Skip to content

GitLab

"examples/vscode:/vscode.git/clone" did not exist on "32cd0048153955ae3bb4591b47a82a9a28e22cb0"
Commit 4353fa59 authored by limm's avatar limm
Browse files

add part code

parents
Pipeline #2807 canceled with stages
Hide whitespace changes
Inline Side-by-side
Showing with 5470 additions and 0 deletions
CITATION.cff 0 → 100644
View file @ 4353fa59
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
title: "OpenMMLab's Model deployment toolbox"
authors:
- name: "MMDeploy Contributors"
date-released: 2021-12-27
url: "https://github.com/open-mmlab/mmdeploy"
license: Apache-2.0
CMakeLists.txt 0 → 100644
View file @ 4353fa59
# Copyright (c) OpenMMLab. All rights reserved.
if (NOT DEFINED CMAKE_INSTALL_PREFIX)
set(CMAKE_INSTALL_PREFIX "${CMAKE_BINARY_DIR}/install" CACHE PATH "installation directory")
endif ()
message(STATUS "CMAKE_INSTALL_PREFIX: ${CMAKE_INSTALL_PREFIX}")
if (NOT CMAKE_BUILD_TYPE)
set(CMAKE_BUILD_TYPE Release CACHE STRING "choose 'Release' as default build type" FORCE)
endif ()
cmake_minimum_required(VERSION 3.14)
project(MMDeploy VERSION 1.3.1)
set(CMAKE_CXX_STANDARD 17)
set(MMDEPLOY_VERSION_MAJOR ${PROJECT_VERSION_MAJOR})
set(MMDEPLOY_VERSION_MINOR ${PROJECT_VERSION_MINOR})
set(MMDEPLOY_VERSION_PATCH ${PROJECT_VERSION_PATCH})
set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
if (MSVC)
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
else ()
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
endif ()
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
# options
option(MMDEPLOY_SHARED_LIBS "build shared libs" OFF)
option(MMDEPLOY_BUILD_SDK "build MMDeploy SDK" OFF)
option(MMDEPLOY_DYNAMIC_BACKEND "dynamic load backend" OFF)
option(MMDEPLOY_BUILD_SDK_MONOLITHIC "build single lib for SDK API" ON)
option(MMDEPLOY_BUILD_TEST "build unittests" OFF)
option(MMDEPLOY_BUILD_SDK_PYTHON_API "build SDK Python API" OFF)
option(MMDEPLOY_BUILD_SDK_CSHARP_API "build SDK C# API support" OFF)
option(MMDEPLOY_BUILD_SDK_JAVA_API "build SDK JAVA API" OFF)
option(MMDEPLOY_BUILD_EXAMPLES "build examples" OFF)
option(MMDEPLOY_SPDLOG_EXTERNAL "use external spdlog" OFF)
option(MMDEPLOY_ZIP_MODEL "support SDK model in zip format" OFF)
option(MMDEPLOY_COVERAGE "build SDK for coverage" OFF)
option(MMDEPLOY_USE_MSCV_STATIC "statically linked CRT" OFF)
option(MMDEPLOY_ELENA_FUSION "use elena to fuse preprocess" OFF)
set(MMDEPLOY_TARGET_DEVICES "cpu" CACHE STRING "target devices to support")
set(MMDEPLOY_TARGET_BACKENDS "" CACHE STRING "target inference engines to support")
set(MMDEPLOY_CODEBASES "all" CACHE STRING "select OpenMMLab codebases")
if ((NOT MMDEPLOY_BUILD_SDK_MONOLITHIC) AND MMDEPLOY_DYNAMIC_BACKEND)
set(MMDEPLOY_DYNAMIC_BACKEND OFF)
endif ()
if (MMDEPLOY_SHARED_LIBS)
set(MMDEPLOY_LIB_TYPE SHARED)
else ()
set(MMDEPLOY_LIB_TYPE STATIC)
endif ()
set(MMDEPLOY_TASKS "" CACHE INTERNAL "")
if (MMDEPLOY_COVERAGE)
add_compile_options(-coverage -fprofile-arcs -ftest-coverage)
add_link_options(-coverage -lgcov)
endif ()
# when CUDA devices are enabled, the environment variable ASAN_OPTIONS=protect_shadow_gap=0
# must be set at runtime
if (MMDEPLOY_ASAN_ENABLE)
add_compile_options($<$<COMPILE_LANGUAGE:CXX>:-fsanitize=address>)
add_link_options(-fsanitize=address)
endif ()
# notice that ubsan has linker issues for ubuntu < 18.04, see
# https://stackoverflow.com/questions/50024731/ld-unrecognized-option-push-state-no-as-needed
if (MMDEPLOY_UBSAN_ENABLE)
add_compile_options($<$<COMPILE_LANGUAGE:CXX>:-fsanitize=undefined>)
add_link_options(-fsanitize=undefined)
endif ()
if (MSVC)
add_compile_options($<$<COMPILE_LANGUAGE:CXX>:/diagnostics:classic>)
add_compile_options($<$<COMPILE_LANGUAGE:CXX>:/wd4251>)
if (MMDEPLOY_USE_MSCV_STATIC)
foreach(lang C CXX)
string(REPLACE /MD /MT CMAKE_${lang}_FLAGS_DEBUG "${CMAKE_${lang}_FLAGS_DEBUG}")
string(REPLACE /MD /MT CMAKE_${lang}_FLAGS_RELEASE "${CMAKE_${lang}_FLAGS_RELEASE}")
endforeach()
endif ()
endif ()
if(APPLE)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fobjc-arc")
endif()
add_library(MMDeployStaticModules INTERFACE)
add_library(MMDeployDynamicModules INTERFACE)
add_library(MMDeployLibs INTERFACE)
if ((cuda IN_LIST MMDEPLOY_TARGET_DEVICES) OR (trt IN_LIST MMDEPLOY_TARGET_BACKENDS))
include(cmake/cuda.cmake NO_POLICY_SCOPE)
endif ()
# this must come after including cuda.cmake because policies in function scope is captured
# at function definition
include(cmake/MMDeploy.cmake)
add_subdirectory(csrc/mmdeploy)
if (MMDEPLOY_BUILD_SDK)
if (NOT MMDEPLOY_BUILD_SDK_MONOLITHIC)
install(TARGETS MMDeployStaticModules
MMDeployDynamicModules
MMDeployLibs
EXPORT MMDeployTargets)
endif ()
if (MMDEPLOY_BUILD_TEST)
add_subdirectory(tests/test_csrc)
endif ()
if (MMDEPLOY_BUILD_EXAMPLES)
include(${CMAKE_SOURCE_DIR}/cmake/opencv.cmake)
add_subdirectory(demo/csrc)
endif ()
# export MMDeploy package
install(EXPORT MMDeployTargets
FILE MMDeployTargets.cmake
DESTINATION lib/cmake/MMDeploy)
if (MMDEPLOY_SPDLOG_EXTERNAL)
set(SPDLOG_DEPENDENCY "find_package(spdlog QUIET)")
endif ()
# append backend deps
mmdeploy_add_deps(trt BACKENDS ${MMDEPLOY_TARGET_BACKENDS} DEPS TENSORRT CUDNN)
mmdeploy_add_deps(ort BACKENDS ${MMDEPLOY_TARGET_BACKENDS} DEPS ONNXRUNTIME)
mmdeploy_add_deps(ncnn BACKENDS ${MMDEPLOY_TARGET_BACKENDS} DEPS ncnn)
mmdeploy_add_deps(openvino BACKENDS ${MMDEPLOY_TARGET_BACKENDS} DEPS InferenceEngine)
if (NOT MMDEPLOY_SHARED_LIBS)
mmdeploy_add_deps(pplnn BACKENDS ${MMDEPLOY_TARGET_BACKENDS} DEPS pplnn)
endif ()
mmdeploy_add_deps(snpe BACKENDS ${MMDEPLOY_TARGET_BACKENDS} DEPS snpe)
mmdeploy_add_deps(rknn BACKENDS ${MMDEPLOY_TARGET_BACKENDS} DEPS rknn)
include(CMakePackageConfigHelpers)
# generate the config file that is includes the exports
configure_package_config_file(${CMAKE_SOURCE_DIR}/cmake/MMDeployConfig.cmake.in
"${CMAKE_CURRENT_BINARY_DIR}/MMDeployConfig.cmake"
INSTALL_DESTINATION "lib/cmake"
NO_SET_AND_CHECK_MACRO
NO_CHECK_REQUIRED_COMPONENTS_MACRO
)
write_basic_package_version_file(
"${CMAKE_CURRENT_BINARY_DIR}/MMDeployConfigVersion.cmake"
VERSION "${MMDeploy_VERSION_MAJOR}.${MMDeploy_VERSION_MINOR}"
COMPATIBILITY AnyNewerVersion
)
install(FILES
${CMAKE_CURRENT_BINARY_DIR}/MMDeployConfig.cmake
${CMAKE_CURRENT_BINARY_DIR}/MMDeployConfigVersion.cmake
${CMAKE_CURRENT_SOURCE_DIR}/cmake/MMDeploy.cmake
DESTINATION lib/cmake/MMDeploy
)
if (MSVC)
install(FILES
${CMAKE_CURRENT_SOURCE_DIR}/cmake/loader.cpp.in
DESTINATION lib/cmake/MMDeploy
)
endif ()
install(DIRECTORY
${CMAKE_CURRENT_SOURCE_DIR}/cmake/modules
DESTINATION lib/cmake/MMDeploy
)
if (${CMAKE_VERSION} VERSION_LESS "3.17.0")
install(SCRIPT cmake/post-install.cmake)
endif ()
endif ()
LICENSE 0 → 100644
View file @ 4353fa59
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
and distribution as defined by Sections 1 through 9 of this document.
"Licensor" shall mean the copyright owner or entity authorized by
the copyright owner that is granting the License.
"Legal Entity" shall mean the union of the acting entity and all
other entities that control, are controlled by, or are under common
control with that entity. For the purposes of this definition,
"control" means (i) the power, direct or indirect, to cause the
