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PaddleClas
未验证 提交 1e8d2e9b 编写于 作者: C cuicheng01 提交者： GitHub
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Merge pull request #2295 from TingquanGao/dev/docs 

docs: refactor
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docs/zh_CN/Makefile 已删除 100644 → 0
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# Minimal makefile for Sphinx documentation
#
# You can set these variables from the command line, and also
# from the environment for the first two.
SPHINXOPTS ?=
SPHINXBUILD ?= sphinx-build
#SOURCEDIR = source
BUILDDIR = build
# Put it first so that "make" without argument is like "make help".
help:
@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
.PHONY: help Makefile
# Catch-all target: route all unknown targets to Sphinx using the new
# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
%: Makefile
@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
docs/zh_CN/advanced_tutorials/gallery2fc.md 已删除 100644 → 0
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# 识别模型转分类模型
PaddleClas 提供了 `gallery2fc.py` 工具，帮助大家将识别模型转为分类模型。目前该工具仅支持转换量化后模型，因此建议使用 PaddleClas 提供的 `general_PPLCNet_x2_5_pretrained_v1.0_quant` 预训练模型，该模型为量化后的通用识别模型，backbone 为 PPLCNet_x2_5。
如需使用其他模型，关于量化的具体操作请参考文档 [模型量化](./model_prune_quantization.md)。
## 一、模型转换说明
### 1.1 准备底库数据、预训练模型
#### 1. 底库数据集
首先需要准备好底库数据，下面以 PaddleClas 提供的饮料数据集（drink_dataset_v1.0）为例进行说明，饮料数据集获取方法：
```shell
cd PaddleClas/
wget https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/drink_dataset_v1.0.tar
tar -xf drink_dataset_v1.0.tar
```
饮料数据集的底库图片路径为 `drink_dataset_v1.0/gallery/`，底库图片列表可在 `drink_dataset_v1.0/gallery/drink_label.txt` 中查看，关于底库数据格式说明，请参考文档[数据集格式说明](../data_preparation/recognition_dataset.md#1-数据集格式说明)。
#### 2. 预训练模型
在开始转换模型前，需要准备好预训练模型，下面以量化后的 `general_PPLCNet_x2_5` 模型为例，下载预训练模型：
```shell
cd PaddleClas/pretrained/
wget https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/models/pretrain/general_PPLCNet_x2_5_pretrained_v1.0_quant.pdparams
```
### 1.2 准备配置文件
在进行模型转换时，需要通过配置文件定义所需参数，本例中所用配置文件为 `ppcls/configs/GeneralRecognition/Gallery2FC_PPLCNet_x2_5.yaml`，对于配置文件字段的说明，如下所示：
* Global:
* pretrained_model: 预训练模型路径，无需包含 `.pdparams` 后缀名；
* image_shape: 模型输入数据尺寸，无需包含 batch size 维度；
* save_inference_dir: 转换后模型的保存路径；
* Arch: 模型结构相关定义，可参考 [配置说明](../models_training/config_description.md#3-%E8%AF%86%E5%88%AB%E6%A8%A1%E5%9E%8B)；
* IndexProcess: 底库数据集相关定义
* image_root: 底库数据集路径；
* data_file: 底库数据集列表文件路径；
### 1.3 模型转换
在完成上述准备工作后，即可进行模型转换，命令如下所示：
```python
python ppcls/utils/gallery2fc.py -c ppcls/configs/GeneralRecognition/Gallery2FC_PPLCNet_x2_5.yaml
```
在上述命令执行完成后，转换并导出的模型保存在目录 `./inference/general_PPLCNet_x2_5_quant/` 下。在推理部署时，需要注意的是，模型的输出结果通常有多个，应选取分类结果作为模型输出，需要注意区分。
docs/zh_CN/advanced_tutorials/index.rst 已删除 100644 → 0
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高级教程
================================
.. toctree::
:maxdepth: 2
DataAugmentation.md
knowledge_distillation.md
model_prune_quantization.md
code_overview.md
how_to_contribute.md
docs/zh_CN/algorithm_introduction/index.rst 已删除 100644 → 0
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算法介绍
================================
.. toctree::
:maxdepth: 2
image_classification.md
metric_learning.md
knowledge_distillation.md
model_prune_quantization.md
ImageNet_models.md
DataAugmentation.md
docs/zh_CN/others/course_link.md → docs/zh_CN/community/courses.md
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......@@ -29,6 +29,3 @@
- 产业应用十问十答
- 智能零售下的应用案例
- 识别系统快速落地方案
docs/zh_CN/conf.py 已删除 100644 → 0
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# Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
