更新配置文件,移除 YOLO 版本实现计划,调整 UAV 和 COCO 配置中的数据量和批次大小
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		@@ -3,22 +3,22 @@ fed_algo: "FedAvg"                # federated learning algorithm
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model_name: "yolo_v11_n"          # yolo_v11_n, yolo_v11_t, yolo_v11_s, yolo_v11_m, yolo_v11_l, yolo_v11_x
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i_seed: 202509                    # initial random seed
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num_client: 100                   # total number of clients
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num_round: 500                    # total number of communication rounds
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num_client: 36                    # total number of clients
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num_round: 50                     # total number of communication rounds
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num_local_class: 1                # 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/uav/"
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dataset_path: "/mnt/DATA/uav/"
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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: 16                # validation batch size
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local_batch_size: 36               # local training 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: 640                     # minimum number of images per client
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max_data: 720                     # maximum number of images per client
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num_workers: 8                    # number of data loader workers
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min_data: 385                     # minimum number of images per client
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max_data: 400                     # 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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