direction or management of such entity, whether by contract or
otherwise, or (ii) ownership of fifty percent (50%) or more of the
outstanding shares, or (iii) beneficial ownership of such entity.
"You" (or "Your") shall mean an individual or Legal Entity
exercising permissions granted by this License.
"Source" form shall mean the preferred form for making modifications,
including but not limited to software source code, documentation
source, and configuration files.
"Object" form shall mean any form resulting from mechanical
transformation or translation of a Source form, including but
not limited to compiled object code, generated documentation,
and conversions to other media types.
"Work" shall mean the work of authorship, whether in Source or
Object form, made available under the License, as indicated by a
copyright notice that is included in or attached to the work
(an example is provided in the Appendix below).
"Derivative Works" shall mean any work, whether in Source or Object
form, that is based on (or derived from) the Work and for which the
editorial revisions, annotations, elaborations, or other modifications
represent, as a whole, an original work of authorship. For the purposes
of this License, Derivative Works shall not include works that remain
separable from, or merely link (or bind by name) to the interfaces of,
the Work and Derivative Works thereof.
"Contribution" shall mean any work of authorship, including
the original version of the Work and any modifications or additions
to that Work or Derivative Works thereof, that is intentionally
submitted to Licensor for inclusion in the Work by the copyright owner
or by an individual or Legal Entity authorized to submit on behalf of
the copyright owner. For the purposes of this definition, "submitted"
means any form of electronic, verbal, or written communication sent
to the Licensor or its representatives, including but not limited to
communication on electronic mailing lists, source code control systems,
and issue tracking systems that are managed by, or on behalf of, the
Licensor for the purpose of discussing and improving the Work, but
excluding communication that is conspicuously marked or otherwise
designated in writing by the copyright owner as "Not a Contribution."
"Contributor" shall mean Licensor and any individual or Legal Entity
on behalf of whom a Contribution has been received by Licensor and
subsequently incorporated within the Work.
2. Grant of Copyright License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
copyright license to reproduce, prepare Derivative Works of,
publicly display, publicly perform, sublicense, and distribute the
Work and such Derivative Works in Source or Object form.
3. Grant of Patent License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
(except as stated in this section) patent license to make, have made,
use, offer to sell, sell, import, and otherwise transfer the Work,
where such license applies only to those patent claims licensable
by such Contributor that are necessarily infringed by their
Contribution(s) alone or by combination of their Contribution(s)
with the Work to which such Contribution(s) was submitted. If You
institute patent litigation against any entity (including a
cross-claim or counterclaim in a lawsuit) alleging that the Work
or a Contribution incorporated within the Work constitutes direct
or contributory patent infringement, then any patent licenses
granted to You under this License for that Work shall terminate
as of the date such litigation is filed.
