mkdocs.yml

site_name: oneflow-yolo-doc
use_directory_urls: false

repo_name: OneYOLO-Doc
repo_url: https://github.com/Oneflow-Inc/oneflow-yolo-doc/
edit_uri: "blob/master/docs/"

# Configuration
theme:
  name: material
  custom_dir: 'overrides/'

  # 404 page
  static_templates:
    - 404.html

  # Don't include MkDocs' JavaScript
  include_search_page: false
  search_index_only: true

  # Default values, taken from mkdocs_theme.yml
  language: zh
  features:
    - navigation.tabs
    - navigation.top
    - instant
  palette:
    scheme: default
    primary: indigo
    accent: indigo
  font:
    text: Roboto
    code: Roboto Mono
  icon:
    logo: logo
  favicon: assets/favicon.png

markdown_extensions:
  - pymdownx.arithmatex:
      generic: true
  - pymdownx.highlight:
      auto_title: false
      anchor_linenums: true
      linenums_style: pymdownx-inline
  - pymdownx.inlinehilite
  - pymdownx.snippets
  - pymdownx.superfences
  - attr_list
  - md_in_html
  - tables
  
extra_javascript:
  - javascripts/mathjax.js
  - https://polyfill.io/v3/polyfill.min.js?features=es6
  - https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js

extra:
  disqus: true

nav:
    - 首页🏠: index.md

    - YOLOv5教程📚:
        - 引言:
            - one-yolov5 特点解析: tutorials/00_chapter/overview.md
            - 消费级显卡的春天，GTX 3090 YOLOv5s单卡完整训练COCO数据集缩短11.35个小时: tutorials/00_chapter/optim_speed_version1.md
        - 第一章 网络结构: 
            - 1.1. YOLOv5 网络结构解析: tutorials/01_chapter/yolov5_network_structure_analysis.md
        - 第二章 训练模型的数据集:
            - 2.1. 如何准备YOLOv5模型训练数据: tutorials/02_chapter/how_to_prepare_yolov5_training_data.md
        - 第三章 模型训练: 
            - 3.1 快速开始: tutorials/03_chapter/quick_start.md
            - 3.2 从OneFlow Hub 加载YOLOv5: tutorials/03_chapter/loading_model_from_oneflowhub.md
            - 3.3 测试时增强 (TTA): tutorials/03_chapter/TTA.md
            - 3.4 模型融合 (Model Ensembling): tutorials/03_chapter/model_ensembling.md
            - 3.5 Weights & Biases : tutorials/03_chapter/intro_to_wandb.md
        - 第四章 数据组织与处理解读: 
            - 4.1 mosaic 解读:  tutorials/04_chapter/mosaic.md
        - 第五章 YOLOv5中IoU损失: 
            - 5.1 矩形推理: tutorials/05_chapter/rectangular_reasoning.md
            - 5.2 IoU深入解析: tutorials/05_chapter/iou_in-depth_analysis.md
            - 5.3 模型精确度评估: tutorials/05_chapter/map_analysis.md
            - 5.4 计算mAP用到的numpy函数: tutorials/05_chapter/Introduction_to_functions_used_in_metrics.md
        - 第六章 模型导出和部署介绍:
            - 6.1 模型导出: tutorials/06_chapter/export_onnx_tflite_tensorrt.md



    - 源码解读:
        - train.py : source_code_interpretation/train_py.md 
        - utils:
            - loss.py: source_code_interpretation/utils/loss_py.md
            - augmentations.py: source_code_interpretation/utils/augmentations_py.md
            - dataloaders.py:  source_code_interpretation/utils/dataloaders_py.md
            - downloads.py: source_code_interpretation/utils/downloads_py.md
            - geneal.py: source_code_interpretation/utils/general_py.md
            - autoanchor.py: source_code_interpretation/utils/autoanchor_py.md



    - 论文解读:
        - history: thesis_interpretation/00_yolo_history.md
        - YOLOv1 : thesis_interpretation/01_yolo.md
        - YOLOv2 : thesis_interpretation/02_yolo.md
        - YOLOv3 : thesis_interpretation/03_yolo.md
        - YOLOv4 : thesis_interpretation/04_yolo.md
        - YOLOv6 : thesis_interpretation/06_yolo.md