yolov5s6.0 yaml文件解读

yolov5s6.0的yaml文件是用来配置模型训练和推理的参数的。下面是一个简单的yaml文件示例：

# train and val datasets (image directory or *.txt file with image paths)
train: ../data/train/images/
val: ../data/val/images/

# number of classes
nc: 80

# class names
names: ['person', 'bicycle', 'car', ...]

# YOLOv5 backbone
backbone:
  # model name
  name: yolov5s

  # pretrained weights path
  pretrained: ''

  # number of channels in the input image
  in_channels: 3

# YOLOv5 head
head:
  # anchor sizes
  anchors: [[10,13, 16,30, 33,23], [30,61, 62,45, 59,119], [116,90, 156,198, 373,326]]

  # number of output channels
  num_classes: 80

  # number of anchor boxes per feature map cell
  num_anchors: 3

# training parameters
train_params:
  # batch size
  batch_size: 16

  # number of epochs
  epochs: 300

  # learning rate
  lr: 0.01

  # optimizer
  optimizer:
    name: SGD
    momentum: 0.9

# inference parameters
infer_params:
  # confidence threshold for object detection
  conf_thresh: 0.25

  # NMS threshold for object detection
  nms_thresh: 0.45

其中，train和val字段指定了训练和验证数据集的路径；nc字段指定了类别数；names字段指定了类别名称；backbone字段指定了模型的骨干网络；head字段指定了模型的检测头；train_params字段指定了训练参数，如批大小、学习率等；infer_params字段指定了推理参数，如置信度阈值、NMS阈值等。