4. Redistribution. You may reproduce and distribute copies of the
Work or Derivative Works thereof in any medium, with or without
modifications, and in Source or Object form, provided that You
meet the following conditions:
(a) You must give any other recipients of the Work or
Derivative Works a copy of this License; and
(b) You must cause any modified files to carry prominent notices
stating that You changed the files; and
(c) You must retain, in the Source form of any Derivative Works
that You distribute, all copyright, patent, trademark, and
attribution notices from the Source form of the Work,
excluding those notices that do not pertain to any part of
the Derivative Works; and
(d) If the Work includes a "NOTICE" text file as part of its
distribution, then any Derivative Works that You distribute must
include a readable copy of the attribution notices contained
within such NOTICE file, excluding those notices that do not
pertain to any part of the Derivative Works, in at least one
of the following places: within a NOTICE text file distributed
as part of the Derivative Works; within the Source form or
documentation, if provided along with the Derivative Works; or,
within a display generated by the Derivative Works, if and
wherever such third-party notices normally appear. The contents
of the NOTICE file are for informational purposes only and
do not modify the License. You may add Your own attribution
notices within Derivative Works that You distribute, alongside
or as an addendum to the NOTICE text from the Work, provided
that such additional attribution notices cannot be construed
as modifying the License.
You may add Your own copyright statement to Your modifications and
may provide additional or different license terms and conditions
for use, reproduction, or distribution of Your modifications, or
for any such Derivative Works as a whole, provided Your use,
reproduction, and distribution of the Work otherwise complies with
the conditions stated in this License.
5. Submission of Contributions. Unless You explicitly state otherwise,
any Contribution intentionally submitted for inclusion in the Work
by You to the Licensor shall be under the terms and conditions of
this License, without any additional terms or conditions.
Notwithstanding the above, nothing herein shall supersede or modify
the terms of any separate license agreement you may have executed
with Licensor regarding such Contributions.
6. Trademarks. This License does not grant permission to use the trade
names, trademarks, service marks, or product names of the Licensor,
except as required for reasonable and customary use in describing the
origin of the Work and reproducing the content of the NOTICE file.
7. Disclaimer of Warranty. Unless required by applicable law or
agreed to in writing, Licensor provides the Work (and each
Contributor provides its Contributions) on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
implied, including, without limitation, any warranties or conditions
of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
PARTICULAR PURPOSE. You are solely responsible for determining the
appropriateness of using or redistributing the Work and assume any
risks associated with Your exercise of permissions under this License.
8. Limitation of Liability. In no event and under no legal theory,
whether in tort (including negligence), contract, or otherwise,
unless required by applicable law (such as deliberate and grossly
negligent acts) or agreed to in writing, shall any Contributor be
liable to You for damages, including any direct, indirect, special,
incidental, or consequential damages of any character arising as a
result of this License or out of the use or inability to use the
Work (including but not limited to damages for loss of goodwill,
work stoppage, computer failure or malfunction, or any and all
other commercial damages or losses), even if such Contributor
has been advised of the possibility of such damages.
9. Accepting Warranty or Additional Liability. While redistributing
the Work or Derivative Works thereof, You may choose to offer,
and charge a fee for, acceptance of support, warranty, indemnity,
or other liability obligations and/or rights consistent with this
License. However, in accepting such obligations, You may act only
on Your own behalf and on Your sole responsibility, not on behalf
of any other Contributor, and only if You agree to indemnify,
defend, and hold each Contributor harmless for any liability
incurred by, or claims asserted against, such Contributor by reason
of your accepting any such warranty or additional liability.
END OF TERMS AND CONDITIONS
APPENDIX: How to apply the Apache License to your work.
To apply the Apache License to your work, attach the following
boilerplate notice, with the fields enclosed by brackets "[]"
replaced with your own identifying information. (Don't include
the brackets!) The text should be enclosed in the appropriate
comment syntax for the file format. We also recommend that a
file or class name and description of purpose be included on the
same "printed page" as the copyright notice for easier
identification within third-party archives.
