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| author | Jordan Gong <jordan.gong@protonmail.com> | 2021-02-18 18:38:31 +0800 |
|---|---|---|
| committer | Jordan Gong <jordan.gong@protonmail.com> | 2021-02-18 18:38:31 +0800 |
| commit | 8012fce3e595aad31f4a52dc316b46e558234dff (patch) | |
| tree | 4a5e19a21ad8a4470931f5884777c127197153c0 /models/model.py | |
| parent | 2988c1b9afd4e869b629a8629abedbf63d2452aa (diff) | |
| parent | 84a3d5991f2f7272d1be54ad6cfe6ce695f915a0 (diff) | |
Merge branch 'master' into data_parallel_py3.8
Diffstat (limited to 'models/model.py')
| -rw-r--r-- | models/model.py | 14 |
1 files changed, 8 insertions, 6 deletions
diff --git a/models/model.py b/models/model.py index 2715b26..3d619fe 100644 --- a/models/model.py +++ b/models/model.py @@ -55,6 +55,7 @@ class Model: self.is_train: bool = True self.in_channels: int = 3 + self.in_size: tuple[int, int] = (64, 48) self.pr: Optional[int] = None self.k: Optional[int] = None @@ -147,7 +148,7 @@ class Model: hpm_optim_hp = optim_hp.pop('hpm', {}) fc_optim_hp = optim_hp.pop('fc', {}) sched_hp = self.hp.get('scheduler', {}) - self.rgb_pn = RGBPartNet(self.in_channels, **model_hp, + self.rgb_pn = RGBPartNet(self.in_channels, self.in_size, **model_hp, image_log_on=self.image_log_on) # Try to accelerate computation using CUDA or others self.rgb_pn = nn.DataParallel(self.rgb_pn) @@ -230,16 +231,16 @@ class Model: if self.image_log_on: i_a, i_c, i_p = images self.writer.add_images( + 'Appearance image', i_a, self.curr_iter + ) + self.writer.add_images( 'Canonical image', i_c, self.curr_iter ) - for (i, (o, a, p)) in enumerate(zip(x_c1, i_a, i_p)): + for i, (o, p) in enumerate(zip(x_c1, i_p)): self.writer.add_images( f'Original image/batch {i}', o, self.curr_iter ) self.writer.add_images( - f'Appearance image/batch {i}', a, self.curr_iter - ) - self.writer.add_images( f'Pose image/batch {i}', p, self.curr_iter ) time_used = datetime.now() - start_time @@ -306,7 +307,7 @@ class Model: # Init models model_hp = self.hp.get('model', {}) - self.rgb_pn = RGBPartNet(ae_in_channels=self.in_channels, **model_hp) + self.rgb_pn = RGBPartNet(self.in_channels, self.in_size, **model_hp) # Try to accelerate computation using CUDA or others self.rgb_pn = nn.DataParallel(self.rgb_pn) self.rgb_pn = self.rgb_pn.to(self.device) @@ -467,6 +468,7 @@ class Model: dataset_config: DatasetConfiguration ) -> Union[CASIAB]: self.in_channels = dataset_config.get('num_input_channels', 3) + self.in_size = dataset_config.get('frame_size', (64, 48)) self._dataset_sig = self._make_signature( dataset_config, popped_keys=['root_dir', 'cache_on'] |