analyzer:
  device: cuda
  optimize_transforms: true
  reader:
    _target_: facetorch.analyzer.reader.ImageReader
    device:
      _target_: torch.device
      type: ${analyzer.device}
    optimize_transform: ${analyzer.optimize_transforms}
    transform:
      _target_: torchvision.transforms.Compose
      transforms:
      - _target_: facetorch.transforms.SquarePad
      - _target_: torchvision.transforms.Resize
        size:
        - 1080
  detector:
    _target_: facetorch.analyzer.detector.FaceDetector
    downloader:
      _target_: facetorch.downloader.DownloaderHuggingFace
      file_id: 154x2VjmTQVqmowB0yZw4Uck7uQs2vVBs
      path_local: /opt/facetorch/models/torchscript/detector/1/model.pt
      repo_id: tomas-gajarsky/facetorch-detector-retinaface
      filename: model.pt
    device:
      _target_: torch.device
      type: ${analyzer.device}
    reverse_colors: true
    preprocessor:
      _target_: facetorch.analyzer.detector.pre.DetectorPreProcessor
      transform:
        _target_: torchvision.transforms.Compose
        transforms:
        - _target_: torchvision.transforms.Normalize
          mean: [123.0, 117.0, 104.0]
          std:  [1.0, 1.0, 1.0]
      device:
        _target_: torch.device
        type: ${analyzer.device}
      optimize_transform: ${analyzer.optimize_transforms}
      reverse_colors: ${analyzer.detector.reverse_colors}
    postprocessor:
      _target_: facetorch.analyzer.detector.post.PostRetFace
      transform: None
      device:
        _target_: torch.device
        type: ${analyzer.device}
      optimize_transform: ${analyzer.optimize_transforms}
      confidence_threshold: 0.02
      top_k: 5000
      nms_threshold: 0.4
      keep_top_k: 750
      score_threshold: 0.6
      prior_box:
        _target_: facetorch.analyzer.detector.post.PriorBox
        min_sizes:
        - [16, 32]
        - [64, 128]
        - [256, 512]
        steps: [8, 16, 32]
        clip: false
      variance: [0.1, 0.2]
      reverse_colors: ${analyzer.detector.reverse_colors}
      expand_box_ratio: 0.1
  unifier:
    _target_: facetorch.analyzer.unifier.FaceUnifier
    transform:
      _target_: torchvision.transforms.Compose
      transforms:
      - _target_: torchvision.transforms.Normalize
        mean: [-123.0, -117.0, -104.0]
        std:  [255.0, 255.0, 255.0]
      - _target_: torchvision.transforms.Resize
        size: [380, 380]
    device:
      _target_: torch.device
      type: ${analyzer.device}
    optimize_transform: ${analyzer.optimize_transforms}
  predictor:
    embed:
      _target_: facetorch.analyzer.predictor.FacePredictor
      downloader:
        _target_: facetorch.downloader.DownloaderHuggingFace
        file_id: 19h3kqar1wlELAmM5hDyj9tlrUh8yjrCl
        path_local: /opt/facetorch/models/torchscript/predictor/embed/1/model.pt
        repo_id: tomas-gajarsky/facetorch-embed-resnet-50
        filename: model.pt
      device:
        _target_: torch.device
        type: ${analyzer.device}
      preprocessor:
        _target_: facetorch.analyzer.predictor.pre.PredictorPreProcessor
        transform:
          _target_: torchvision.transforms.Compose
          transforms:
          - _target_: torchvision.transforms.Resize
            size: [244, 244]
          - _target_: torchvision.transforms.Normalize
            mean: [0.485, 0.456, 0.406]
            std:  [0.228, 0.224, 0.225]
        device:
          _target_: torch.device
          type: ${analyzer.predictor.fer.device.type}
        optimize_transform: ${analyzer.optimize_transforms}
        reverse_colors: false
      postprocessor:
        _target_: facetorch.analyzer.predictor.post.PostEmbedder
        transform: None
        device:
          _target_: torch.device
          type: ${analyzer.predictor.fer.device.type}
        optimize_transform: ${analyzer.optimize_transforms}
        labels: [abstract]
    verify:
      _target_: facetorch.analyzer.predictor.FacePredictor
      downloader:
        _target_: facetorch.downloader.DownloaderHuggingFace
        file_id: 1H-aPtFd9C5D7y1vzoWsObKAxeIBE9QPd
        path_local: /opt/facetorch/models/torchscript/predictor/verify/1/model.pt
        repo_id: tomas-gajarsky/facetorch-verify-adaface
        filename: model.pt
      device:
        _target_: torch.device
        type: ${analyzer.device}
      preprocessor:
        _target_: facetorch.analyzer.predictor.pre.PredictorPreProcessor
        transform:
          _target_: torchvision.transforms.Compose
          transforms:
          - _target_: torchvision.transforms.Resize
            size: [112, 112]
          - _target_: torchvision.transforms.Normalize
            mean: [0.485, 0.456, 0.406]
            std:  [0.229, 0.224, 0.225]
        device:
          _target_: torch.device