#
# import os
# import sys
# sys.path.insert(0, os.path.abspath('.'))
import sphinx_rtd_theme
from recommonmark.parser import CommonMarkParser
#import sphinx-markdown-tables
# -- Project information -----------------------------------------------------
project = 'PaddleClas'
copyright = '2021, PaddleClas'
author = 'PaddleClas'
# The full version, including alpha/beta/rc tags
release = '2.3.0'
# -- General configuration ---------------------------------------------------
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
source_parsers = {
'.md': CommonMarkParser,
}
source_suffix = ['.rst', '.md']
extensions = [
'recommonmark',
'sphinx_markdown_tables'
]
# Add any paths that contain templates here, relative to this directory.
templates_path = ['_templates']
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
#
# This is also used if you do content translation via gettext catalogs.
# Usually you set "language" from the command line for these cases.
language = 'zh_CN'
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
# This pattern also affects html_static_path and html_extra_path.
exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
# -- Options for HTML output -------------------------------------------------
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
#
html_theme = "sphinx_rtd_theme"
html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = ['_static']
docs/zh_CN/data_preparation/index.rst 已删除 100644 → 0
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数据准备
================================
.. toctree::
:maxdepth: 2
recognition_dataset.md
classification_dataset.md
docs/zh_CN/inference_deployment/shitu_gallery_manager.md → docs/zh_CN/deployment/PP-ShiTu/gallery_manager.md
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......@@ -192,4 +192,3 @@ index_root/ # 库存储目录
- 问题4: 报错 图像与index库不一致
答：可能用户自己修改了image_list.txt，修改完成后，请及时更新index库，保证其一致。
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FAQ系列
================================
.. toctree::
:maxdepth: 2
faq_2021_s2.md
faq_2021_s1.md
faq_2020_s1.md
faq_selected_30.md
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图像识别流程
================================
.. toctree::
:maxdepth: 2
mainbody_detection.md
feature_extraction.md
vector_search.md
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欢迎使用PaddleClas图像分类库！
================================
.. toctree::
:maxdepth: 1
introduction/index
installation/index
quick_start/index
image_recognition_pipeline/index
data_preparation/index
models_training/index
inference_deployment/index
models/index
algorithm_introduction/index
advanced_tutorials/index
others/index
faq_series/index
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推理部署
================================
.. toctree::
:maxdepth: 2
export_model.md
python_deploy.md
cpp_deploy.md
paddle_serving_deploy.md
paddle_hub_serving_deploy.md
paddle_lite_deploy.md
whl_deploy.md
cpp_deploy_on_windows.md
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安装
================================
.. toctree::
:maxdepth: 2
install_paddle.md
install_paddleclas.md
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## PaddleClas 功能特性
飞桨图像识别套件 PaddleClas 是飞桨为工业界和学术界所准备的一个图像识别任务的工具集，助力使用者训练出更好的视觉模型和应用落地。具体地，它包含以下几个核心特性。
- 实用的图像识别系统：集成了目标检测、特征学习、图像检索等模块，广泛适用于各类图像识别任务。
提供商品识别、车辆识别、 logo 识别和动漫人物识别等 4 个场景应用示例。
- 丰富的预训练模型库：提供了 36 个系列共 175 个 ImageNet 预训练模型，其中 7 个精选系列模型支持结构快速修改。
- 全面易用的特征学习组件：集成 arcmargin, triplet loss 等 12 度量学习方法，通过配置文件即可随意组合切换。
- SSLD 知识蒸馏： 14 个分类预训练模型，精度普遍提升 3% 以上；其中 ResNet50_vd 模型在 ImageNet-1k 数据集上的 Top-1 精度达到了 84.0%，Res2Net200_vd 预训练模型 Top-1 精度高达 85.1% 。
- 数据增广：支持 AutoAugment 、 Cutout 、 Cutmix 等 8 种数据增广算法详细介绍、代码复现和在统一实验环境下的效果评估。
![](../../images/recognition.gif)
更多关于图像识别快速体验、算法详解、模型训练评估与预测部署方法，请参考[首页 README 文档教程](../../../README_ch.md)。
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介绍
================================
.. toctree::
:maxdepth: 2
function_intro.md
more_demo/index
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## 动漫人物图片识别效果图
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069080-a821e0b7-8a10-4946-bf05-ff093cc16064.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069100-7539d292-1bd8-4655-8a6d-d1f2238bd618.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069103-f91359d4-1197-4a6e-b2f7-434c76a6b704.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069108-ad54ae1d-610d-4cfa-9cd6-8ee8d280d61d.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069114-3c771434-84a8-4e58-961e-d35edfbfe5ef.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069119-e8d85be5-da87-4125-ae8b-9fd4cac139d9.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069124-98c30894-4837-4f2f-8399-3d3ebadfd0a1.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069125-a9edf115-33a1-48bf-9e4f-7edbc4269a1e.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069129-98553a25-00e2-4f0f-9b44-dfc4e4f6b6d1.png " width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069131-f7649bb2-255c-4725-a635-799b8b4d815a.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069135-acb69b89-55db-41ac-9846-e2536ef3d955.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069137-1f0abfdb-6608-432e-bd40-c8e1ab86ef8b.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069140-18c6a439-f117-498d-9cdb-ade71cc2c248.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069145-80452f86-afcf-42b5-8423-328cca9e4750.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069154-63a25c1c-b448-44c2-8baf-eb31952c5476.jpeg" width = "400" /> </div>
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<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069167-937aa847-c661-431c-b3dc-5a3c890b31cd.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069170-43d0dce4-6c62-485d-adf4-364c8467c251.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069175-70bc9e50-b833-4a2a-8a3f-c0775dac49c2.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069179-d01f8a0f-4383-4b08-b064-4e6bb006e745.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069184-d423a84c-c9dd-4125-9dc7-397cae21efc9.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069188-fc4deb80-38a2-4c50-9a29-30cee4c8e374.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069193-77a19ee8-b1e2-4c27-9016-3440a1547470.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069196-5f050524-ac08-4831-89f5-9e9e3ce085c1.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069200-4f963171-c790-4f43-8ca3-2e701ad3731c.jpeg" width = "400" /> </div>
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介绍
================================
.. toctree::
:maxdepth: 2
cartoon.md
logo.md
more_demo.md
product.md
vehicle.md
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## 商标图片识别效果图
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096687-5b562e2d-0653-4be6-861d-1936a4440df2.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096698-4b95eb4b-6638-47dc-ae48-7b40744a31ba.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096701-4a4b2bd9-85f2-4d55-be4b-be6ab5e0fb81.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096706-ef4ad024-7284-4cb3-975a-779fd06b96f5.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096710-620b0495-cc83-4501-a104-dfe20afb53d2.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096713-48e629aa-c637-4603-b005-18570fa94d6d.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096715-709957f2-50bb-4edb-a6e4-e7d5601872c7.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096717-a74744cc-4fb8-4e78-b1cb-20409582ca52.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096721-d4af003c-7945-4591-9e47-4e428dc2628c.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096726-460af6ab-8595-4fb4-9960-4c66b18bee1e.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096728-81494000-92b5-40ad-a6a7-606dae3548a3.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096731-2e980977-9ee6-4e29-bdf7-8397820f70e8.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096732-7d425b45-6b04-4984-948d-278da13dd802.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096735-a9c85c14-5965-4529-a235-ce00035bd7ab.jpg " width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096736-3182efc6-ba43-4cde-9397-88a131f4fed8.jpg " width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096737-91e6fa24-1eb5-4aba-9271-5a3722cbe35b.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096740-f440f89b-5f95-493a-b087-00c7cd3481ef.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096747-31b924e3-ffb2-45ab-872e-4ff923ed04f1.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096752-1f98c937-5d83-4c29-b495-01971b5fb258.jpeg" width = "400" /> </div>
