Merge pull request #1686 from Sibo2rr/dev/en

readthedoc in english

Author: cuicheng01

docs/en/advanced_tutorials/index.rst

@@ -0,0 +1,12 @@
+advanced_tutorials
+================================
+
+.. toctree::
+   :maxdepth: 2
+
+   DataAugmentation_en.md
+   distillation/index
+   multilabel/index
+   model_prune_quantization_en.md
+   code_overview_en.md
+   how_to_contribute_en.md

docs/en/advanced_tutorials/multilabel/index.rst

@@ -4,4 +4,4 @@ Multilabel Classification
 .. toctree::
    :maxdepth: 3
 
-   multilabel.md
+   multilabel_en.md

docs/en/algorithm_introduction/DataAugmentation_en.md

@@ -23,7 +23,7 @@
 
 Data augmentation is a commonly used regularization method in image classification task, which is often used in scenarios with insufficient data or large model. In this chapter, we mainly introduce 8 image augmentation methods besides standard augmentation methods. Users can apply these methods in their own tasks for better model performance. Under the same conditions, these augmentation methods' performance on ImageNet1k dataset is shown as follows.
 
-![](../../../images/image_aug/main_image_aug.png)
+![](../../images/image_aug/main_image_aug.png)
 
 
 <a name="2"></a>
@@ -50,7 +50,7 @@ Compared with the above standard image augmentation methods, the researchers hav
 
 Visualization results of some images after augmentation are shown as follows.
 
-![](../../../images/image_aug/image_aug_samples_s_en.jpg)
+![](../../images/image_aug/image_aug_samples_s_en.jpg)
 
 
 The following table shows more detailed information of the transformations.
@@ -72,7 +72,7 @@ The following table shows more detailed information of the transformations.
 
 PaddleClas integrates all the above data augmentation strategies. More details including principles and usage of the strategies are introduced in the following chapters. For better visualization, we use the following figure to show the changes after the transformations. And `RandCrop` is replaced with` Resize` for simplification.
 
-![](../../../images/image_aug/test_baseline.jpeg)
+![](../../images/image_aug/test_baseline.jpeg)
 
 <a name="2.1"></a>
 ### 2.1 Image Transformation
@@ -91,7 +91,7 @@ Unlike conventional artificially designed image augmentation methods, AutoAugmen
 
 The images after `AutoAugment` are as follows.
 
-![][test_autoaugment]
+![](../../images/image_aug/test_autoaugment.jpeg)
 
 <a name="2.1.2"></a>
 #### 2.1.2 RandAugment
@@ -107,7 +107,7 @@ In `RandAugment`, the author proposes a random augmentation method. Instead of u
 
 The images after `RandAugment` are as follows.
 
-![][test_randaugment]
+![](../../images/image_aug/test_randaugment.jpeg)
 
 <a name="2.1.3"></a>
 #### 2.1.3 TimmAutoAugment
@@ -137,7 +137,7 @@ Cutout is a kind of dropout, but occludes input image rather than feature map. I
 
 The images after `Cutout` are as follows.
 
-![][test_cutout]
+![](../../images/image_aug/test_cutout.jpeg)
 
 <a name="2.2.2"></a>
 #### 2.2.2 RandomErasing
@@ -150,7 +150,7 @@ RandomErasing is similar to the Cutout. It is also to solve the problem of poor
 
 The images after `RandomErasing` are as follows.
 
-![][test_randomerassing]
+![](../../images/image_aug/test_randomerassing.jpeg)
 
 <a name="2.2.3"></a>
 #### 2.2.3 HideAndSeek
@@ -162,11 +162,11 @@ Github repo: [https://github.com/kkanshul/Hide-and-Seek](https://github.com/kkan
 
 Images are divided into some patches for `HideAndSeek` and masks are generated with certain probability for each patch. The meaning of the masks in different areas is shown in the figure below.
 
-![][hide_and_seek_mask_expanation]
+![](../../images/image_aug/hide-and-seek-visual.png)
 
 The images after `HideAndSeek` are as follows.
 
-![][test_hideandseek]
+![](../../images/image_aug/gridmask-0.png)
 
 <a name="2.2.4"></a>
 #### 2.2.4 GridMask
@@ -180,7 +180,7 @@ The author points out that the previous method based on image cropping has two p
 1. Excessive deletion of the area may cause most or all of the target subject to be deleted, or cause the context information loss, resulting in the images after enhancement becoming noisy data.
 2. Reserving too much area has little effect on the object and context.
 
-![][gridmask-0]
+![](../../images/image_aug/hide-and-seek-visual.png)
 
 Therefore, it is the core problem to be solved how to
 if you avoid over-deletion or over-retention becomes the core problem to be solved.
@@ -195,7 +195,7 @@ It shows that the second method is better.
 
 The images after `GridMask` are as follows.
 