Copyright [yyyy] [name of copyright owner]
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
MANIFEST.in 0 → 100644
View file @ 4353fa59
include requirements/*.txt
include mmdeploy/backend/ncnn/*.so
include mmdeploy/backend/ncnn/*.dll
include mmdeploy/backend/ncnn/*.pyd
include mmdeploy/backend/ncnn/mmdeploy_onnx2ncnn*
include mmdeploy/lib/*.so
include mmdeploy/lib/*.so*
include mmdeploy/lib/*.dll
include mmdeploy/lib/*.pyd
include mmdeploy/backend/torchscript/*.so
include mmdeploy/backend/torchscript/*.dll
include mmdeploy/backend/torchscript/*.pyd
README.md 0 → 100644
View file @ 4353fa59
<div align="center">
<img src="resources/mmdeploy-logo.png" width="450"/>
<div>&nbsp;</div>
<div align="center">
<b><font size="5">OpenMMLab website</font></b>
<sup>
<a href="https://openmmlab.com">
<i><font size="4">HOT</font></i>
</a>
</sup>
&nbsp;&nbsp;&nbsp;&nbsp;
<b><font size="5">OpenMMLab platform</font></b>
<sup>
<a href="https://platform.openmmlab.com">
<i><font size="4">TRY IT OUT</font></i>
</a>
</sup>
</div>
<div>&nbsp;</div>
[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmdeploy.readthedocs.io/en/latest/)
[![badge](https://github.com/open-mmlab/mmdeploy/workflows/build/badge.svg)](https://github.com/open-mmlab/mmdeploy/actions)
[![codecov](https://codecov.io/gh/open-mmlab/mmdeploy/branch/main/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmdeploy)
[![license](https://img.shields.io/github/license/open-mmlab/mmdeploy.svg)](https://github.com/open-mmlab/mmdeploy/tree/main/LICENSE)
[![issue resolution](https://img.shields.io/github/issues-closed-raw/open-mmlab/mmdeploy)](https://github.com/open-mmlab/mmdeploy/issues)
[![open issues](https://img.shields.io/github/issues-raw/open-mmlab/mmdeploy)](https://github.com/open-mmlab/mmdeploy/issues)
English | [简体中文](README_zh-CN.md)
</div>
<div align="center">
<a href="https://openmmlab.medium.com/" style="text-decoration:none;">
<img src="https://user-images.githubusercontent.com/25839884/218352562-cdded397-b0f3-4ca1-b8dd-a60df8dca75b.png" width="3%" alt="" /></a>
<img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" />
<a href="https://discord.gg/raweFPmdzG" style="text-decoration:none;">
<img src="https://user-images.githubusercontent.com/25839884/218347213-c080267f-cbb6-443e-8532-8e1ed9a58ea9.png" width="3%" alt="" /></a>
<img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" />
<a href="https://twitter.com/OpenMMLab" style="text-decoration:none;">
<img src="https://user-images.githubusercontent.com/25839884/218346637-d30c8a0f-3eba-4699-8131-512fb06d46db.png" width="3%" alt="" /></a>
<img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" />
<a href="https://www.youtube.com/openmmlab" style="text-decoration:none;">
<img src="https://user-images.githubusercontent.com/25839884/218346691-ceb2116a-465a-40af-8424-9f30d2348ca9.png" width="3%" alt="" /></a>
</div>
## Highlights
The MMDeploy 1.x has been released, which is adapted to upstream codebases from OpenMMLab 2.0. Please **align the version** when using it.
The default branch has been switched to `main` from `master`. MMDeploy 0.x (`master`) will be deprecated and new features will only be added to MMDeploy 1.x (`main`) in future.
| mmdeploy | mmengine | mmcv | mmdet | others |
| :------: | :------: | :------: | :------: | :----: |
| 0.x.y | - | \<=1.x.y | \<=2.x.y | 0.x.y |
| 1.x.y | 0.x.y | 2.x.y | 3.x.y | 1.x.y |
[deploee](https://platform.openmmlab.com/deploee/) offers over 2,300 AI models in ONNX, NCNN, TRT and OpenVINO formats. Featuring a built-in list of real hardware devices, deploee enables users to convert Torch models into any target inference format for profiling purposes.
## Introduction
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the [OpenMMLab](https://openmmlab.com/) project.
