refine code

applications/first_order_model/configs/vox-256.yaml

-dataset_params:
-  root_dir: data/vox-png
-  frame_shape: [256, 256, 3]
-  id_sampling: True
-  pairs_list: data/vox256.csv
-  augmentation_params:
-    flip_param:
-      horizontal_flip: True
-      time_flip: True
-    jitter_param:
-      brightness: 0.1
-      contrast: 0.1
-      saturation: 0.1
-      hue: 0.1
-
-
 model_params:
   common_params:
     num_kp: 10
@@ -42,42 +26,3 @@ model_params:
     max_features: 512
     num_blocks: 4
     sn: True
-
-train_params:
-  num_epochs: 100
-  num_repeats: 75
-  epoch_milestones: [60, 90]
-  lr_generator: 2.0e-4
-  lr_discriminator: 2.0e-4
-  lr_kp_detector: 2.0e-4
-  batch_size: 40
-  scales: [1, 0.5, 0.25, 0.125]
-  checkpoint_freq: 50
-  transform_params:
-    sigma_affine: 0.05
-    sigma_tps: 0.005
-    points_tps: 5
-  loss_weights:
-    generator_gan: 0
-    discriminator_gan: 1
-    feature_matching: [10, 10, 10, 10]
-    perceptual: [10, 10, 10, 10, 10]
-    equivariance_value: 10
-    equivariance_jacobian: 10
-
-reconstruction_params:
-  num_videos: 1000
-  format: '.mp4'
-
-animate_params:
-  num_pairs: 50
-  format: '.mp4'
-  normalization_params:
-    adapt_movement_scale: False
-    use_relative_movement: True
-    use_relative_jacobian: True
-
-visualizer_params:
-  kp_size: 5
-  draw_border: True
-  colormap: 'gist_rainbow'

applications/tools/first-order-demo.py

+# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import matplotlib
 matplotlib.use('Agg')
 import os
@@ -5,20 +19,20 @@ import sys
 
 import yaml
 import pickle
-from argparse import ArgumentParser
-from tqdm import tqdm
-
 import imageio
 import numpy as np
-from skimage.transform import resize
+
+from tqdm import tqdm
 from skimage import img_as_ubyte
-import paddle
+from argparse import ArgumentParser
+from skimage.transform import resize
+from scipy.spatial import ConvexHull
 
 from ppgan.models.generators.occlusion_aware import OcclusionAwareGenerator
 from ppgan.modules.keypoint_detector import KPDetector
 from ppgan.utils.animate import normalize_kp
-from scipy.spatial import ConvexHull
 
+import paddle
 paddle.disable_static()
 
 if sys.version_info[0] < 3:
@@ -60,8 +74,7 @@ def make_animation(source_image,
         predictions = []
         source = paddle.to_tensor(source_image[np.newaxis].astype(
             np.float32)).transpose([0, 3, 1, 2])
-        # if not cpu:
-        #     source = source.cuda()
+
         driving = paddle.to_tensor(
             np.array(driving_video)[np.newaxis].astype(np.float32)).transpose(
                 [0, 4, 1, 2, 3])

applications/tools/video-enhance.py

+# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import sys
 sys.path.append('.')
 

ppgan/utils/animate.py

-import os
-from tqdm import tqdm
+import numpy as np
+from scipy.spatial import ConvexHull
 
 import paddle
 
-import imageio
-from scipy.spatial import ConvexHull
-import numpy as np
-
 
 def normalize_kp(kp_source,
                  kp_driving,