TAFG 0.01

configs/synthesizers/TAFG.yml

@@ -49,7 +49,7 @@ loss:
     criterion: 'L1'
     style_loss: False
     perceptual_loss: True
-    weight: 1
+    weight: 5
   style:
     layer_weights:
       "1": 0.03125
@@ -63,10 +63,10 @@ loss:
     weight: 0
   fm:
     level: 1
-    weight: 1
+    weight: 10
   recon:
     level: 1
-    weight: 1
+    weight: 5
 
 optimizers:
   generator:
@@ -97,7 +97,8 @@ data:
       root_a: "/data/i2i/VoxCeleb2Anime/trainA"
       root_b: "/data/i2i/VoxCeleb2Anime/trainB"
       edges_path: "/data/i2i/VoxCeleb2Anime/edges"
-      edge_type: "hed"
+      landmarks_path: "/data/i2i/VoxCeleb2Anime/landmarks"
+      edge_type: "landmark_canny"
       size: [128, 128]
       random_pair: True
       pipeline:

configs/synthesizers/TAHG.yml

@@ -1,129 +0,0 @@
-name: TAHG
-engine: TAHG
-result_dir: ./result
-max_pairs: 1000000
-
-misc:
-  random_seed: 324
-
-checkpoint:
-  epoch_interval: 1 # one checkpoint every 1 epoch
-  n_saved: 2
-
-interval:
-  print_per_iteration: 10 # print once per 10 iteration
-  tensorboard:
-    scalar: 100
-    image: 2
-
-model:
-  generator:
-    _type: TAHG-Generator
-    _bn_to_sync_bn: False
-    style_in_channels: 3
-    content_in_channels: 1
-    num_blocks: 4
-  discriminator:
-    _type: TAHG-Discriminator
-    in_channels: 3
-
-loss:
-  gan:
-    loss_type: lsgan
-    real_label_val: 1.0
-    fake_label_val: 0.0
-    weight: 1.0
-  edge:
-    criterion: 'L1'
-    hed_pretrained_model_path: "./network-bsds500.pytorch"
-    weight: 1
-  perceptual:
-    layer_weights:
-      "3": 1.0
-#      "0": 1.0
-#      "5": 1.0
-#      "10": 1.0
-#      "19": 1.0
-    criterion: 'L2'
-    style_loss: True
-    perceptual_loss: False
-    weight: 20
-  recon:
-    level: 1
-    weight: 1
-
-optimizers:
-  generator:
-    _type: Adam
-    lr: 0.0001
-    betas: [ 0.5, 0.999 ]
-    weight_decay: 0.0001
-  discriminator:
-    _type: Adam
-    lr: 1e-4
-    betas: [ 0.5, 0.999 ]
-    weight_decay: 0.0001
-
-data:
-  train:
-    scheduler:
-      start_proportion: 0.5
-      target_lr: 0
-    buffer_size: 50
-    dataloader:
-      batch_size: 160
-      shuffle: True
-      num_workers: 2
-      pin_memory: True
-      drop_last: True
-    dataset:
-      _type: GenerationUnpairedDatasetWithEdge
-      root_a: "/data/i2i/VoxCeleb2Anime/trainA"
-      root_b: "/data/i2i/VoxCeleb2Anime/trainB"
-      edges_path: "/data/i2i/VoxCeleb2Anime/edges"
-      edge_type: "hed"
-      size: [128, 128]
-      random_pair: True
-      pipeline:
-        - Load
-        - Resize:
-            size: [128, 128]
-        - ToTensor
-        - Normalize:
-            mean: [ 0.5, 0.5, 0.5 ]
-            std: [ 0.5, 0.5, 0.5 ]
-  test:
-    dataloader:
-      batch_size: 8
-      shuffle: False
-      num_workers: 1
-      pin_memory: False
-      drop_last: False
-    dataset:
-      _type: GenerationUnpairedDatasetWithEdge
-      root_a: "/data/i2i/VoxCeleb2Anime/testA"
-      root_b: "/data/i2i/VoxCeleb2Anime/testB"
-      edges_path: "/data/i2i/VoxCeleb2Anime/edges"
-      edge_type: "hed"
-      random_pair: False
-      size: [128, 128]
-      pipeline:
-        - Load
-        - Resize:
-            size: [128, 128]
-        - ToTensor
-        - Normalize:
-            mean: [ 0.5, 0.5, 0.5 ]
-            std: [ 0.5, 0.5, 0.5 ]
-    video_dataset:
-      _type: SingleFolderDataset
-      root: "/data/i2i/VoxCeleb2Anime/test_video_frames/"
-      with_path: True
-      pipeline:
-        - Load
-        - Resize:
-            size: [ 256, 256 ]
-        - ToTensor
-        - Normalize:
-            mean: [ 0.5, 0.5, 0.5 ]
-            std: [ 0.5, 0.5, 0.5 ]