message: training: data augmentation tweaks
diff: @@ -253,7 +253,7 @@ class TrainingDataset(PreprocessedDataset):
  # Generate a random crop
  sy = sx = self.tile_size
  - if np.random.rand() < 0.05:
  + if np.random.rand() < 0.1:
  # Randomly zero pad later to avoid artifacts for images that require padding
  sy -= np.random.randint(0, model.ALIGNMENT)
  sx -= np.random.randint(0, model.ALIGNMENT)
  @@ -307,7 +307,7 @@ class TrainingDataset(PreprocessedDataset):
  # Randomly zero the color channels if there are auxiliary features
  # This prevents "ghosting" artifacts when the color buffer is entirely black
  - if len(self.channels) > 3 and np.random.rand() < 0.005:
  + if len(self.channels) > 3 and np.random.rand() < 0.01:
  input_image[:, :, 0:3] = 0
  target_image[:] = 0
  