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<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096767-e8f701eb-d0e8-4304-b031-e2bff8c199f3.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096778-ec2ad374-b9fc-427e-9e8b-8e5d2afc6394.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096783-9ec5e04d-19e3-463d-ad9d-7a26202bbb9c.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096788-44f04979-18ca-4ba6-b833-7489b344ffff.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096791-6989451e-157c-4101-8b54-7578b05eb7c9.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096796-cc4477cf-016c-4b19-86c3-61824704ecf5.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096798-ba33ee0d-45b8-48ad-a8fa-14cd643a6976.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096805-e29a2ba8-4785-4ca6-9e0d-596fad6ce8dc.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096812-7d8c57a5-fbae-4496-8144-3b40ac74fef0.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096816-50f0ac3d-f2eb-4011-a34e-58e2e215b7b0.jpg " width = "400" /> </div>
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浏览文件 @ 9b12161b
## 识别效果展示
- 商品识别
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277277-7b29f596-35f6-4f00-8d2b-0ef0be57a090.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277291-f7d2b2a1-5790-4f5b-a0e6-f5c52d04a69a.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277300-8ce0d5ce-e0ca-46ea-bb9a-74df0df66ae3.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277308-14a097bd-2bcd-41ce-a9e6-5e9cd0bd8b08.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277311-208ae574-a708-46e2-a41e-c639322913b1.jpg" width = "400" /> </div>
[更多效果图](product.md)
- 动漫人物识别
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069108-ad54ae1d-610d-4cfa-9cd6-8ee8d280d61d.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069100-7539d292-1bd8-4655-8a6d-d1f2238bd618.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140069080-a821e0b7-8a10-4946-bf05-ff093cc16064.jpeg" width = "400" /> </div>
[更多效果图](cartoon.md)
- logo识别
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096687-5b562e2d-0653-4be6-861d-1936a4440df2.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096701-4a4b2bd9-85f2-4d55-be4b-be6ab5e0fb81.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096706-ef4ad024-7284-4cb3-975a-779fd06b96f5.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096713-48e629aa-c637-4603-b005-18570fa94d6d.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096752-1f98c937-5d83-4c29-b495-01971b5fb258.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140096767-e8f701eb-d0e8-4304-b031-e2bff8c199f3.jpeg" width = "400" /> </div>
[更多效果图](logo.md)
- 车辆识别
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140243899-c60f0a51-db9b-438a-9f2d-0d2893c200bb.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140243905-7eeb938d-d88f-4540-a667-06e08dcf1f55.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140243911-735a6ec0-a624-4965-b3cd-2b9f52fa8d65.jpeg" width = "400" /> </div>
[更多效果图](vehicle.md)
docs/zh_CN/introduction/more_demo/product.md 已删除 100644 → 0
浏览文件 @ 9b12161b
## 商品图片识别效果图
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277277-7b29f596-35f6-4f00-8d2b-0ef0be57a090.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277287-7bdad02a-8e3c-4e04-861c-95a5dae1f3c6.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277291-f7d2b2a1-5790-4f5b-a0e6-f5c52d04a69a.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277294-80aaab94-5109-41be-97f8-3ada73118963.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277296-2a8d7846-cd2e-454e-8b72-46233da09451.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277300-8ce0d5ce-e0ca-46ea-bb9a-74df0df66ae3.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277302-25c973eb-f9aa-42ce-b9e9-66cee738c241.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277303-3d3460da-c6aa-4994-b585-17bc9f3df504.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277306-20cbef71-cc58-4ae1-965b-4806e82988a9.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277308-14a097bd-2bcd-41ce-a9e6-5e9cd0bd8b08.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277309-be092d1c-6513-472c-8b7f-685f4353ae5b.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277311-208ae574-a708-46e2-a41e-c639322913b1.