From 40924b5f74dc759fab39df1ccaef4a0a2306ba32 Mon Sep 17 00:00:00 2001 From: jh Date: Wed, 17 Mar 2021 12:13:28 -0700 Subject: [PATCH] test --- models/Model_SAEHD/Model.py | 24 +++++------------------- 1 file changed, 5 insertions(+), 19 deletions(-) diff --git a/models/Model_SAEHD/Model.py b/models/Model_SAEHD/Model.py index 2c706af..6ae3fb5 100644 --- a/models/Model_SAEHD/Model.py +++ b/models/Model_SAEHD/Model.py @@ -446,28 +446,14 @@ Examples: df, liae, df-d, df-ud, liae-ud, ... gpu_target_part_mask = gpu_target_srcm_mouth if self.options['ms_ssim_loss']: - # FIXME - ms_ssim_loss = nn.MsSsim(resolution, kernel_size=5)(gpu_target_src*gpu_target_part_mask, gpu_pred_src_src*gpu_target_part_mask, max_val=1.0) - print('ms_ssim_loss.shape: ', ms_ssim_loss.shape) - ms_ssim_mean_loss = tf.reduce_mean(300 * ms_ssim_loss) - print('ms_ssim_mean_loss.shape: ', ms_ssim_mean_loss.shape) - abs_loss = tf.abs ( gpu_target_src*gpu_target_part_mask - gpu_pred_src_src*gpu_target_part_mask ) - print('abs_loss.shape: ', abs_loss.shape) - abs_mean_loss = tf.reduce_mean(300 * abs_loss, axis=[1,2,3]) - print('abs_mean_loss.shape: ', abs_mean_loss.shape) - gpu_src_loss += 300*nn.MsSsim(resolution, kernel_size=5)(gpu_target_src*gpu_target_part_mask, gpu_pred_src_src*gpu_target_part_mask, max_val=1.0) - - # gpu_src_loss += tf.reduce_mean ( 300*nn.MsSsim(resolution, kernel_size=5)(gpu_target_src*gpu_target_part_mask, gpu_pred_src_src*gpu_target_part_mask, max_val=1.0)) + gpu_src_loss += 300 * nn.MsSsim(resolution, kernel_size=5)(gpu_target_src*gpu_target_part_mask, gpu_pred_src_src*gpu_target_part_mask, max_val=1.0) else: gpu_src_loss += tf.reduce_mean ( 300*tf.abs ( gpu_target_src*gpu_target_part_mask - gpu_pred_src_src*gpu_target_part_mask ), axis=[1,2,3]) - # FIXME - # if self.options['ms_ssim_loss']: - # gpu_src_loss += tf.reduce_mean ( 10*nn.MsSsim(resolution)(gpu_target_srcm, gpu_pred_src_srcm, max_val=1.0)) - # else: - print('gpu_target_srcm.shape:', gpu_target_srcm.shape) - print('gpu_pred_src_srcm.shape:', gpu_pred_src_srcm.shape) - gpu_src_loss += tf.reduce_mean ( 10*tf.square( gpu_target_srcm - gpu_pred_src_srcm ),axis=[1,2,3] ) + if self.options['ms_ssim_loss']: + gpu_src_loss += 10 * nn.MsSsim(resolution)(gpu_target_srcm, gpu_pred_src_srcm, max_val=1.0) + else: + gpu_src_loss += tf.reduce_mean ( 10*tf.square( gpu_target_srcm - gpu_pred_src_srcm ),axis=[1,2,3] ) face_style_power = self.options['face_style_power'] / 100.0 if face_style_power != 0 and not self.pretrain: