添加coco128配置文件

config/coco128_cfg.yaml

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+# global system:
+fed_algo: "FedAvg"                # federated learning algorithm
+model_name: "yolo_v11_n"          # yolo_v11_n, yolo_v11_t, yolo_v11_s, yolo_v11_m, yolo_v11_l, yolo_v11_x
+i_seed: 202509                    # initial random seed
+
+num_client: 5                     # total number of clients
+num_round: 5                      # total number of communication rounds
+num_local_class: 80               # number of classes per client
+
+res_root: "results"               # root directory for results
+dataset_path: "/mnt/DATA/COCO128/"
+# train_txt: "train.txt"            # path to training set txt file
+# val_txt: "val.txt"                # path to validation set txt file
+# test_txt: "test.txt"              # path to test set txt file                 
+
+local_batch_size: 32              # local training batch size
+val_batch_size: 4                 # validation batch size
+
+num_workers: 4                    # number of data loader workers
+min_data: 128                     # minimum number of images per client
+max_data: 128                     # maximum number of images per client
+partition_mode: "overlap"         # "overlap" or "disjoint"
+connection_ratio: 1               # connection ratio, e.g., 1.0 means all clients
+
+# local training:
+min_lr: 0.000100000000            # initial learning rate
+max_lr: 0.010000000000            # maximum learning rate
+momentum: 0.9370000000            # SGD momentum/Adam beta1
+weight_decay: 0.000500            # optimizer weight decay
+
+warmup_epochs: 3.00000            # warmup epochs
+box: 7.500000000000000            # box loss gain
+cls: 0.500000000000000            # cls loss gain
+dfl: 1.500000000000000            # dfl loss gain
+hsv_h: 0.0150000000000            # image HSV-Hue augmentation (fraction)
+hsv_s: 0.7000000000000            # image HSV-Saturation augmentation (fraction)
+hsv_v: 0.4000000000000            # image HSV-Value augmentation (fraction)
+degrees: 0.00000000000            # image rotation (+/- deg)
+translate: 0.100000000            # image translation (+/- fraction)
+scale: 0.5000000000000            # image scale (+/- gain)
+shear: 0.0000000000000            # image shear (+/- deg)
+flip_ud: 0.00000000000            # image flip up-down (probability)
+flip_lr: 0.50000000000            # image flip left-right (probability)
+mosaic: 1.000000000000            # image mosaic (probability)
+mix_up: 0.000000000000            # image mix-up (probability)
+names:
+  0: person
+  1: bicycle
+  2: car
+  3: motorcycle
+  4: airplane
+  5: bus
+  6: train
+  7: truck
+  8: boat
+  9: traffic light
+  10: fire hydrant
+  11: stop sign
+  12: parking meter
+  13: bench
+  14: bird
+  15: cat
+  16: dog
+  17: horse
+  18: sheep
+  19: cow
+  20: elephant
+  21: bear
+  22: zebra
+  23: giraffe
+  24: backpack
+  25: umbrella
+  26: handbag
+  27: tie
+  28: suitcase
+  29: frisbee
+  30: skis
+  31: snowboard
+  32: sports ball
+  33: kite
+  34: baseball bat
+  35: baseball glove
+  36: skateboard
+  37: surfboard
+  38: tennis racket
+  39: bottle
+  40: wine glass
+  41: cup
+  42: fork
+  43: knife
+  44: spoon
+  45: bowl
+  46: banana
+  47: apple
+  48: sandwich
+  49: orange
+  50: broccoli
+  51: carrot
+  52: hot dog
+  53: pizza
+  54: donut
+  55: cake
+  56: chair
+  57: couch
+  58: potted plant
+  59: bed
+  60: dining table
+  61: toilet
+  62: tv
+  63: laptop
+  64: mouse
+  65: remote
+  66: keyboard
+  67: cell phone
+  68: microwave
+  69: oven
+  70: toaster
+  71: sink
+  72: refrigerator
+  73: book
+  74: clock
+  75: vase
+  76: scissors
+  77: teddy bear
+  78: hair drier
+  79: toothbrush