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277314-72901737-5ef5-4a23-820b-1db58c5e6ca0.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277318-aef4080c-24f2-4d92-be3c-45b500b75584.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277320-8046d0df-1256-41ce-a8d6-6d2c1292462c.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277321-e3864473-6a8e-485f-81f2-562b902d6cff.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277324-0aacc27f-699a-437b-bac0-4a20c90b47b1.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277328-8d28f754-8645-4c05-a9a6-0312bbe2f890.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277333-59da1513-e7e5-455c-ab73-7a3162216923.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277335-454c0423-5398-4348-aaab-e2652fd08999.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277338-a7d09c28-1b86-4cf5-bd79-99d51c5b5311.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277343-9c456d21-8018-4cd5-9c0b-cc7c087fac69.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277345-2ef780f1-d7c9-4cf2-a370-f220a052eb71.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277347-baa4b870-7fca-4d4c-8528-fad720270024.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277351-e0691080-ede4-49ae-9075-d36a41cebf25.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277354-509f8f85-f171-44e9-8ca1-4c3cae77b5fb.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277357-39d572b8-60ee-44db-9e0e-2c0ea2be2ed3.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277359-6caf33f6-2a38-48e5-b349-f4dd1ef2566b.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277362-260daa87-1db7-4f89-ba9c-1b32876fd3b6.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277366-14cfd2f9-d044-4288-843e-463a1816163e.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277368-b0e96341-e030-4e4d-8010-6f7c3bc94d2f.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277370-1f26e4e5-9988-4427-a035-44bfd9d472d6.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277372-27e60b60-cd5c-4b05-ae38-2e9524c627f3.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277374-bd292bb2-e1f9-4d5f-aa49-d67ac571d01b.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277377-b0b8cdb9-8196-4598-ae47-b615914bf6bf.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277382-fc89d18a-a57b-4331-adbb-bda3584fb122.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277386-d676467c-9846-4051-8192-b3e089d01cdc.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277390-83f66d3f-c415-47e6-b651-6b51fbe59bbf.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277394-9895d654-3163-4dd9-882c-ac5a893e2ad3.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277396-9e5e3aa3-6d9e-40ab-a325-2edea452156d.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277399-b92e2092-eabd-45c8-bf36-b2e238167892.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277404-285f943a-de70-48b8-9545-53e229b7350d.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277406-0b7ec434-f064-4985-80f3-c00735b3e32d.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277408-4f9b8b19-42c2-4ba4-bf6d-b95ababe0313.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277409-6df0faf7-71b7-4c9a-a875-36ae7ee7129d.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277411-9c2b364a-749d-465e-a85d-29a69e9ff3ef.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277413-c54a462c-dd3b-4ad0-985d-ef0ec1f216ec.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277414-6d922055-cd59-4f84-b5b6-651209d6336a.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277417-78e1322e-4039-4232-b217-1be4f207f804.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277419-181822a3-bae6-4c4f-9959-59e991c2df6c.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277422-76f09d84-cb47-4332-aa88-a12458cd8993.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277424-a72203b5-1a99-4464-a39c-245f7a891f25.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277429-521ac9a6-e4c3-4c74-9c5b-8e8dd6cddf34.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277433-4f9fb9c8-7930-4303-b54e-a6eace347923.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277434-f3aa3565-a2c5-4c1c-ab44-930a8b073b5f.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277437-90cf1cd7-6a62-4ac4-ac85-3aa534e50cee.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277439-54e168bc-9518-429e-9e97-cb9ca5e811c9.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277441-a3c277d7-c889-4556-b74a-400cadf8b771.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277442-22a0cd38-acd8-4b5a-8e59-c4bea852fb79.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277444-ea662034-c17f-47ba-9ea3-694d3cb0c880.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277448-a71f4a0a-c3cc-4432-a803-843b7c65307f.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277449-0b3a2e98-3e09-4bd6-be32-c35f44154e8a.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277452-e36ccc63-8e39-4973-a336-4ace855d25e6.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277454-bddd9527-b189-4771-ab9e-52085db5a44d.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277455-7ea277ba-bc75-48db-9567-40e1acb56f02.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277460-0f5ee4dc-5ece-45d5-8ef9-666f1be41b76.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277461-37cab773-6341-4c91-b1f4-780d530eab3b.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277465-8f53ef9d-0465-4a90-afac-b1dd3c970b72.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277467-655ddabe-cbe0-4d1f-a30e-c2965428e8d7.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277470-4587e905-3fc8-4dad-84ee-0844ba4d2474.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277473-a155944f-efe3-492a-babc-2f3fe700a99b.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277475-c95ab821-f5ae-427a-8721-8991f9c7f29f.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277479-55b59855-2ed6-4526-9481-6b92b25fef97.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277484-556f0e4c-007b-4f6a-b21f-c485f630cbcb.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277486-a39eb069-bc13-415e-b936-ba294216dfac.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277487-80952841-6a76-4fb3-8049-fe15ce8f7cfb.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277491-e892a6a8-6f9a-46c7-83e0-261cfb92d276.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277494-520f483e-654d-4399-9684-1fcd9778b76e.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277496-54b1ada5-e6a6-4654-a8a6-739511cec750.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277500-ff7e2afd-9cd7-484a-bd1e-362226f5197f.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277501-94489261-bea5-4492-bf3e-98cc8aaa7a7f.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277504-567a32bc-a573-4154-a9cd-6acbec923768.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277506-e893d4d5-43ce-4df1-9f08-3cdf6a8c7e2c.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277509-5766629f-bb92-4552-b34a-647e29b9a89b.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277511-8821708b-09f0-4aab-86dd-40ae3794697a.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277515-ed6a0dff-bd91-4233-a9af-e2744df7c7e0.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277519-1883d6a1-9348-4514-8924-dde27dd38704.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277524-b9d8515c-4df2-410a-b4a6-da098cb9da61.jpg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140277526-52a9c666-a799-4921-b371-41d97d7d9242.jpg" width = "400" /> </div>
docs/zh_CN/introduction/more_demo/vehicle.md 已删除 100644 → 0
浏览文件 @ 9b12161b
## 车辆图片识别效果图
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140243899-c60f0a51-db9b-438a-9f2d-0d2893c200bb.jpeg" width = "400" /> </div>
<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140243904-fdbe2e01-dc7c-449a-8e9e-baea4f85fee4.jpeg" width = "400" /> </div>
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<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140243911-735a6ec0-a624-4965-b3cd-2b9f52fa8d65.jpeg" width = "400" /> </div>
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<div align="center"> <img src="https://user-images.githubusercontent.com/12560511/140243940-d289fc7d-d343-4aa5-a807-9ce09a241ccd.jpeg" width = "400" /> </div>
docs/zh_CN/make.bat 已删除 100644 → 0
浏览文件 @ 9b12161b
@ECHO OFF
pushd %~dp0
REM Command file for Sphinx documentation
if "%SPHINXBUILD%" == "" (
set SPHINXBUILD=sphinx-build
)
set SOURCEDIR=source
set BUILDDIR=build
if "%1" == "" goto help
%SPHINXBUILD% >NUL 2>NUL
if errorlevel 9009 (
echo.
echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
echo.installed, then set the SPHINXBUILD environment variable to point
echo.to the full path of the 'sphinx-build' executable. Alternatively you
echo.may add the Sphinx directory to PATH.
echo.
echo.If you don't have Sphinx installed, grab it from
echo.https://www.sphinx-doc.org/
exit /b 1
)
%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
goto end
:help
%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
:end
popd
docs/zh_CN/models/HarDNet.md → docs/zh_CN/models/ImageNet1k/HarDNet.md
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......@@ -32,4 +32,3 @@ HarDNet（Harmonic DenseNet）是 2019 年由国立清华大学提出的一种
| HarDNet85 | 224 | 256 | 6.24 | 14.85 | 20.57 |
| HarDNet39_ds | 224 | 256 | 1.40 | 2.30 | 3.33 |
| HarDNet68_ds | 224 | 256 | 2.26 | 3.34 | 5.06 |
docs/zh_CN/models/PP-HGNet.md → docs/zh_CN/models/ImageNet1k/PP-HGNet.md
浏览文件 @ 1e8d2e9b
......@@ -404,4 +404,3 @@ PaddleClas 提供了基于 Paddle Lite 来完成模型端侧部署的示例，
Paddle2ONNX 支持将 PaddlePaddle 模型格式转化到 ONNX 模型格式。通过 ONNX 可以完成将 Paddle 模型到多种推理引擎的部署，包括TensorRT/OpenVINO/MNN/TNN/NCNN，以及其它对 ONNX 开源格式进行支持的推理引擎或硬件。更多关于 Paddle2ONNX 的介绍，可以参考[Paddle2ONNX 代码仓库](https://github.com/PaddlePaddle/Paddle2ONNX)。
PaddleClas 提供了基于 Paddle2ONNX 来完成 inference 模型转换 ONNX 模型并作推理预测的示例，您可以参考[Paddle2ONNX 模型转换与预测](../../../deploy/paddle2onnx/readme.md)来完成相应的部署工作。
docs/zh_CN/models/ImageNet1k/README.md 0 → 120000
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model_list.md
\ No newline at end of file
docs/zh_CN/models/PULC/README.md 0 → 120000
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model_list.md
\ No newline at end of file
docs/zh_CN/models/index.rst 已删除 100644 → 0
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模型库
================================
.. toctree::
:maxdepth: 2
DPN_DenseNet.md
models_intro.md
RepVGG.md
EfficientNet_and_ResNeXt101_wsl.md
ViT_and_DeiT.md
SwinTransformer.md
Others.md
SEResNext_and_Res2Net.md
ESNet.md
HRNet.md
ReXNet.md
Inception.md
TNT.md
RedNet.md
DLA.md
ResNeSt_RegNet.md
PP-LCNet.md
HarDNet.md
ResNet_and_vd.md
LeViT.md
Mobile.md
MixNet.md
Twins.md
docs/zh_CN/models_training/index.rst 已删除 100644 → 0
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模型训练
================================
.. toctree::
:maxdepth: 2
config_description.md
classification.md
recognition.md
train_strategy.md
docs/zh_CN/others/index.rst 已删除 100644 → 0
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其他
================================
.. toctree::
:maxdepth: 2
transfer_learning.md
train_with_DALI.md
VisualDL.md
train_on_xpu.md
feature_visiualization.md
paddle_mobile_inference.md
course_link.md
competition_support.md
update_history.md
versions.md
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# 版本更新信息
----------
## 目录
* [1. v2.3](#1)
* [2. v2.2](#2)
<a name='1'></a>
## 1. v2.3
- 模型更新
- 添加轻量化模型预训练权重，包括检测模型、特征模型
- 发布 PP-LCNet 系列模型，此系列模型是专门在 CPU 上设计运行的自研模型
- SwinTransformer、Twins、Deit 支持从 scrach 直接训练，达到论文精度
- 框架基础能力
- 添加 DeepHash 模块，支持特征模型直接输出二值特征
- 添加 PKSampler，特征模型不能多机多卡的训练的问题
- 支持 PaddleSlim：支持分类模型、特征模型的量化、裁剪训练及离线量化功能
- Legendary models 支持模型中间结果输出
- 支持多标签分类训练
- 预测部署
- 使用 Faiss 替换原有特征检索库，提升平台适配性
- 支持 PaddleServing：支持分类模型、图像识别流程的部署
- 推荐库版本
- python 版本：3.7
- PaddlePaddle 版本：2.1.3
- PaddleSlim 版本：2.2.0
- PaddleServing 版本：0.6.1
<a name='2'></a>
## 2. v2.2
- 模型更新
- 添加 LeViT、Twins、TNT、DLA、HardNet、RedNet、SwinTransfomer 模型
- 框架基础能力
- 将分类模型分为两类
- legendary models：引入 TheseusLayer 基类，及增加了修改网络功能接口，同时支持网络截断输出功能
- model zoo：其他普通分类模型
- 添加 Metric Learning 算法支持
- 添加多种相关 Loss 算法，及基础网络模块 gears（支持与 backbone、loss 组合）方便使用
- 同时支持普通分类及 metric learning 相关任务训练
- 支持静态图训练
- 分类训练支持 dali 加速
- 支持 fp16 训练
- 应用更新
- 添加商品识别、车辆识别（车辆细粒度分类、车辆 ReID）、logo 识别、动漫人物识别应用具体案例及相关模型
- 添加图像识别完整 pipeline，包含检测模块、特征提取模块、向量检索模块
- 预测部署
- 添加百度自研向量检索模块 Mobius，支持图像识别系统预测部署
- 图像识别，建立特征库支持 batch_size>1
- 文档更新
- 添加图像识别相关文档
- 修复之前文档 bug
- 推荐库版本
- python 版本：3.7
- PaddlePaddle：2.1.2
docs/zh_CN/quick_start/index.rst 已删除 100644 → 0
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快速开始
================================
.. toctree::
:maxdepth: 2
quick_start_classification_new_user.md
quick_start_classification_professional.md
quick_start_recognition.md
quick_start_multilabel_classification.md
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