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pyramid with common encoders per level

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luni
2022-09-16 20:51:31 +00:00
parent eac8aad8ab
commit 37df8468e2
3 changed files with 81 additions and 26 deletions
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models/cvae_pyramid_model.py
+32 -5
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@@ -12,15 +12,39 @@ from models.cvae_model import CVAE, CVAE128, CVAE32
class Pyramid(tf.keras.Model):
def __init__(self, low_res=32, latent_dim=128, avg_garment_path=''):
def __init__(self, low_res=32,
latent_dim=128,
avg_garment_path='',
static_model='',
body_model='',
curvature_model='',
freeze_encoders=False,
use_full_res_encoders=True):
super(Pyramid, self).__init__()
if low_res == 32:
self.model_low = CVAE32(latent_dim=latent_dim)
self.model_low = CVAE32(latent_dim=latent_dim,
static_model=static_model,
body_model=body_model,
curvature_model=curvature_model,
freeze_encoders=freeze_encoders,
use_full_res_encoders=use_full_res_encoders)
if low_res == 128:
self.model_low = CVAE128(latent_dim=latent_dim)
self.model_full = CVAE(latent_dim=latent_dim)
self.model_low = CVAE128(latent_dim=latent_dim,
static_model=static_model,
body_model=body_model,
curvature_model=curvature_model,
freeze_encoders=freeze_encoders,
use_full_res_encoders=use_full_res_encoders)
self.model_full = CVAE(latent_dim=latent_dim,
static_model=static_model,
body_model=body_model,
curvature_model=curvature_model,
freeze_encoders=freeze_encoders)
self.use_full_res_encoders = use_full_res_encoders
if avg_garment_path != '':
self.avg_garment = np.load(avg_garment_path)
else:
@@ -29,7 +53,10 @@ class Pyramid(tf.keras.Model):
def call(self, inputs, training=None):
uv_unposed, uv_static, uv_body_posed, uv_curv, uv_unposed_low, uv_static_low, uv_body_posed_low, uv_curv_low = inputs
pred_low, mean_low, logvar_low, _ = self.model_low([uv_unposed_low, uv_static_low, uv_body_posed_low, uv_curv_low], training=training)
if self.use_full_res_encoders:
pred_low, mean_low, logvar_low, _ = self.model_low([uv_unposed_low, uv_static_low, uv_body_posed_low, uv_curv_low, uv_static, uv_body_posed, uv_curv], training=training)
else:
pred_low, mean_low, logvar_low, _ = self.model_low([uv_unposed_low, uv_static_low, uv_body_posed_low, uv_curv_low], training=training)
x = tf.image.resize(pred_low, (512, 256), tf.image.ResizeMethod.LANCZOS5)