Upload spsl.yaml

spsl.yaml

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+# log dir 
+log_dir: /mntcephfs/lab_data/zhiyuanyan/benchmark_results/logs_final/spsl_4frames
+
+# model setting
+pretrained: /data/home/zhiyuanyan/DeepfakeBench/training/pretrained/xception-b5690688.pth   # path to a pre-trained model, if using one
+# pretrained: /home/tianshuoge/resnet34-b627a593.pth   # path to a pre-trained model, if using one
+model_name: spsl   # model name
+backbone_name: xception  # backbone name
+
+#backbone setting
+backbone_config:
+  mode: original  # shallow_xception
+  num_classes: 2
+  inc: 4
+  dropout: false
+
+# dataset
+all_dataset: [FaceForensics++, FF-F2F, FF-DF, FF-FS, FF-NT, FaceShifter, DeepFakeDetection, Celeb-DF-v1, Celeb-DF-v2, DFDCP, DFDC, DeeperForensics-1.0, UADFV]
+train_dataset: [FF-FS]
+test_dataset: [FaceForensics++, FF-F2F, FF-DF, FF-FS, FF-NT]
+
+compression: c23  # compression-level for videos
+train_batchSize: 32   # training batch size
+test_batchSize: 32   # test batch size
+workers: 8   # number of data loading workers
+frame_num: {'train': 4, 'test': 32}   # number of frames to use per video in training and testing
+resolution: 256   # resolution of output image to network
+with_mask: false   # whether to include mask information in the input
+with_landmark: false   # whether to include facial landmark information in the input
+save_ckpt: true   # whether to save checkpoint
+save_feat: true   # whether to save features
+
+
+# data augmentation
+use_data_augmentation: true  # Add this flag to enable/disable data augmentation
+data_aug:
+  flip_prob: 0.5
+  rotate_prob: 0.5
+  rotate_limit: [-10, 10]
+  blur_prob: 0.5
+  blur_limit: [3, 7]
+  brightness_prob: 0.5
+  brightness_limit: [-0.1, 0.1]
+  contrast_limit: [-0.1, 0.1]
+  quality_lower: 40
+  quality_upper: 100
+
+# mean and std for normalization
+mean: [0.5, 0.5, 0.5]
+std: [0.5, 0.5, 0.5]
+
+# optimizer config
+optimizer:
+  # choose between 'adam' and 'sgd'
+  type: adam
+  adam:
+    lr: 0.0002  # learning rate
+    beta1: 0.9  # beta1 for Adam optimizer
+    beta2: 0.999 # beta2 for Adam optimizer
+    eps: 0.00000001  # epsilon for Adam optimizer
+    weight_decay: 0.0005  # weight decay for regularization
+    amsgrad: false
+  sgd:
+    lr: 0.0002  # learning rate
+    momentum: 0.9  # momentum for SGD optimizer
+    weight_decay: 0.0005  # weight decay for regularization
+
+# training config
+lr_scheduler: null   # learning rate scheduler
+nEpochs: 10   # number of epochs to train for
+start_epoch: 0   # manual epoch number (useful for restarts)
+save_epoch: 1   # interval epochs for saving models
+rec_iter: 100   # interval iterations for recording
+logdir: ./logs   # folder to output images and logs
+manualSeed: 1024   # manual seed for random number generation
+save_ckpt: false   # whether to save checkpoint
+
+# loss function
+loss_func: cross_entropy   # loss function to use
+losstype: null
+
+# metric
+metric_scoring: auc   # metric for evaluation (auc, acc, eer, ap)
+
+# cuda
+
+cuda: true   # whether to use CUDA acceleration
+cudnn: true   # whether to use CuDNN for convolution operations