<div align="center">
<img src="resources/introduction.png">
</div>
## Main features
### Fully support OpenMMLab models
The currently supported codebases and models are as follows, and more will be included in the future
- [mmpretrain](docs/en/04-supported-codebases/mmpretrain.md)
- [mmdet](docs/en/04-supported-codebases/mmdet.md)
- [mmseg](docs/en/04-supported-codebases/mmseg.md)
- [mmagic](docs/en/04-supported-codebases/mmagic.md)
- [mmocr](docs/en/04-supported-codebases/mmocr.md)
- [mmpose](docs/en/04-supported-codebases/mmpose.md)
- [mmdet3d](docs/en/04-supported-codebases/mmdet3d.md)
- [mmrotate](docs/en/04-supported-codebases/mmrotate.md)
- [mmaction2](docs/en/04-supported-codebases/mmaction2.md)
### Multiple inference backends are available
The supported Device-Platform-InferenceBackend matrix is presented as following, and more will be compatible.
The benchmark can be found from [here](docs/en/03-benchmark/benchmark.md)
<div style="width: fit-content; margin: auto;">
<table>
<tr>
<th>Device / <br> Platform</th>
<th>Linux</th>
<th>Windows</th>
<th>macOS</th>
<th>Android</th>
</tr>
<tr>
<th>x86_64 <br> CPU</th>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-ort.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-ort.yml"></a></sub> <sub>onnxruntime</sub> <br>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-pplnn.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-pplnn.yml"></a></sub> <sub>pplnn</sub> <br>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-ncnn.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-ncnn.yml"></a></sub> <sub>ncnn</sub> <br>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-torchscript.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-torchscript.yml"></a></sub> <sub>LibTorch</sub> <br>
<sub><img src="https://img.shields.io/badge/build-no%20status-lightgrey"></sub> <sub>OpenVINO</sub> <br>
<sub><img src="https://img.shields.io/badge/build-no%20status-lightgrey"></sub> <sub>TVM</sub> <br>
</td>
<td>
<sub><img src="https://img.shields.io/badge/build-no%20status-lightgrey"></sub> <sub>onnxruntime</sub> <br>
<sub><img src="https://img.shields.io/badge/build-no%20status-lightgrey"></sub> <sub>OpenVINO</sub> <br>
<sub><img src="https://img.shields.io/badge/build-no%20status-lightgrey"></sub> <sub>ncnn</sub> <br>
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
</tr>
<tr>
<th>ARM <br> CPU</th>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/build.yml"><img src="https://byob.yarr.is/open-mmlab/mmdeploy/cross_build_aarch64"></a></sub> <sub>ncnn</sub> <br>
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td align="center">
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-ncnn.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-ncnn.yml"></a></sub> <sub>ncnn</sub> <br>
</td>
</tr>
<tr>
<th>RISC-V</th>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/linux-riscv64-gcc.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/linux-riscv64-gcc.yml"></a></sub> <sub>ncnn</sub> <br>
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
</tr>
<tr>
<th>NVIDIA <br> GPU</th>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/build.yml"><img src="https://byob.yarr.is/open-mmlab/mmdeploy/build_cuda113_linux"></a></sub> <sub>onnxruntime</sub> <br>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/build.yml"><img src="https://byob.yarr.is/open-mmlab/mmdeploy/build_cuda113_linux"></a></sub> <sub>TensorRT</sub> <br>
<sub><img src="https://img.shields.io/badge/build-no%20status-lightgrey"></sub> <sub>LibTorch</sub> <br>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-pplnn.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-pplnn.yml"></a></sub> <sub>pplnn</sub> <br>
</td>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/build.yml"><img src="https://byob.yarr.is/open-mmlab/mmdeploy/build_cuda113_windows"></a></sub> <sub>onnxruntime</sub> <br>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/build.yml"><img src="https://byob.yarr.is/open-mmlab/mmdeploy/build_cuda113_windows"></a></sub> <sub>TensorRT</sub> <br>
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
</tr>
<tr>
<th>NVIDIA <br> Jetson</th>
<td>
<sub><img src="https://img.shields.io/badge/build-no%20status-lightgrey"></sub> <sub>TensorRT</sub> <br>
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
</tr>
<tr>
<th>Huawei <br> ascend310</th>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-ascend.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-ascend.yml"></a></sub> <sub>CANN</sub> <br>
