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mkdocs.yml
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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
- one-yolov5 v1.2.0 released: tutorials/00_chapter/release_v1_2_0.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 分割和分类模型训练示例: tutorials/03_chapter/model_train.md
- 3.3 从OneFlow Hub 加载YOLOv5: tutorials/03_chapter/loading_model_from_oneflowhub.md
- 3.4 测试时增强 (TTA): tutorials/03_chapter/TTA.md
- 3.5 模型融合 (Model Ensembling): tutorials/03_chapter/model_ensembling.md
- 3.6 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:
- val.py : source_code_interpretation/val_py.md
- train.py : source_code_interpretation/train_py.md
- detect.py : source_code_interpretation/detect_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
- callbacks.py: source_code_interpretation/utils/callbacks_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