          type: ${analyzer.predictor.verify.device.type}
        optimize_transform: ${analyzer.optimize_transforms}
        reverse_colors: false
      postprocessor:
        _target_: facetorch.analyzer.predictor.post.PostEmbedder
        transform: None
        device:
          _target_: torch.device
          type: ${analyzer.predictor.verify.device.type}
        optimize_transform: ${analyzer.optimize_transforms}
        labels: [abstract]
    fer:
      _target_: facetorch.analyzer.predictor.FacePredictor
      downloader:
        _target_: facetorch.downloader.DownloaderHuggingFace
        file_id: 1xoB5VYOd0XLjb-rQqqHWCkQvma4NytEd
        path_local: /opt/facetorch/models/torchscript/predictor/fer/2/model.pt
        repo_id: tomas-gajarsky/facetorch-fer-efficientnet-b2
        filename: model.pt
      device:
        _target_: torch.device
        type: ${analyzer.device}
      preprocessor:
        _target_: facetorch.analyzer.predictor.pre.PredictorPreProcessor
        transform:
          _target_: torchvision.transforms.Compose
          transforms:
          - _target_: torchvision.transforms.Resize
            size: [260, 260]
          - _target_: torchvision.transforms.Normalize
            mean: [0.485, 0.456, 0.406]
            std:  [0.229, 0.224, 0.225]
        device:
          _target_: torch.device
          type: ${analyzer.predictor.fer.device.type}
        optimize_transform: ${analyzer.optimize_transforms}
        reverse_colors: false
      postprocessor:
        _target_: facetorch.analyzer.predictor.post.PostArgMax
        transform: None
        device:
          _target_: torch.device
          type: ${analyzer.predictor.fer.device.type}
        optimize_transform: ${analyzer.optimize_transforms}
        dim: 1
        labels:
        - Anger
        - Contempt
        - Disgust
        - Fear
        - Happiness
        - Neutral
        - Sadness
        - Surprise
    au:
      _target_: facetorch.analyzer.predictor.FacePredictor
      downloader:
        _target_: facetorch.downloader.DownloaderHuggingFace
        file_id: 1uoVX9suSA5JVWTms3hEtJKzwO-CUR_jV
        path_local: /opt/facetorch/models/torchscript/predictor/au/1/model.pt
        repo_id: tomas-gajarsky/facetorch-au-opengraph
        filename: model.pt
      device:
        _target_: torch.device
        type: ${analyzer.device}  # str
      preprocessor:
        _target_: facetorch.analyzer.predictor.pre.PredictorPreProcessor
        transform:
          _target_: torchvision.transforms.Compose
          transforms:
          - _target_: torchvision.transforms.Resize
            size: [224, 224]            # List[int]
          - _target_: torchvision.transforms.Normalize
            mean: [0.485, 0.456, 0.406] # List[float]
            std:  [0.229, 0.224, 0.225] # List[float]
        device:
          _target_: torch.device
          type: ${analyzer.predictor.au.device.type}
        optimize_transform: ${analyzer.optimize_transforms}
        reverse_colors: False           # bool
      postprocessor:
        _target_: facetorch.analyzer.predictor.post.PostMultiLabel
        transform: None
        device:
          _target_: torch.device
          type: ${analyzer.predictor.au.device.type}
        optimize_transform: ${analyzer.optimize_transforms}
        dim: 1
        threshold: 0.5
        labels:
        - inner_brow_raiser
        - outer_brow_raiser
        - brow_lowerer
        - upper_lid_raiser
        - cheek_raiser
        - lid_tightener
        - nose_wrinkler
        - upper_lip_raiser
        - nasolabial_deepener
        - lip_corner_puller
        - sharp_lip_puller
        - dimpler
        - lip_corner_depressor
        - lower_lip_depressor
        - chin_raiser
        - lip_pucker
        - tongue_show
        - lip_stretcher
        - lip_funneler
        - lip_tightener
        - lip_pressor
        - lips_part
        - jaw_drop
        - mouth_stretch
        - lip_bite
        - nostril_dilator
        - nostril_compressor
        - left_inner_brow_raiser
        - right_inner_brow_raiser
        - left_outer_brow_raiser
        - right_outer_brow_raiser
        - left_brow_lowerer
        - right_brow_lowerer
        - left_cheek_raiser
        - right_cheek_raiser
        - left_upper_lip_raiser
        - right_upper_lip_raiser
        - left_nasolabial_deepener
        - right_nasolabial_deepener
        - left_dimpler
        - right_dimpler
    va:
      _target_: facetorch.analyzer.predictor.FacePredictor
      downloader:
        _target_: facetorch.downloader.DownloaderHuggingFace
        file_id: 1Xl4ilNCU_DgKNhITrXb3UyQUUdm3VTKS
        path_local: /opt/facetorch/models/torchscript/predictor/va/1/model.pt
        repo_id: tomas-gajarsky/facetorch-va-elim
        filename: model.pt
      device:
        _target_: torch.device
        type: ${analyzer.device}
      preprocessor:
        _target_: facetorch.analyzer.predictor.pre.PredictorPreProcessor
        transform:
          _target_: torchvision.transforms.Compose
          transforms:
          - _target_: torchvision.transforms.Resize
            size: [224, 224]
            antialias: true
          - _target_: torchvision.transforms.Normalize
            mean: [0.485, 0.456, 0.406]
            std:  [0.229, 0.224, 0.225]
        device:
          _target_: torch.device
          type: ${analyzer.predictor.va.device.type}
        optimize_transform: ${analyzer.optimize_transforms}
        reverse_colors: false
      postprocessor:
        _target_: facetorch.analyzer.predictor.post.PostLabelConfidencePairs
        transform: None
        device:
          _target_: torch.device
          type: ${analyzer.predictor.va.device.type}
        optimize_transform: ${analyzer.optimize_transforms}
        labels: [valence, arousal]
    deepfake:
      _target_: facetorch.analyzer.predictor.FacePredictor
      downloader:
        _target_: facetorch.downloader.DownloaderHuggingFace
        file_id: 1GjDTwQpvrkCjXOdiBy1oMkzm7nt-bXFg
        path_local: /opt/facetorch/models/torchscript/predictor/deepfake/1/model.pt
        repo_id: tomas-gajarsky/facetorch-deepfake-efficientnet-b7
        filename: model.pt
      device:
        _target_: torch.device
        type: ${analyzer.device}
      preprocessor:
        _target_: facetorch.analyzer.predictor.pre.PredictorPreProcessor
        transform:
          _target_: torchvision.transforms.Compose
          transforms:
          - _target_: torchvision.transforms.Resize
            size: [380, 380]
          - _target_: torchvision.transforms.Normalize
            mean: [0.485, 0.456, 0.406]
            std:  [0.229, 0.224, 0.225]
        device:
          _target_: torch.device
          type: ${analyzer.device}
        optimize_transform: ${analyzer.optimize_transforms}
        reverse_colors: false
      postprocessor:
        _target_: facetorch.analyzer.predictor.post.PostSigmoidBinary
        transform: None
        device:
          _target_: torch.device
          type: ${analyzer.device}
        optimize_transform: ${analyzer.optimize_transforms}
        labels: [Real, Fake]
        threshold: 0.7
    align:
      _target_: facetorch.analyzer.predictor.FacePredictor
      downloader:
        _target_: facetorch.downloader.DownloaderHuggingFace
        file_id: 16gNFQdEH2nWvW3zTbdIAniKIbPAp6qBA
        path_local: /opt/facetorch/models/torchscript/predictor/align/1/model.pt
        repo_id: tomas-gajarsky/facetorch-align-synergynet
        filename: model.pt
      device:
        _target_: torch.device
        type: ${analyzer.device}
      preprocessor:
        _target_: facetorch.analyzer.predictor.pre.PredictorPreProcessor
        transform:
          _target_: torchvision.transforms.Compose
          transforms:
          - _target_: torchvision.transforms.Resize
            size: [120, 120]
        device:
          _target_: torch.device
          type: ${analyzer.predictor.align.device.type}
        optimize_transform: ${analyzer.optimize_transforms}
        reverse_colors: false
      postprocessor:
        _target_: facetorch.analyzer.predictor.post.PostEmbedder
        transform: None
        device:
          _target_: torch.device
          type: ${analyzer.predictor.align.device.type}
        optimize_transform: ${analyzer.optimize_transforms}
        labels: [abstract]
  utilizer:
    align:
      _target_: facetorch.analyzer.utilizer.align.Lmk3DMeshPose
      transform: None
      device:
        _target_: torch.device
        type: ${analyzer.device}
      optimize_transform: false
      downloader_meta:
        _target_: facetorch.downloader.DownloaderGDrive   # (unchanged)
        file_id: 11tdAcFuSXqCCf58g52WT1Rpa8KuQwe2o
        path_local: /opt/facetorch/data/3dmm/meta.pt
      image_size: 120
    draw_boxes:
      _target_: facetorch.analyzer.utilizer.draw.BoxDrawer
      transform: None
      device:
        _target_: torch.device
        type: ${analyzer.device}
      optimize_transform: false
      color: green
      line_width: 3
    draw_landmarks:
      _target_: facetorch.analyzer.utilizer.draw.LandmarkDrawerTorch
      transform: None
      device:
        _target_: torch.device
        type: ${analyzer.device}
      optimize_transform: false
      width: 2
      color: green
  logger:
    _target_: facetorch.logger.LoggerJsonFile
    name: facetorch
    level: 10
    path_file: /home/user/code/logs/facetorch/main.log
    json_format: '%(asctime)s %(levelname)s %(message)s'
main:
  sleep: 3
debug: true
batch_size: 8
fix_img_size: true
return_img_data: true
include_tensors: true