in_memory'] = True
config['is_cape'] = False
config['train_dir'] = '/home/workspace/data/dataset/local-cache/train_skirt'
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
config['frames_file'] = 'frames_skirt_10p.txt'
config['frames_file_valid'] = 'frames_skirt_10p.txt'
# config['frames_file_test'] = 'frames_dress_30k.txt'
config['static_model'] = 'checkpoints/static_1_skirt'
config['body_model'] = 'checkpoints/body_1_skirt_2_2'
config['curvature_model'] = 'checkpoints/curv_1_skirt'
config['smpl_res'] = 14475
if config['is_cape']:
config['smpl_res'] = 3638
config['pretrained_model'] = ''
###############
config['lr'] = 0.0001# 0.0001
###############
config['starting_balancing_coeff'] = 0.001
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
'pose_shape': (72 + 11,),
'uv_body_posed': (512, 256, 3),
'mesh_body_posed': (config['smpl_res'], 3,),
'mesh_posed': (config['smpl_res'], 3,),
'uv_curvature': (512, 256, 7),
}
config['signature_static'] = { 'uv_static': (512, 256, 3),
'mesh_mask': (config['smpl_res'],),
'uv_mask': (512, 256,),
}
if config['use_skinning']:
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
config['signature_dynamic']['mesh_unposed'] = (config['smpl_res'], 3,)
else:
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
config['upscale_enhancer'] = ''
config['freeze_encoders'] = True
config['use_one_hot'] = False
config['cvae'] = dict()
config['cvae']['is_label'] = False
config['cvae']['add_noise'] = True
config['cvae']['noise_amount'] = 0.001
config['cvae']['kernel_size'] = 7
config['cvae']['encoder_depths'] = [3, 3, 3, 9, 3]
config['cvae']['encoder_dims'] = [32, 64, 128, 256, 64]
config['cvae']['decoder_depths'] = config['cvae']['encoder_depths']
config['cvae']['decoder_dims'] = config['cvae']['encoder_dims']
config['cond_ae_static'] = dict()
config['cond_ae_static']['is_label'] = False
config['cond_ae_static']['kernel_size'] = 7
config['cond_ae_static']['bottleneck_size'] = 8
config['cond_ae_static']['encoder_depths'] = [3, 3, 3, 9, 3]
config['cond_ae_static']['encoder_dims'] = [16, 32, 64, 64, config['cond_ae_static']['bottleneck_size']]
config['cond_ae_static']['decoder_depths'] = config['cond_ae_static']['encoder_depths']
config['cond_ae_static']['decoder_dims'] = config['cond_ae_static']['encoder_dims']
config['cond_ae_static']['activation'] = 'tanh'
config['cond_ae_curv'] = dict()
config['cond_ae_curv']['is_label'] = True
config['cond_ae_curv']['kernel_size'] = 7
config['cond_ae_curv']['bottleneck_size'] = 40
config['cond_ae_curv']['encoder_depths'] = [3, 3, 9, 9, 3]
config['cond_ae_curv']['encoder_dims'] = [16, 32, 64, 128, config['cond_ae_curv']['bottleneck_size']]
config['cond_ae_curv']['decoder_depths'] = config['cond_ae_curv']['encoder_depths']
config['cond_ae_curv']['decoder_dims'] = config['cond_ae_curv']['encoder_dims']
config['cond_ae_curv']['activation'] = 'tanh'
config['cond_ae_body'] = dict()
config['cond_ae_body']['is_label'] = False
config['cond_ae_body']['kernel_size'] = 7
config['cond_ae_body']['bottleneck_size'] = 16
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3]
config['cond_ae_body']['encoder_dims'] = [16, 32, 64, 128, config['cond_ae_body']['bottleneck_size']]
config['cond_ae_body']['decoder_depths'] = config['cond_ae_body']['encoder_depths']
config['cond_ae_body']['decoder_dims'] = config['cond_ae_body']['encoder_dims']
config['cond_ae_body']['activation'] = 'tanh'
cvae.py
+5 -3
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@@ -1,6 +1,6 @@
import os
import sys
from configs.config_abl_all_post import config
from configs.config_abl_all_10p_curv_10_r2 import config
os.environ["CUDA_VISIBLE_DEVICES"] = config['gpu']
import tensorflow as tf
@@ -494,7 +494,8 @@ if __name__ == '__main__':
use_one_hot=config['use_one_hot'],
use_no_orient=config['remove_global_orientation'],
frames_file=config['frames_file'] if 'frames_file' in config.keys() else None,
is_cape=config['is_cape'])
is_cape=config['is_cape'],
curv_neighbourhood=config['curv_neighbourhood'])
static_dataset_train = StaticDataset(folder=config['train_dir'],
signature=config['signature_static'],
resolutions=[config['resolution']],
@@ -509,7 +510,8 @@ if __name__ == '__main__':
use_one_hot=config['use_one_hot'],
use_no_orient=config['remove_global_orientation'],
frames_file=config['frames_file_valid'] if 'frames_file_valid' in config.keys() else None,
is_cape=config['is_cape'])
is_cape=config['is_cape'],
curv_neighbourhood=config['curv_neighbourhood'])
static_dataset_valid = StaticDataset(folder=config['valid_dir'],
signature=config['signature_static'],
resolutions=[config['resolution']],
dataset.py
+4 -3
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@@ -194,7 +194,8 @@ class DatasetFactory():
use_one_hot=False,
use_no_orient=True,
testing=False,
frames_file=None):
frames_file=None,
curv_neighbourhood=25):
assert set(resolutions).issubset(set([32, 64, 128, 256, 512]))
dataset_idx = DatasetIdx(folder, shuffle, is_cape=is_cape, testing=testing, frames_file=frames_file)
@@ -260,7 +261,7 @@ class DatasetFactory():
if 'mesh_curvature' in signature.keys():
mesh_curvature = np.load(os.path.join(folder, 'mesh_curvature', id + separator + frame_nr + '.npz')); mesh_curvature = mesh_curvature['mesh_curvature']
mesh_curvature = np.load(os.path.join(folder, f'mesh_curvature_{curv_neighbourhood}', id + separator + frame_nr + '.npz')); mesh_curvature = mesh_curvature['mesh_curvature']
item['mesh_curvature'] = mesh_curvature.astype(np.int32)
@@ -270,7 +271,7 @@ class DatasetFactory():
res_string = '_' + str(res)
if 'uv_curvature' + res_string in signature.keys():
uv_curvature = np.load(os.path.join(folder, 'uv_curvature' + res_string, id + separator + frame_nr + '.npz'));
uv_curvature = np.load(os.path.join(folder, f'uv_curvature_{curv_neighbourhood}' + res_string, id + separator + frame_nr + '.npz'));
if res_string != '':
uv_curvature = uv_curvature['uv_curvature']
else: