mirror of https://github.com/open-mmlab/mmcv.git
[Docs] Build Chinese docs (#1073)
* Remove _build directroy in docs_zh_CN * Change utils title to Chinese * Translate documents * Translate documents * Use symbolic link to avoid repeated images * Use symbolic link to avoid repeated images * fix readme.md * update copyright * refactor docs * rename title to Chinesepull/1182/head
Zaida Zhou
GitHub
parent
0cbe5f4c84
commit
db580dda8d
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@ -65,6 +65,7 @@ instance/
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# Sphinx documentation
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docs/_build/
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docs_zh_CN/_build/
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# PyBuilder
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target/
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@ -27,8 +27,8 @@ __version__ = locals()['__version__']
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# -- Project information -----------------------------------------------------
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project = 'mmcv'
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copyright = '2018-2019, Kai Chen'
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author = 'Kai Chen'
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copyright = '2018-2021, OpenMMLab'
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author = 'MMCV Authors'
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# The short X.Y version
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version = __version__
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@ -1,6 +1,8 @@
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Welcome to MMCV's documentation!
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================================
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You can switch between Chinese and English documents in the lower-left corner of the layout.
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.. toctree::
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:maxdepth: 2
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@ -13,7 +13,7 @@ import mmcv
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img = mmcv.imread('test.jpg')
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img = mmcv.imread('test.jpg', flag='grayscale')
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img_ = mmcv.imread(img) # nothing will happen, img_ = img
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img_ = mmcv.imread(img) # nothing will happen, img_ = img
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mmcv.imwrite(img, 'out.jpg')
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```
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@ -105,7 +105,7 @@ Then use `list_from_file` to load the list from a.txt.
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['/mnt/a', '/mnt/b', '/mnt/c', '/mnt/d', '/mnt/e']
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```
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For example `b.txt` is a text file with 5 lines.
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For example `b.txt` is a text file with 3 lines.
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```
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1 cat
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@ -113,7 +113,7 @@ For example `b.txt` is a text file with 5 lines.
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3 panda
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```
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Then use `dict_from_file` to load the list from a.txt.
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Then use `dict_from_file` to load the dict from `b.txt` .
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```python
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>>> mmcv.dict_from_file('b.txt')
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@ -0,0 +1,19 @@
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# Minimal makefile for Sphinx documentation
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#
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# You can set these variables from the command line.
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SPHINXOPTS =
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SPHINXBUILD = sphinx-build
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SOURCEDIR = .
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BUILDDIR = _build
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# Put it first so that "make" without argument is like "make help".
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help:
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@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
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.PHONY: help Makefile
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# Catch-all target: route all unknown targets to Sphinx using the new
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# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
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%: Makefile
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@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
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@ -0,0 +1 @@
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../docs/_static
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@ -0,0 +1,48 @@
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API 文档
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=========
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fileio
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-------
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.. automodule:: mmcv.fileio
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:members:
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image
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------
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.. automodule:: mmcv.image
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:members:
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video
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------
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.. automodule:: mmcv.video
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:members:
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arraymisc
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---------
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.. automodule:: mmcv.arraymisc
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:members:
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visualization
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--------------
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.. automodule:: mmcv.visualization
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:members:
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utils
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-----
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.. automodule:: mmcv.utils
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:members:
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cnn
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----
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.. automodule:: mmcv.cnn
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:members:
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runner
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------
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.. automodule:: mmcv.runner
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:members:
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ops
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------
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.. automodule:: mmcv.ops
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:members:
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@ -0,0 +1,7 @@
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社区
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===========
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.. toctree::
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:maxdepth: 2
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community/contributing.md
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@ -0,0 +1,3 @@
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## 贡献代码
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欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
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@ -0,0 +1,195 @@
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#
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# Configuration file for the Sphinx documentation builder.
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#
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# This file does only contain a selection of the most common options. For a
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# full list see the documentation:
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# http://www.sphinx-doc.org/en/master/config
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# -- Path setup --------------------------------------------------------------
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# If extensions (or modules to document with autodoc) are in another directory,
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# add these directories to sys.path here. If the directory is relative to the
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# documentation root, use os.path.abspath to make it absolute, like shown here.
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#
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import os
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import sys
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from m2r import MdInclude
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from recommonmark.transform import AutoStructify
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sys.path.insert(0, os.path.abspath('..'))
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version_file = '../mmcv/version.py'
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with open(version_file, 'r') as f:
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exec(compile(f.read(), version_file, 'exec'))
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__version__ = locals()['__version__']
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# -- Project information -----------------------------------------------------
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project = 'mmcv'
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copyright = '2018-2021, OpenMMLab'
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author = 'MMCV Authors'
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# The short X.Y version
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version = __version__
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# The full version, including alpha/beta/rc tags
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release = __version__
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# -- General configuration ---------------------------------------------------
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# If your documentation needs a minimal Sphinx version, state it here.
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#
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# needs_sphinx = '1.0'
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# Add any Sphinx extension module names here, as strings. They can be
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# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
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# ones.
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extensions = [
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'sphinx.ext.autodoc',
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'sphinx.ext.napoleon',
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'sphinx.ext.viewcode',
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'recommonmark',
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'sphinx.ext.autosectionlabel',
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'sphinx_markdown_tables'
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] # yapf: disable
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autodoc_mock_imports = ['mmcv._ext', 'mmcv.utils.ext_loader', 'torchvision']
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autosectionlabel_prefix_document = True
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# Add any paths that contain templates here, relative to this directory.
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templates_path = ['_templates']
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# The suffix(es) of source filenames.
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# You can specify multiple suffix as a list of string:
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#
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source_suffix = {
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'.rst': 'restructuredtext',
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'.md': 'markdown',
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}
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# The master toctree document.
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master_doc = 'index'
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# The language for content autogenerated by Sphinx. Refer to documentation
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# for a list of supported languages.
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#
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# This is also used if you do content translation via gettext catalogs.
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# Usually you set "language" from the command line for these cases.
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language = 'zh_CN'
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# List of patterns, relative to source directory, that match files and
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# directories to ignore when looking for source files.
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# This pattern also affects html_static_path and html_extra_path.
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exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
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# The name of the Pygments (syntax highlighting) style to use.
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pygments_style = 'sphinx'
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# -- Options for HTML output -------------------------------------------------
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# The theme to use for HTML and HTML Help pages. See the documentation for
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# a list of builtin themes.
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#
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html_theme = 'sphinx_rtd_theme'
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# Theme options are theme-specific and customize the look and feel of a theme
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# further. For a list of options available for each theme, see the
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# documentation.
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#
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# html_theme_options = {}
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# Add any paths that contain custom static files (such as style sheets) here,
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# relative to this directory. They are copied after the builtin static files,
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# so a file named "default.css" will overwrite the builtin "default.css".
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html_static_path = ['_static']
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# Custom sidebar templates, must be a dictionary that maps document names
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# to template names.
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#
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# The default sidebars (for documents that don't match any pattern) are
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# defined by theme itself. Builtin themes are using these templates by
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# default: ``['localtoc.html', 'relations.html', 'sourcelink.html',
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# 'searchbox.html']``.
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#
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# html_sidebars = {}
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# -- Options for HTMLHelp output ---------------------------------------------
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# Output file base name for HTML help builder.
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htmlhelp_basename = 'mmcvdoc'
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# -- Options for LaTeX output ------------------------------------------------
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latex_elements = {
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# The paper size ('letterpaper' or 'a4paper').
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#
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# 'papersize': 'letterpaper',
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# The font size ('10pt', '11pt' or '12pt').
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#
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# 'pointsize': '10pt',
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# Additional stuff for the LaTeX preamble.
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#
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# 'preamble': '',
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# Latex figure (float) alignment
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#
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# 'figure_align': 'htbp',
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}
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# Grouping the document tree into LaTeX files. List of tuples
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# (source start file, target name, title,
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# author, documentclass [howto, manual, or own class]).
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latex_documents = [
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(master_doc, 'mmcv.tex', 'mmcv Documentation', 'Kai Chen', 'manual'),
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]
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# -- Options for manual page output ------------------------------------------
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# One entry per manual page. List of tuples
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# (source start file, name, description, authors, manual section).
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man_pages = [(master_doc, 'mmcv', 'mmcv Documentation', [author], 1)]
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# -- Options for Texinfo output ----------------------------------------------
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# Grouping the document tree into Texinfo files. List of tuples
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# (source start file, target name, title, author,
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# dir menu entry, description, category)
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texinfo_documents = [
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(master_doc, 'mmcv', 'mmcv Documentation', author, 'mmcv',
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'One line description of project.', 'Miscellaneous'),
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]
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# -- Options for Epub output -------------------------------------------------
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# Bibliographic Dublin Core info.
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epub_title = project
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# The unique identifier of the text. This can be a ISBN number
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# or the project homepage.
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#
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# epub_identifier = ''
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# A unique identification for the text.
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#
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# epub_uid = ''
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# A list of files that should not be packed into the epub file.
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epub_exclude_files = ['search.html']
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# -- Extension configuration -------------------------------------------------
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def setup(app):
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app.add_config_value('no_underscore_emphasis', False, 'env')
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app.add_config_value('m2r_parse_relative_links', False, 'env')
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app.add_config_value('m2r_anonymous_references', False, 'env')
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app.add_config_value('m2r_disable_inline_math', False, 'env')
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app.add_directive('mdinclude', MdInclude)
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app.add_config_value('recommonmark_config', {
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'auto_toc_tree_section': 'Contents',
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'enable_eval_rst': True,
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}, True)
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app.add_transform(AutoStructify)
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@ -0,0 +1,11 @@
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部署
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========
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.. toctree::
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:maxdepth: 2
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deployment/onnx.md
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deployment/onnxruntime_op.md
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deployment/onnxruntime_custom_ops.md
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deployment/tensorrt_plugin.md
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deployment/tensorrt_custom_ops.md
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|
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@ -0,0 +1,3 @@
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# MMCV 中的 onnx 模块 (实验性质)
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欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
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|
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@ -0,0 +1,3 @@
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# Onnxruntime 自定义算子
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|
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欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
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|
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@ -0,0 +1,3 @@
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# MMCV 中用于 ONNX Runtime 的自定义算子
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欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
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|
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@ -0,0 +1,3 @@
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# TensorRT 自定义算子
|
||||
|
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欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
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|
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@ -0,0 +1,3 @@
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# MMCV 中用于自定义算子的 TensorRT 插件 (实验性质)
|
||||
|
||||
欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
|
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|
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@ -0,0 +1,3 @@
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## 常见问题
|
||||
|
||||
欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
|
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|
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@ -0,0 +1,9 @@
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介绍及安装
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===================
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.. toctree::
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:maxdepth: 2
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get_started/introduction.md
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get_started/installation.md
|
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get_started/build.md
|
||||
|
|
@ -0,0 +1,3 @@
|
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## 从源码编译 MMCV
|
||||
|
||||
欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
## 安装 MMCV
|
||||
|
||||
欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
## 介绍 MMCV
|
||||
|
||||
欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
|
||||
|
|
@ -0,0 +1,21 @@
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欢迎来到 MMCV 的中文文档！
|
||||
=============================
|
||||
|
||||
您可以在页面左下角切换中英文文档。
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 2
|
||||
|
||||
get_started.rst
|
||||
deployment.rst
|
||||
understand_mmcv.rst
|
||||
api.rst
|
||||
faq.md
|
||||
community.rst
|
||||
|
||||
|
||||
Indices and tables
|
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==================
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||||
|
||||
* :ref:`genindex`
|
||||
* :ref:`search`
|
||||
|
|
@ -0,0 +1,35 @@
|
|||
@ECHO OFF
|
||||
|
||||
pushd %~dp0
|
||||
|
||||
REM Command file for Sphinx documentation
|
||||
|
||||
if "%SPHINXBUILD%" == "" (
|
||||
set SPHINXBUILD=sphinx-build
|
||||
)
|
||||
set SOURCEDIR=.
|
||||
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.http://sphinx-doc.org/
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS%
|
||||
goto end
|
||||
|
||||
:help
|
||||
%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS%
|
||||
|
||||
:end
|
||||
popd
|
||||
|
|
@ -0,0 +1 @@
|
|||
../docs/mmcv-logo.png
|
||||
|
|
@ -0,0 +1,15 @@
|
|||
深入理解 MMCV
|
||||
=================
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 2
|
||||
|
||||
understand_mmcv/config.md
|
||||
understand_mmcv/registry.md
|
||||
understand_mmcv/runner.md
|
||||
understand_mmcv/io.md
|
||||
understand_mmcv/data_process.md
|
||||
understand_mmcv/visualization.md
|
||||
understand_mmcv/cnn.md
|
||||
understand_mmcv/ops.md
|
||||
understand_mmcv/utils.md
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
## 卷积神经网络
|
||||
|
||||
欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
## 配置
|
||||
|
||||
欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
|
||||
|
|
@ -0,0 +1,275 @@
|
|||
## 数据处理
|
||||
|
||||
### 图像
|
||||
|
||||
图像模块提供了一些图像预处理的函数，该模块依赖 `opencv` 。
|
||||
|
||||
#### 读取/保存/显示
|
||||
|
||||
使用 `imread` 和 `imwrite` 函数可以读取和保存图像。
|
||||
|
||||
```python
|
||||
import mmcv
|
||||
|
||||
img = mmcv.imread('test.jpg')
|
||||
img = mmcv.imread('test.jpg', flag='grayscale')
|
||||
img_ = mmcv.imread(img) # 相当于什么也没做
|
||||
mmcv.imwrite(img, 'out.jpg')
|
||||
```
|
||||
|
||||
从二进制中读取图像
|
||||
|
||||
```python
|
||||
with open('test.jpg', 'rb') as f:
|
||||
data = f.read()
|
||||
img = mmcv.imfrombytes(data)
|
||||
```
|
||||
|
||||
显示图像文件或已读取的图像
|
||||
|
||||
```python
|
||||
mmcv.imshow('tests/data/color.jpg')
|
||||
|
||||
for i in range(10):
|
||||
img = np.random.randint(256, size=(100, 100, 3), dtype=np.uint8)
|
||||
mmcv.imshow(img, win_name='test image', wait_time=200)
|
||||
```
|
||||
|
||||
#### 色彩空间转换
|
||||
|
||||
支持的转换函数：
|
||||
|
||||
- bgr2gray
|
||||
- gray2bgr
|
||||
- bgr2rgb
|
||||
- rgb2bgr
|
||||
- bgr2hsv
|
||||
- hsv2bgr
|
||||
|
||||
```python
|
||||
img = mmcv.imread('tests/data/color.jpg')
|
||||
img1 = mmcv.bgr2rgb(img)
|
||||
img2 = mmcv.rgb2gray(img1)
|
||||
img3 = mmcv.bgr2hsv(img)
|
||||
```
|
||||
|
||||
#### 缩放
|
||||
|
||||
有三种缩放图像的方法。所有以 `imresize_*` 开头的函数都有一个 `return_scale` 参数，如果
|
||||
该参数为 `False` ，函数的返回值只有调整之后的图像，否则是一个元组 `(resized_img, scale)` 。
|
||||
|
||||
```python
|
||||
# 缩放图像至给定的尺寸
|
||||
mmcv.imresize(img, (1000, 600), return_scale=True)
|
||||
|
||||
# 缩放图像至与给定的图像同样的尺寸
|
||||
mmcv.imresize_like(img, dst_img, return_scale=False)
|
||||
|
||||
# 以一定的比例缩放图像
|
||||
mmcv.imrescale(img, 0.5)
|
||||
|
||||
# 缩放图像至最长的边不大于1000、最短的边不大于800并且没有改变图像的长宽比
|
||||
mmcv.imrescale(img, (1000, 800))
|
||||
```
|
||||
|
||||
#### 旋转
|
||||
|
||||
我们可以使用 `imrotate` 旋转图像一定的角度。旋转的中心需要指定，默认值是原始图像的中心。有
|
||||
两种旋转的模式，一种保持图像的尺寸不变，因此旋转后原始图像中的某些部分会被裁剪，另一种是扩大
|
||||
图像的尺寸进而保留完整的原始图像。
|
||||
|
||||
```python
|
||||
img = mmcv.imread('tests/data/color.jpg')
|
||||
|
||||
# 顺时针旋转图像30度
|
||||
img_ = mmcv.imrotate(img, 30)
|
||||
|
||||
# 逆时针旋转图像90度
|
||||
img_ = mmcv.imrotate(img, -90)
|
||||
|
||||
# 顺时针旋转图像30度并且缩放图像为原始图像的1.5倍
|
||||
img_ = mmcv.imrotate(img, 30, scale=1.5)
|
||||
|
||||
# 以坐标(100, 100)为中心顺时针旋转图像30度
|
||||
img_ = mmcv.imrotate(img, 30, center=(100, 100))
|
||||
|
||||
# 顺时针旋转图像30度并扩大图像的尺寸
|
||||
img_ = mmcv.imrotate(img, 30, auto_bound=True)
|
||||
```
|
||||
|
||||
#### 翻转
|
||||
|
||||
我们可以使用 `imflip` 翻转图像。
|
||||
|
||||
```python
|
||||
img = mmcv.imread('tests/data/color.jpg')
|
||||
|
||||
# 水平翻转图像
|
||||
mmcv.imflip(img)
|
||||
|
||||
# 垂直翻转图像
|
||||
mmcv.imflip(img, direction='vertical')
|
||||
```
|
||||
|
||||
#### 裁剪
|
||||
|
||||
`imcrop` 可以裁剪图像的一个或多个区域，每个区域用左上角和右下角坐标表示，形如(x1, y1, x2, y2)
|
||||
|
||||
```python
|
||||
import mmcv
|
||||
import numpy as np
|
||||
|
||||
img = mmcv.imread('tests/data/color.jpg')
|
||||
|
||||
# 裁剪区域 (10, 10, 100, 120)
|
||||
bboxes = np.array([10, 10, 100, 120])
|
||||
patch = mmcv.imcrop(img, bboxes)
|
||||
|
||||
# 裁剪两个区域，分别是 (10, 10, 100, 120) 和 (0, 0, 50, 50)
|
||||
bboxes = np.array([[10, 10, 100, 120], [0, 0, 50, 50]])
|
||||
patches = mmcv.imcrop(img, bboxes)
|
||||
|
||||
# 裁剪两个区域并且缩放区域1.2倍
|
||||
patches = mmcv.imcrop(img, bboxes, scale_ratio=1.2)
|
||||
```
|
||||
|
||||
#### 填充
|
||||
|
||||
`impad` and `impad_to_multiple` 可以用给定的值将图像填充至给定的尺寸。
|
||||
|
||||
```python
|
||||
img = mmcv.imread('tests/data/color.jpg')
|
||||
|
||||
# 用给定值将图像填充至 (1000, 1200)
|
||||
img_ = mmcv.impad(img, shape=(1000, 1200), pad_val=0)
|
||||
|
||||
# 用给定值分别填充图像的3个通道至 (1000, 1200)
|
||||
img_ = mmcv.impad(img, shape=(1000, 1200), pad_val=[100, 50, 200])
|
||||
|
||||
# 用给定值填充图像的左、右、上、下四条边
|
||||
img_ = mmcv.impad(img, padding=(10, 20, 30, 40), pad_val=0)
|
||||
|
||||
# 用3个值分别填充图像的左、右、上、下四条边的3个通道
|
||||
img_ = mmcv.impad(img, padding=(10, 20, 30, 40), pad_val=[100, 50, 200])
|
||||
|
||||
# 将图像的四条边填充至能够被给定值整除
|
||||
img_ = mmcv.impad_to_multiple(img, 32)
|
||||
```
|
||||
|
||||
### 视频
|
||||
|
||||
视频模块提供了以下的功能：
|
||||
|
||||
- 一个 `VideoReader` 类，具有友好的 API 接口可以读取和转换视频
|
||||
- 一些编辑视频的方法，包括 `cut` ， `concat` ， `resize`
|
||||
- 光流的读取/保存/变换
|
||||
|
||||
#### VideoReader
|
||||
|
||||
`VideoReader` 类提供了和序列一样的接口去获取视频帧。该类会缓存所有被访问过的帧。
|
||||
|
||||
```python
|
||||
video = mmcv.VideoReader('test.mp4')
|
||||
|
||||
# 获取基本的信息
|
||||
print(len(video))
|
||||
print(video.width, video.height, video.resolution, video.fps)
|
||||
|
||||
# 遍历所有的帧
|
||||
for frame in video:
|
||||
print(frame.shape)
|
||||
|
||||
# 读取下一帧
|
||||
img = video.read()
|
||||
|
||||
# 使用索引获取帧
|
||||
img = video[100]
|
||||
|
||||
# 获取指定范围的帧
|
||||
img = video[5:10]
|
||||
```
|
||||
|
||||
将视频切成帧并保存至给定目录或者从给定目录中生成视频。
|
||||
|
||||
```python
|
||||
# 将视频切成帧并保存至目录
|
||||
video = mmcv.VideoReader('test.mp4')
|
||||
video.cvt2frames('out_dir')
|
||||
|
||||
# 从给定目录中生成视频
|
||||
mmcv.frames2video('out_dir', 'test.avi')
|
||||
```
|
||||
|
||||
#### 编辑函数
|
||||
|
||||
有几个用于编辑视频的函数，这些函数是对 `ffmpeg` 的封装。
|
||||
|
||||
```python
|
||||
# 裁剪视频
|
||||
mmcv.cut_video('test.mp4', 'clip1.mp4', start=3, end=10, vcodec='h264')
|
||||
|
||||
# 将多个视频拼接成一个视频
|
||||
mmcv.concat_video(['clip1.mp4', 'clip2.mp4'], 'joined.mp4', log_level='quiet')
|
||||
|
||||
# 将视频缩放至给定的尺寸
|
||||
mmcv.resize_video('test.mp4', 'resized1.mp4', (360, 240))
|
||||
|
||||
# 将视频缩放至给定的倍率
|
||||
mmcv.resize_video('test.mp4', 'resized2.mp4', ratio=2)
|
||||
```
|
||||
|
||||
#### 光流
|
||||
|
||||
`mmcv` 提供了以下用于操作光流的函数：
|
||||
|
||||
- 读取/保存
|
||||
- 可视化
|
||||
- 流变换
|
||||
|
||||
我们提供了两种将光流dump到文件的方法，分别是非压缩和压缩的方法。非压缩的方法直接将浮点数值的光流
|
||||
保存至二进制文件，虽然光流无损但文件会比较大。而压缩的方法先量化光流至 0-255 整形数值再保存为
|
||||
jpeg图像。光流的x维度和y维度会被拼接到图像中。
|
||||
|
||||
1. 读取/保存
|
||||
|
||||
```python
|
||||
flow = np.random.rand(800, 600, 2).astype(np.float32)
|
||||
# 保存光流到flo文件 (~3.7M)
|
||||
mmcv.flowwrite(flow, 'uncompressed.flo')
|
||||
# 保存光流为jpeg图像 (~230K)，图像的尺寸为 (800, 1200)
|
||||
mmcv.flowwrite(flow, 'compressed.jpg', quantize=True, concat_axis=1)
|
||||
|
||||
# 读取光流文件，以下两种方式读取的光流尺寸均为 (800, 600, 2)
|
||||
flow = mmcv.flowread('uncompressed.flo')
|
||||
flow = mmcv.flowread('compressed.jpg', quantize=True, concat_axis=1)
|
||||
```
|
||||
|
||||
2. 可视化
|
||||
|
||||
使用 `mmcv.flowshow()` 可视化光流
|
||||
|
||||
```python
|
||||
mmcv.flowshow(flow)
|
||||
```
|
||||
|
||||
|
||||
|
||||
3. 流变换
|
||||
|
||||
```python
|
||||
img1 = mmcv.imread('img1.jpg')
|
||||
flow = mmcv.flowread('flow.flo')
|
||||
warpped_img2 = mmcv.flow_warp(img1, flow)
|
||||
```
|
||||
|
||||
img1 (左) and img2 (右)
|
||||
|
||||
|
||||
|
||||
光流 (img2 -> img1)
|
||||
|
||||
|
||||
|
||||
变换后的图像和真实图像的差异
|
||||
|
||||
|
||||
|
|
@ -0,0 +1,119 @@
|
|||
## 文件输入输出
|
||||
|
||||
文件输入输出模块提供了两个通用的 API 接口用于读取和保存不同格式的文件。
|
||||
|
||||
### 读取和保存数据
|
||||
|
||||
`mmcv` 提供了一个通用的 api 用于读取和保存数据，目前支持的格式有 json、yaml 和 pickle。
|
||||
|
||||
```python
|
||||
import mmcv
|
||||
|
||||
# 从文件中读取数据
|
||||
data = mmcv.load('test.json')
|
||||
data = mmcv.load('test.yaml')
|
||||
data = mmcv.load('test.pkl')
|
||||
# 从文件对象中读取数据
|
||||
with open('test.json', 'r') as f:
|
||||
data = mmcv.load(f, file_format='json')
|
||||
|
||||
# 将数据序列化为字符串
|
||||
json_str = mmcv.dump(data, file_format='json')
|
||||
|
||||
# 将数据保存至文件 (根据文件名后缀反推文件类型)
|
||||
mmcv.dump(data, 'out.pkl')
|
||||
|
||||
# 将数据保存至文件对象
|
||||
with open('test.yaml', 'w') as f:
|
||||
data = mmcv.dump(data, f, file_format='yaml')
|
||||
```
|
||||
|
||||
我们提供了易于拓展的方式以支持更多的文件格式。我们只需要创建一个继承自 `BaseFileHandler` 的
|
||||
文件句柄类并将其注册到 `mmcv` 中即可。句柄类至少需要重写三个方法。
|
||||
|
||||
```python
|
||||
import mmcv
|
||||
|
||||
# 支持为文件句柄类注册多个文件格式
|
||||
# @mmcv.register_handler(['txt', 'log'])
|
