mirror of https://github.com/PyRetri/PyRetri.git
78 lines
2.5 KiB
YAML
78 lines
2.5 KiB
YAML
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# retrieval settings
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datasets:
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# number of images in a batch.
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batch_size: 16
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# function for stacking images in a batch.
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collate_fn:
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name: "CollateFn"
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# function for loading images.
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folder:
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name: "Folder"
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# a list of data augmentation functions.
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transformers:
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names: ["DirectResize", "TwoFlip", "ToTensor", "Normalize"] # names of transformers.
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DirectResize:
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size: (256, 128) # target size of the output img.
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interpolation: 3 # nearest interpolation
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Normalize:
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mean: [0.485, 0.456, 0.406]
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std: [0.229, 0.224, 0.225]
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model:
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name: "ft_net" # name of the model.
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ft_net:
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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.
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extract:
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# way to assemble features if transformers produce multiple images (e.g. TwoFlip, TenCrop). 0 means concat these features and 1 means sum these features.
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assemble: 1
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# function for assigning output features.
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extractor:
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name: "ReIDSeries" # name of the extractor.
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ReIDSeries:
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extract_features: ["output"] # name of the output feature map. If it is ["all"], then all available features will be output.
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# function for splitting the output features (e.g. PCB).
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splitter:
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name: "Identity" # name of the function for splitting features.
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# a list of pooling functions.
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aggregators:
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names: ["GAP"] # names of aggregators.
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index:
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# path of the query set features and gallery set features.
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query_fea_dir: "/data/features/best_features/duke/query"
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gallery_fea_dir: "/data/features/best_features/duke/gallery"
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# name of the features to be loaded. It should be "output feature map" + "_" + "aggregation".
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# If there are multiple elements in the list, they will be concatenated on the channel-wise.
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feature_names: ['output']
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# a list of dimension process functions.
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dim_processors:
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names: ["L2Normalize"] # names of dimension processors.
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# function for enhancing the quality of features.
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feature_enhancer:
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name: "Identity" # name of the feature enhancer.
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# function for calculating the distance between query features and gallery features.
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metric:
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name: "KNN" # name of the metric.
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# function for re-ranking the results.
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re_ranker:
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name: "Identity" # name of the re-ranker.
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evaluate:
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# function for evaluating results.
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evaluator:
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name: "ReIDOverAll" # name of the evaluator.
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