-![][test_gridmask]
+![](../../images/image_aug/test_gridmask.jpeg)
 
 <a name="2.3"></a>
 ### 2.3 Image mix
@@ -215,7 +215,7 @@ Mixup is the first solution for image aliasing, it is easy to realize and perfor
 
 The images after `Mixup` are as follows.
 
-![][test_mixup]
+![](../../images/image_aug/test_mixup.png)
 
 <a name="2.3.2"></a>
 #### 2.3.2 Cutmix
@@ -229,7 +229,7 @@ Cutmix randomly cuts out an `ROI` from one image, and then covered onto the corr
 
 The images after `Cutmix` are as follows.
 
-![][test_cutmix]
+![](../../images/image_aug/test_cutmix.png)
 
 For the practical part of data augmentation, please refer to [Data Augmentation Practice](../advanced_tutorials/DataAugmentation_en.md).
 

docs/en/algorithm_introduction/ImageNet_models_en.md

@@ -42,21 +42,15 @@ Based on the ImageNet-1k classification dataset, the 37 classification network s
 
 Curves of accuracy to the inference time of common server-side models are shown as follows.
 
-<div align="center">
-    <img src="../../images/models/V100_benchmark/v100.fp32.bs1.main_fps_top1_s.png" width="800">
-</div>
+![](../../images/models/V100_benchmark/v100.fp32.bs1.main_fps_top1_s.png)
 
 Curves of accuracy to the inference time of common mobile-side models are shown as follows.
 
-<div align="center">
-    <img src="../../images/models/mobile_arm_top1.png" width="800">
-</div>
+![](../../images/models/mobile_arm_top1.png)
 
 Curves of accuracy to the inference time of some VisionTransformer models are shown as follows.
 
-<div align="center">
-    <img src="../../images/models/V100_benchmark/v100.fp32.bs1.visiontransformer.png" width="800">
-</div>
+![](../../images/models/V100_benchmark/v100.fp32.bs1.visiontransformer.png)
 
 <a name="2"></a>
 

docs/en/algorithm_introduction/image_classification_en.md

@@ -1,3 +1,4 @@
+# Image Classification Task Introduction
 ## Catalogue
 
 - [1. Dataset Introduction](#1)

docs/en/algorithm_introduction/index.rst

@@ -0,0 +1,12 @@
+algorithm_introduction
+================================
+
+.. toctree::
+   :maxdepth: 2
+
+   image_classification_en.md
+   metric_learning_en.md
+   knowledge_distillation_en.md
+   model_prune_quantization_en.md
+   ImageNet_models_en.md
+   DataAugmentation_en.md

docs/en/conf.py

@@ -10,70 +10,56 @@
 # 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 recommonmark
+# import os
+# import sys
+# sys.path.insert(0, os.path.abspath('.'))
+import sphinx_rtd_theme
+from recommonmark.parser import CommonMarkParser
+# -- Project information -----------------------------------------------------
 
-exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
+project = 'PaddleClas-en'
+copyright = '2022, PaddleClas'
+author = 'PaddleClas'
 
-# -- Project information -----------------------------------------------------
+# The full version, including alpha/beta/rc tags
+release = '2.3'
 
-project = 'PaddleClas'
-copyright = '2020, paddlepaddle'
-author = 'paddlepaddle'
 
 # -- 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 = [
-    'sphinx.ext.autodoc',
-    'sphinx.ext.napoleon',
-    'sphinx.ext.coverage',
-    'sphinx.ext.viewcode',
-    'sphinx.ext.mathjax',
-    'sphinx.ext.githubpages',
-    'sphinx.ext.napoleon',
-    'recommonmark',
-    'sphinx_markdown_tables',
-]
-
+     'recommonmark',
+     'sphinx_markdown_tables'
+ ]
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ['_templates']
 
-# md file can also be parased
-source_suffix = ['.rst', '.md']
+# The root document.
+root_doc = 'doc_en'
 
-# The master toctree document.
-master_doc = 'index'
+# 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']
 
-# 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 = 'en'
 
 # -- Options for HTML output -------------------------------------------------
 
 # The theme to use for HTML and HTML Help pages.  See the documentation for
 # a list of builtin themes.
-
-# on_rtd is whether we are on readthedocs.org, this line of code grabbed from docs.readthedocs.org
-on_rtd = os.environ.get('READTHEDOCS', None) == 'True'
-
-if not on_rtd:  # only import and set the theme if we're building docs locally
-    import sphinx_rtd_theme
-    html_theme = 'sphinx_rtd_theme'
-    html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
-
-# otherwise, readthedocs.org uses their theme by default, so no need to specify it
+#
+# 更改文档配色
+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']
-
-html_logo = '../images/logo.png'

docs/en/data_preparation/index.rst

@@ -0,0 +1,8 @@
+data_preparation
+================================
+
+.. toctree::
+   :maxdepth: 2
+
+   recognition_dataset_en.md
+   classification_dataset_en.md

docs/en/doc_en.rst

@@ -0,0 +1,23 @@
+Welcome to PaddleClas！
+================================
+
+.. 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
+   
+   
+   
+   
+