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fix

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luni
2023-02-28 20:00:09 +00:00
parent f479643be6
commit 6320275ea5
4 changed files with 17 additions and 13 deletions
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aaa_helpers.txt
+1
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@@ -15,6 +15,7 @@ nohup python cvae.py --name="lhunor_cvae_iccv_gnn_1" > nohup/iccv/cvae_iccv_gnn_
nohup python cvae.py --name="lhunor_abl_all" > nohup/iccv/ablation/abl_all.out 2>&1 & nohup python cvae.py --name="lhunor_abl_all" > nohup/iccv/ablation/abl_all.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_all_gnn" > nohup/iccv/ablation/abl_all_gnn.out 2>&1 & nohup python cvae.py --name="lhunor_abl_all_gnn" > nohup/iccv/ablation/abl_all_gnn.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_all_gnn_3" > nohup/iccv/ablation/abl_all_gnn_3.out 2>&1 &
nohup python upscale_test.py --name="iccv_32_2" > nohup/iccv/upscale/iccv_32_2.out 2>&1 & nohup python upscale_test.py --name="iccv_32_2" > nohup/iccv/upscale/iccv_32_2.out 2>&1 &
nohup python upscale_test.py --name="iccv_64_2" > nohup/iccv/upscale/iccv_64_2.out 2>&1 & nohup python upscale_test.py --name="iccv_64_2" > nohup/iccv/upscale/iccv_64_2.out 2>&1 &
configs/iccv/config_abl_all.py
+5 -5
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@@ -7,7 +7,7 @@ config = dict()
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512 # DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
# DON'T FORGET TO CHECK AVG GARMENT USED # DON'T FORGET TO CHECK AVG GARMENT USED
config['use_skinning'] = True # and deshaping config['use_skinning'] = False # and deshaping
config['remove_global_orientation'] = True config['remove_global_orientation'] = True
config['use_curvature'] = True config['use_curvature'] = True
config['use_extra_losses'] = True # edge, collision, 3d mesh config['use_extra_losses'] = True # edge, collision, 3d mesh
@@ -19,12 +19,12 @@ 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'] = '0' config['gpu'] = '2'
config['name'] = 'abl_all_gnn_2' config['name'] = 'abl_all_gnn_3'
config['notes'] = '' config['notes'] = ''
config['tags'] = ['iccv', 'abl_all_gnn'] config['tags'] = ['iccv', 'abl_all_gnn']
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 # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
if config['use_skinning']: if config['use_skinning']:
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '') assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
@@ -54,7 +54,7 @@ if config['is_cape']:
config['smpl_res'] = 3638 config['smpl_res'] = 3638
config['pretrained_model'] = 'checkpoints/iccv/abl_all' config['pretrained_model'] = 'checkpoints/iccv/abl_skin'
############### ###############
config['lr'] = 0.0001# 0.0001 config['lr'] = 0.0001# 0.0001
cvae.py
+3
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@@ -568,6 +568,9 @@ if __name__ == '__main__':
train_accumulator.reset() train_accumulator.reset()
valid_accumulator.reset() valid_accumulator.reset()
if step % 5000 == 0:
manager.save(checkpoint_number=step)
print(step) print(step)
step += 1 step += 1
models/gnn.py
+8 -8
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@@ -16,20 +16,20 @@ class Smoother(tf.keras.Model):
def __init__(self, ): def __init__(self, ):
super().__init__() super().__init__()
self.a = sp_matrix_to_sp_tensor(sio.loadmat("custom_utils/ssmpl0.mat")['L'].tocoo()) self.a = sp_matrix_to_sp_tensor(sio.loadmat("custom_utils/ssmpl0.mat")['L'].tocoo())
self.conv1 = GCNConv(512, activation='tanh', use_bias=False) self.conv1 = GCNConv(16, activation='tanh', use_bias=False)
self.conv2 = GCNConv(512, activation='tanh', use_bias=False) self.conv2 = GCNConv(3, activation='tanh', use_bias=False)
self.conv3 = GCNConv(512, activation='tanh', use_bias=False) # self.conv3 = GCNConv(512, activation='tanh', use_bias=False)
self.conv4 = GCNConv(512, activation='tanh', use_bias=False) # self.conv4 = GCNConv(512, activation='tanh', use_bias=False)
self.conv5 = GCNConv(64, activation='tanh', use_bias=False) # self.conv5 = GCNConv(64, activation='tanh', use_bias=False)
self.conv6 = GCNConv(3, activation='tanh', use_bias=False) self.conv6 = GCNConv(3, activation='tanh', use_bias=False)
def call(self, inputs, training=None): def call(self, inputs, training=None):
x = inputs x = inputs
x = self.conv1([x, self.a], training=training) x = self.conv1([x, self.a], training=training)
x = self.conv2([x, self.a], training=training) x = self.conv2([x, self.a], training=training)
x = self.conv3([x, self.a], training=training) # x = self.conv3([x, self.a], training=training)
x = self.conv4([x, self.a], training=training) # x = self.conv4([x, self.a], training=training)
x = self.conv5([x, self.a], training=training) # x = self.conv5([x, self.a], training=training)
x = self.conv6([x, self.a], training=training) x = self.conv6([x, self.a], training=training)
return x return x