# retrieval settings

datasets:
  # number of images in a batch.
  batch_size: 16

  # function for stacking images in a batch.
  collate_fn:
    name: "CollateFn"

  # function for loading images.
  folder:
    name: "Folder"

  # a list of data augmentation functions.
  transformers:
    names: ["DirectResize", "TwoFlip", "ToTensor", "Normalize"]  # names of transformers.
    DirectResize:
      size: (256, 128)  # target size of the output img.
      interpolation: 3  # nearest interpolation
    Normalize:
      mean: [0.485, 0.456, 0.406]
      std: [0.229, 0.224, 0.225]

model:
  name: "ft_net"  # name of the model.
  ft_net:
    load_checkpoint: "/home/songrenjie/projects/reID_baseline/model/ft_ResNet50/res50_duke.pth"  # path of the model checkpoint, If it is started with "torchvision://", the model will be loaded from torchvision.

extract:
  # way to assemble features if transformers produce multiple images (e.g. TwoFlip, TenCrop). 0 means concat these features and 1 means sum these features.
  assemble: 1

  # function for assigning output features.
  extractor:
    name: "ReIDSeries"  # name of the extractor.
    ReIDSeries:
      extract_features: ["output"]  # name of the output feature map. If it is ["all"], then all available features will be output.

  # function for splitting the output features (e.g. PCB).
  splitter:
    name: "Identity"  # name of the function for splitting features.

  # a list of pooling functions.
  aggregators:
    names: ["GAP"]  # names of aggregators.

index:
  # path of the query set features and gallery set features.
  query_fea_dir: "/data/features/best_features/duke/query"
  gallery_fea_dir: "/data/features/best_features/duke/gallery"

  # name of the features to be loaded. It should be "output feature map" + "_" + "aggregation".
  # If there are multiple elements in the list, they will be concatenated on the channel-wise.
  feature_names: ['output']

  # a list of dimension process functions.
  dim_processors:
    names: ["L2Normalize"]  # names of dimension processors.

  # function for enhancing the quality of features.
  feature_enhancer:
    name: "Identity"  # name of the feature enhancer.

  # function for calculating the distance between query features and gallery features.
  metric:
    name: "KNN"  # name of the metric.

  # function for re-ranking the results.
  re_ranker:
    name: "Identity"  # name of the re-ranker.

evaluate:
  # function for evaluating results.
  evaluator:
    name: "ReIDOverAll"  # name of the evaluator.