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
</tr>
<tr>
<th>Rockchip</th>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-rknn.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-rknn.yml"></a></sub> <sub>RKNN</sub> <br>
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
</tr>
<tr>
<th>Apple M1</th>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-coreml.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-coreml.yml"></a></sub> <sub>CoreML</sub> <br>
</td>
<td align="center">
-
</td>
</tr>
<tr>
<th>Adreno <br> GPU</th>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-snpe.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-snpe.yml"></a></sub> <sub>SNPE</sub> <br>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-ncnn.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-ncnn.yml"></a></sub> <sub>ncnn</sub> <br>
</td>
</tr>
<tr>
<th>Hexagon <br> DSP</th>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-snpe.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-snpe.yml"></a></sub> <sub>SNPE</sub> <br>
</td>
</tr>
</table>
</div>
### Efficient and scalable C/C++ SDK Framework
All kinds of modules in the SDK can be extended, such as `Transform` for image processing, `Net` for Neural Network inference, `Module` for postprocessing and so on
## [Documentation](https://mmdeploy.readthedocs.io/en/latest/)
Please read [getting_started](docs/en/get_started.md) for the basic usage of MMDeploy. We also provide tutoials about:
- [Build](docs/en/01-how-to-build/build_from_source.md)
- [Build from Docker](docs/en/01-how-to-build/build_from_docker.md)
- [Build from Script](docs/en/01-how-to-build/build_from_script.md)
- [Build for Linux](docs/en/01-how-to-build/linux-x86_64.md)
- [Build for macOS](docs/en/01-how-to-build/macos-arm64.md)
- [Build for Win10](docs/en/01-how-to-build/windows.md)
- [Build for Android](docs/en/01-how-to-build/android.md)
- [Build for Jetson](docs/en/01-how-to-build/jetsons.md)
- [Build for SNPE](docs/en/01-how-to-build/snpe.md)
- [Cross Build for aarch64](docs/en/01-how-to-build/cross_build_ncnn_aarch64.md)
- User Guide
- [How to convert model](docs/en/02-how-to-run/convert_model.md)
- [How to write config](docs/en/02-how-to-run/write_config.md)
- [How to profile model](docs/en/02-how-to-run/profile_model.md)
- [How to quantize model](docs/en/02-how-to-run/quantize_model.md)
- [Useful tools](docs/en/02-how-to-run/useful_tools.md)
- Developer Guide
- [Architecture](docs/en/07-developer-guide/architecture.md)
- [How to support new models](docs/en/07-developer-guide/support_new_model.md)
- [How to support new backends](docs/en/07-developer-guide/support_new_backend.md)
- [How to partition model](docs/en/07-developer-guide/partition_model.md)
- [How to test rewritten model](docs/en/07-developer-guide/test_rewritten_models.md)
- [How to test backend ops](docs/en/07-developer-guide/add_backend_ops_unittest.md)
- [How to do regression test](docs/en/07-developer-guide/regression_test.md)
- Custom Backend Ops
- [ncnn](docs/en/06-custom-ops/ncnn.md)
- [ONNXRuntime](docs/en/06-custom-ops/onnxruntime.md)
- [tensorrt](docs/en/06-custom-ops/tensorrt.md)
- [FAQ](docs/en/faq.md)
- [Contributing](.github/CONTRIBUTING.md)
## Benchmark and Model zoo
You can find the supported models from [here](docs/en/03-benchmark/supported_models.md) and their performance in the [benchmark](docs/en/03-benchmark/benchmark.md).
## Contributing
We appreciate all contributions to MMDeploy. Please refer to [CONTRIBUTING.md](.github/CONTRIBUTING.md) for the contributing guideline.
## Acknowledgement
We would like to sincerely thank the following teams for their contributions to [MMDeploy](https://github.com/open-mmlab/mmdeploy):
- [OpenPPL](https://github.com/openppl-public)
- [OpenVINO](https://github.com/openvinotoolkit/openvino)
- [ncnn](https://github.com/Tencent/ncnn)
## Citation
If you find this project useful in your research, please consider citing:
```BibTeX
@misc{=mmdeploy,
title={OpenMMLab's Model Deployment Toolbox.},
author={MMDeploy Contributors},
howpublished = {\url{https://github.com/open-mmlab/mmdeploy}},
year={2021}
}
```
## License
This project is released under the [Apache 2.0 license](LICENSE).
## Projects in OpenMMLab
- [MMEngine](https://github.com/open-mmlab/mmengine): OpenMMLab foundational library for training deep learning models.
