detector_config.json

{
  "architecture": "FrequencyAwareDetector",
  "backbone_name": "microsoft/swinv2-tiny-patch4-window8-256",
  "num_labels": 2,
  "dct_patch_size": 32,
  "num_freq_bands": 8,
  "fft_bins": 32,
  "image_size": 256,
  "id2label": {
    "0": "real",
    "1": "ai_generated"
  },
  "label2id": {
    "real": 0,
    "ai_generated": 1
  },
  "srm_filters": 30,
  "srm_description": "Spatial Rich Model high-pass filter bank (Fridrich & Kodovsky, 2012)",
  "dct_description": "2D Discrete Cosine Transform patch-wise frequency band analysis",
  "fft_description": "Azimuthally averaged FFT power spectrum with 1/f deviation analysis",
  "backbone_description": "SwinV2-Tiny pretrained on ImageNet for semantic feature extraction",
  "training_dataset": "OwensLab/CommunityForensics-Small",
  "training_dataset_size": 556000,
  "num_generators": 4803,
  "total_params": 28604140,
  "social_media_augmentation": {
    "jpeg_compression": {"probability": 0.10, "quality_range": [30, 95]},
    "gaussian_blur": {"probability": 0.10, "sigma_range": [0.1, 2.0]},
    "downscale_upscale": {"probability": 0.05, "scale_range": [0.5, 0.9]}
  }
}