run-35

stylegan2/generator.py

@@ -105,8 +105,8 @@ class Generator(tf.keras.Model):
 
         image_out = self.synthesis(w_broadcasted)
         # image_out = image_out + conditions[2]
-        image_out = image_out + self.zero_body[:image_out.shape[0]]
-        image_out = image_out * conditions[3][:,tf.newaxis,:,:]
+        image_out = image_out + conditions['uv_shaped_body']
+        image_out = image_out * conditions['uv_mask'][:,tf.newaxis,:,:]
 
         if ret_w_broadcasted:
             return image_out, w_broadcasted

stylegan2/layers/embedding.py

@@ -97,6 +97,7 @@ class GarmentEmbedding(tf.keras.layers.Layer):
 
     def call(self, inputs, training=None, mask=None):
         x = inputs
+        x = tf.image.per_image_standardization(x)
 
         x = tf.transpose(x, [0,2,3,1])
         x = self.encoder(x, training=training)

stylegan2/layers/mapping_block.py

@@ -31,8 +31,8 @@ class Mapping(tf.keras.layers.Layer):
         x = latents
 
         # embed label if any
-        pose_shape_latent = self.pose_shape_embedding([conditions[0], conditions[1]])
-        garment_latent = self.garment_embedding(conditions[2])
+        pose_shape_latent = self.pose_shape_embedding([conditions['pose_shape'][:, :72], conditions['pose_shape'][:, 72:]])
+        garment_latent = self.garment_embedding(conditions['uv_static'])
         x = tf.concat([x, pose_shape_latent, garment_latent], axis=1)
         # x = tf.concat([x, garment_latent], axis=1)