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SikongJueluo
9eb52f8cef
- Evaluate multiple datasets in a single run (CIFAR10 + CIFAR100) - Report Recall@K for a list of K values from one underlying search - Save results to disk: summary.md, metrics.csv, per-dataset predictions.csv, confusion_matrix.csv - Richer evaluation output: query_labels, topk_ids, topk_labels for downstream analysis - Add --dataset and --top-k CLI overrides for benchmark command - Update config schema: dataset→datasets, top_k→top_k_list
40 lines
1.1 KiB
YAML
40 lines
1.1 KiB
YAML
model:
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dino_model: "facebook/dinov2-large"
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compression_dim: 512
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device: "cuda:3" # auto-detect GPU
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sam_model: "facebook/sam2.1-hiera-large" # SAM model name
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sam_min_mask_area: 100 # Minimum mask area threshold
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sam_max_masks: 10 # Maximum number of masks to keep
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sam_points_per_batch: 64
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compressor_path: null # Path to trained HashCompressor weights (optional)
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output:
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directory: "./outputs"
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dataset:
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dataset_root: "datasets/InsDet-FULL"
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output_dir: "datasets/InsDet-FULL/Synthesized"
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num_objects_range: [3, 8]
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num_scenes: 1000
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object_scale_range: [0.1, 0.4]
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rotation_range: [-30, 30]
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overlap_threshold: 0.3
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seed: 42
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benchmark:
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datasets:
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- source_type: "huggingface"
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path: "uoft-cs/cifar100"
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img_column: "img"
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label_column: "fine_label"
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- source_type: "huggingface"
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path: "uoft-cs/cifar10"
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img_column: "img"
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label_column: "label"
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task:
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name: "recall_at_k"
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type: "retrieval"
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top_k_list: [1, 5, 10]
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batch_size: 64
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model_table_prefix: "benchmark"
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