配置更改
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@@ -4,21 +4,21 @@ model_name: "yolo_v11_n" # yolo_v11_n, yolo_v11_t, yolo_v11_s, yolo_v11
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i_seed: 202509 # initial random seed
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num_client: 64 # total number of clients
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num_round: 5 # total number of communication rounds
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num_round: 50 # total number of communication rounds
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num_local_class: 80 # number of classes per client
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res_root: "results" # root directory for results
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dataset_path: "/home/image1325/ssd1/dataset/COCO128/"
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dataset_path: "/mnt/DATA/coco" # root directory for dataset
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# train_txt: "train.txt" # path to training set txt file
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# val_txt: "val.txt" # path to validation set txt file
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# test_txt: "test.txt" # path to test set txt file
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local_batch_size: 32 # local training batch size
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val_batch_size: 4 # validation batch size
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val_batch_size: 128 # validation batch size
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num_workers: 4 # number of data loader workers
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min_data: 128 # minimum number of images per client
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max_data: 128 # maximum number of images per client
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num_workers: 8 # number of data loader workers
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min_data: 1700 # minimum number of images per client
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max_data: 1800 # maximum number of images per client
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partition_mode: "overlap" # "overlap" or "disjoint"
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connection_ratio: 1 # connection ratio, e.g., 1.0 means all clients
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@@ -5,9 +5,9 @@ import os
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def args_parser():
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parser = argparse.ArgumentParser()
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parser.add_argument("--epochs", type=int, default=10, help="number of rounds of local training")
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parser.add_argument("--epochs", type=int, default=16, help="number of rounds of local training")
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parser.add_argument("--input_size", type=int, default=640, help="image input size")
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parser.add_argument("--config", type=str, default="./config/uav_cfg.yaml", help="Path to YAML config")
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parser.add_argument("--config", type=str, default="./config/coco_cfg.yaml", help="Path to YAML config")
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args = parser.parse_args()
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