48 lines
		
	
	
		
			2.4 KiB
		
	
	
	
		
			YAML
		
	
	
	
	
	
		
		
			
		
	
	
			48 lines
		
	
	
		
			2.4 KiB
		
	
	
	
		
			YAML
		
	
	
	
	
	
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								# global system:
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								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_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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								# 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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								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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								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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								# local training:
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								min_lr: 0.000100000000            # initial learning rate
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								max_lr: 0.010000000000            # maximum learning rate
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								momentum: 0.9370000000            # SGD momentum/Adam beta1
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								weight_decay: 0.000500            # optimizer weight decay
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								warmup_epochs: 3.00000            # warmup epochs
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								box: 7.500000000000000            # box loss gain
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								cls: 0.500000000000000            # cls loss gain
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								dfl: 1.500000000000000            # dfl loss gain
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								hsv_h: 0.0150000000000            # image HSV-Hue augmentation (fraction)
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								hsv_s: 0.7000000000000            # image HSV-Saturation augmentation (fraction)
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								hsv_v: 0.4000000000000            # image HSV-Value augmentation (fraction)
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								degrees: 0.00000000000            # image rotation (+/- deg)
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								translate: 0.100000000            # image translation (+/- fraction)
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								scale: 0.5000000000000            # image scale (+/- gain)
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								shear: 0.0000000000000            # image shear (+/- deg)
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								flip_ud: 0.00000000000            # image flip up-down (probability)
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								flip_lr: 0.50000000000            # image flip left-right (probability)
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								mosaic: 1.000000000000            # image mosaic (probability)
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								mix_up: 0.000000000000            # image mix-up (probability)
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								names:
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								  0: uav
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