params.yaml

#seed: 1234
#torch_home:

#method: Deepfakes  # should be one of ['Deepfakes', 'Face2Face', 'FaceSwap', 'NeuralTextures']
#compression: c23   # should be one of ['c23', 'c40']
#exam_dir: data_${method}_${compression}

#transform_params:
#  image_size: 224
#  mean: [0.485, 0.456, 0.406]
#  std: [0.229, 0.224, 0.225]

# train,val设置相同的batch_size
batch_size: 6

train:
  num_workers: 8
#  print_info_step_freq: 1
#  max_epoches: 100
#  use_warmup: True
#  warmup_epochs: 1
  dataset:
    name: DeepfakeDataset
    params:
      #root: E:/DeepFakeDetection/datasets
#      root: /mnt/e/DeepFakeDetection/datasets/FF++
#      face_info_path: weights/ffpp_face_rects.pkl
#      method: ${method}
#      compression: ${compression}
      split: train
#      num_segments设置每个视频提取的帧数量
      num_segments: 2
      sparse_span: 150
#      dense_sample:

test:
  num_workers: 8
  dataset:
    name: DeepfakeDataset
    params:
      #root: E:/DeepFakeDetection/datasets
#      root: /mnt/e/DeepFakeDetection/datasets/FF++
#      face_info_path: weights/ffpp_face_rects.pkl
#      method: ${method}
#      compression: ${compression}
      split: val
      num_segments: 2
      sparse_span: 150

#model:
#  name: STILModel
#  params:
#    num_class: 2
#    num_segment: 8
#  resume:
#  only_resume_model: False
#  not_resume_layer_names:

#optimizer:
#  name: Adam
#  params:
#    lr: 0.001
#    weight_decay: 1.0e-5

#loss:
#  name: CrossEntropyLoss
#  params:

#scheduler:
#  name: piecewise
#  decay_epochs: [5, 20]
#  decay_rates: [0.1, 0.05]