1. python读取yaml文件

1.1. YAML 简介

YAML，Yet Another Markup Language的简写，通常用来编写项目配置，也可用于数据存储，相比conf等配置文件要更简洁。

1.2. YAML 语法

• 支持的数据类型：
  字典、列表、字符串、布尔值、整数、浮点数、Null、时间等
• 基本语法规则：
  1、大小写敏感
  2、使用缩进表示层级关系
  3、相同层级的元素左侧对齐
  4、键值对用冒号 “:” 结构表示，冒号与值之间需用空格分隔
  5、数组前加有 “-” 符号，符号与值之间需用空格分隔
  6、None值可用null 和 ~ 表示
  7、多组数据之间使用3横杠—分割
  8、# 表示注释，但不能在一段代码的行末尾加 #注释，否则会报错

1.3. 安装第三方yaml文件处理库PyYAML

python没有自带的处理yaml文件的库，需要下载第三方库PyYAML 或 ruamel.yaml ，这里我们安装PyYAML。

pip install pyyaml
# 下载速度慢的话加上清华镜像源
pip install pyyaml -i https://pypi.tuna.tsinghua.edu.cn/simple

1.4. yaml文件读取

待读取的文件为yolov8.yaml

# Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv8 object detection model with P3-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect# Parameters
nc: 80  # number of classes
scales: # model compound scaling constants, i.e. 'model=yolov8n.yaml' will call yolov8.yaml with scale 'n'# [depth, width, max_channels]n: [0.33, 0.25, 1024]  # YOLOv8n summary: 225 layers,  3157200 parameters,  3157184 gradients,   8.9 GFLOPss: [0.33, 0.50, 1024]  # YOLOv8s summary: 225 layers, 11166560 parameters, 11166544 gradients,  28.8 GFLOPsm: [0.67, 0.75, 768]   # YOLOv8m summary: 295 layers, 25902640 parameters, 25902624 gradients,  79.3 GFLOPsl: [1.00, 1.00, 512]   # YOLOv8l summary: 365 layers, 43691520 parameters, 43691504 gradients, 165.7 GFLOPsx: [1.00, 1.25, 512]   # YOLOv8x summary: 365 layers, 68229648 parameters, 68229632 gradients, 258.5 GFLOPs# YOLOv8.0n backbone
backbone:# [from, repeats, module, args]- [-1, 1, Conv, [64, 3, 2]]  # 0-P1/2- [-1, 1, Conv, [128, 3, 2]]  # 1-P2/4- [-1, 3, C2f, [128, True]]- [-1, 1, Conv, [256, 3, 2]]  # 3-P3/8- [-1, 6, C2f, [256, True]]- [-1, 1, Conv, [512, 3, 2]]  # 5-P4/16- [-1, 6, C2f, [512, True]]- [-1, 1, Conv, [1024, 3, 2]]  # 7-P5/32- [-1, 3, C2f, [1024, True]]- [-1, 1, SPPF, [1024, 5]]  # 9# YOLOv8.0n head
head:- [-1, 1, nn.Upsample, [None, 2, 'nearest']]- [[-1, 6], 1, Concat, [1]]  # cat backbone P4- [-1, 3, C2f, [512]]  # 12- [-1, 1, nn.Upsample, [None, 2, 'nearest']]- [[-1, 4], 1, Concat, [1]]  # cat backbone P3- [-1, 3, C2f, [256]]  # 15 (P3/8-small)- [-1, 1, Conv, [256, 3, 2]]- [[-1, 12], 1, Concat, [1]]  # cat head P4- [-1, 3, C2f, [512]]  # 18 (P4/16-medium)- [-1, 1, Conv, [512, 3, 2]]- [[-1, 9], 1, Concat, [1]]  # cat head P5- [-1, 3, C2f, [1024]]  # 21 (P5/32-large)- [[15, 18, 21], 1, Detect, [nc]]  # Detect(P3, P4, P5)

读取测试代码：

import yamlwith open('./yolov8.yaml', 'r', encoding='utf-8') as f:result = yaml.load(f.read(), Loader=yaml.FullLoader)
print(result)
print(type(result))
print(result['nc'], type(result['nc']))
print(result['scales'], type(result['scales']))print(result['scales']['n'], type(result['scales']['n']))print(result['backbone'], type(result['backbone']))
print(len(result['backbone']))print(result['backbone'][0])
print(len(result['backbone'][0]))
print(result['backbone'][0][2], type(result['backbone'][0][2]))
print(result['backbone'][0][3], type(result['backbone'][0][3]))

输出：

{'nc': 4, 'scales': {'n': [0.33, 0.25, 1024], 's': [0.33, 0.5, 1024], 'm': [0.67, 0.75, 768], 'l': [1.0, 1.0, 512], 'x': [1.0, 1.25, 512]}, 'backbone': [[-1, 1, 'Conv', [64, 3, 2]], [-1, 1, 'Conv', [128, 3, 2]], [-1, 3, 'C2f', [128, True]], [-1, 1, 'Conv', [256, 3, 2]], [-1, 6, 'C2f', [256, True]], [-1, 1, 'Conv', [512, 3, 2]], [-1, 6, 'C2f', [512, True]], [-1, 1, 'Conv', [1024, 3, 2]], [-1, 3, 'C2f', [1024, True]], [-1, 1, 'SPPF', [1024, 5]]], 'head': [[-1, 1, 'nn.Upsample', ['None', 2, 'nearest']], [[-1, 6], 1, 'Concat', [1]], [-1, 3, 'C2f', [512]], [-1, 1, 'nn.Upsample', ['None', 2, 'nearest']], [[-1, 4], 1, 'Concat', [1]], [-1, 3, 'C2f', [256]], [-1, 1, 'Conv', [256, 3, 2]], [[-1, 12], 1, 'Concat', [1]], [-1, 3, 'C2f', [512]], [-1, 1, 'Conv', [512, 3, 2]], [[-1, 9], 1, 'Concat', [1]], [-1, 3, 'C2f', [1024]], [[15, 18, 21], 1, 'Detect', ['nc']]]}
<class 'dict'>
4 <class 'int'>
{'n': [0.33, 0.25, 1024], 's': [0.33, 0.5, 1024], 'm': [0.67, 0.75, 768], 'l': [1.0, 1.0, 512], 'x': [1.0, 1.25, 512]} <class 'dict'>
[0.33, 0.25, 1024] <class 'list'>
[[-1, 1, 'Conv', [64, 3, 2]], [-1, 1, 'Conv', [128, 3, 2]], [-1, 3, 'C2f', [128, True]], [-1, 1, 'Conv', [256, 3, 2]], [-1, 6, 'C2f', [256, True]], [-1, 1, 'Conv', [512, 3, 2]], [-1, 6, 'C2f', [512, True]], [-1, 1, 'Conv', [1024, 3, 2]], [-1, 3, 'C2f', [1024, True]], [-1, 1, 'SPPF', [1024, 5]]] <class 'list'>
10
[-1, 1, 'Conv', [64, 3, 2]]
4
Conv <class 'str'>
[64, 3, 2] <class 'list'>

参考：Python基础笔记1-Python读写yaml文件（使用PyYAML库）

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