||||
@mmcv.register_handler('txt')
|
||||
class TxtHandler1(mmcv.BaseFileHandler):
|
||||
|
||||
def load_from_fileobj(self, file):
|
||||
return file.read()
|
||||
|
||||
def dump_to_fileobj(self, obj, file):
|
||||
file.write(str(obj))
|
||||
|
||||
def dump_to_str(self, obj, **kwargs):
|
||||
return str(obj)
|
||||
```
|
||||
|
||||
举 `PickleHandler` 为例。
|
||||
|
||||
```python
|
||||
import pickle
|
||||
|
||||
class PickleHandler(mmcv.BaseFileHandler):
|
||||
|
||||
def load_from_fileobj(self, file, **kwargs):
|
||||
return pickle.load(file, **kwargs)
|
||||
|
||||
def load_from_path(self, filepath, **kwargs):
|
||||
return super(PickleHandler, self).load_from_path(
|
||||
filepath, mode='rb', **kwargs)
|
||||
|
||||
def dump_to_str(self, obj, **kwargs):
|
||||
kwargs.setdefault('protocol', 2)
|
||||
return pickle.dumps(obj, **kwargs)
|
||||
|
||||
def dump_to_fileobj(self, obj, file, **kwargs):
|
||||
kwargs.setdefault('protocol', 2)
|
||||
pickle.dump(obj, file, **kwargs)
|
||||
|
||||
def dump_to_path(self, obj, filepath, **kwargs):
|
||||
super(PickleHandler, self).dump_to_path(
|
||||
obj, filepath, mode='wb', **kwargs)
|
||||
```
|
||||
|
||||
### 读取文件并返回列表或字典
|
||||
|
||||
例如， `a.txt` 是文本文件，一共有5行内容。
|
||||
|
||||
```
|
||||
a
|
||||
b
|
||||
c
|
||||
d
|
||||
e
|
||||
```
|
||||
|
||||
使用 `list_from_file` 读取 `a.txt` 。
|
||||
|
||||
```python
|
||||
>>> mmcv.list_from_file('a.txt')
|
||||
['a', 'b', 'c', 'd', 'e']
|
||||
>>> mmcv.list_from_file('a.txt', offset=2)
|
||||
['c', 'd', 'e']
|
||||
>>> mmcv.list_from_file('a.txt', max_num=2)
|
||||
['a', 'b']
|
||||
>>> mmcv.list_from_file('a.txt', prefix='/mnt/')
|
||||
['/mnt/a', '/mnt/b', '/mnt/c', '/mnt/d', '/mnt/e']
|
||||
```
|
||||
|
||||
同样， `b.txt` 也是文本文件，一共有3行内容。
|
||||
|
||||
```
|
||||
1 cat
|
||||
2 dog cow
|
||||
3 panda
|
||||
```
|
||||
|
||||
使用 `dict_from_file` 读取 `b.txt` 。
|
||||
|
||||
```python
|
||||
>>> mmcv.dict_from_file('b.txt')
|
||||
{'1': 'cat', '2': ['dog', 'cow'], '3': 'panda'}
|
||||
>>> mmcv.dict_from_file('b.txt', key_type=int)
|
||||
{1: 'cat', 2: ['dog', 'cow'], 3: 'panda'}
|
||||
```
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
## CUDA 算子
|
||||
|
||||
欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
## 注册器
|
||||
|
||||
欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
## 执行器
|
||||
|
||||
欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
## 辅助函数
|
||||
|
||||
欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
|
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|
|
@ -0,0 +1,3 @@
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## 可视化
|
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|
||||
欢迎有兴趣的朋友一起翻译 MMCV 文档。如有兴趣，请在 [MMCV issue](https://github.com/open-mmlab/mmcv/issues) 提 issue 确定翻译的文档。
|
||||
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Reference in New Issue