- [MMCV](https://github.com/open-mmlab/mmcv): OpenMMLab foundational library for computer vision.
- [MMPretrain](https://github.com/open-mmlab/mmpretrain): OpenMMLab pre-training toolbox and benchmark.
- [MMagic](https://github.com/open-mmlab/mmagic): Open**MM**Lab **A**dvanced, **G**enerative and **I**ntelligent **C**reation toolbox.
- [MMDetection](https://github.com/open-mmlab/mmdetection): OpenMMLab detection toolbox and benchmark.
- [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab's next-generation platform for general 3D object detection.
- [MMYOLO](https://github.com/open-mmlab/mmyolo): OpenMMLab YOLO series toolbox and benchmark
- [MMRotate](https://github.com/open-mmlab/mmrotate): OpenMMLab rotated object detection toolbox and benchmark.
- [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab video perception toolbox and benchmark.
- [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab semantic segmentation toolbox and benchmark.
- [MMOCR](https://github.com/open-mmlab/mmocr): OpenMMLab text detection, recognition, and understanding toolbox.
- [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab pose estimation toolbox and benchmark.
- [MMHuman3D](https://github.com/open-mmlab/mmhuman3d): OpenMMLab 3D human parametric model toolbox and benchmark.
- [MMFewShot](https://github.com/open-mmlab/mmfewshot): OpenMMLab fewshot learning toolbox and benchmark.
- [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab's next-generation action understanding toolbox and benchmark.
- [MMFlow](https://github.com/open-mmlab/mmflow): OpenMMLab optical flow toolbox and benchmark.
- [MMDeploy](https://github.com/open-mmlab/mmdeploy): OpenMMLab model deployment framework.
- [MMRazor](https://github.com/open-mmlab/mmrazor): OpenMMLab model compression toolbox and benchmark.
- [MIM](https://github.com/open-mmlab/mim): MIM installs OpenMMLab packages.
- [Playground](https://github.com/open-mmlab/playground): A central hub for gathering and showcasing amazing projects built upon OpenMMLab.
README_zh-CN.md 0 → 100644
View file @ 4353fa59
<div align="center">
<img src="resources/mmdeploy-logo.png" width="450"/>
<div>&nbsp;</div>
<div align="center">
<b><font size="5">OpenMMLab 官网</font></b>
<sup>
<a href="https://openmmlab.com">
<i><font size="4">HOT</font></i>
</a>
</sup>
&nbsp;&nbsp;&nbsp;&nbsp;
<b><font size="5">OpenMMLab 开放平台</font></b>
<sup>
<a href="https://platform.openmmlab.com">
<i><font size="4">TRY IT OUT</font></i>
</a>
</sup>
</div>
<div>&nbsp;</div>
</div>
[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmdeploy.readthedocs.io/zh_CN/latest/)
[![badge](https://github.com/open-mmlab/mmdeploy/workflows/build/badge.svg)](https://github.com/open-mmlab/mmdeploy/actions)
[![codecov](https://codecov.io/gh/open-mmlab/mmdeploy/branch/main/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmdeploy)
[![license](https://img.shields.io/github/license/open-mmlab/mmdeploy.svg)](https://github.com/open-mmlab/mmdeploy/tree/main/LICENSE)
[![issue resolution](https://img.shields.io/github/issues-closed-raw/open-mmlab/mmdeploy)](https://github.com/open-mmlab/mmdeploy/issues)
[![open issues](https://img.shields.io/github/issues-raw/open-mmlab/mmdeploy)](https://github.com/open-mmlab/mmdeploy/issues)
[English](README.md) | 简体中文
## MMDeploy 1.x 版本
全新的 MMDeploy 1.x 已发布，该版本适配OpenMMLab 2.0 生态体系，使用时务必**对齐版本**。
MMDeploy 代码库默认分支从`master`切换至`main`。 MMDeploy 0.x (`master`)将逐步废弃，新特性将只添加到 MMDeploy 1.x (`main`)。
| mmdeploy | mmengine | mmcv | mmdet | mmpretrain and others |
| :------: | :------: | :------: | :------: | :-------------------: |
| 0.x.y | - | \<=1.x.y | \<=2.x.y | 0.x.y |
| 1.x.y | 0.x.y | 2.x.y | 3.x.y | 1.x.y |
[硬件模型库](https://platform.openmmlab.com/deploee/) 使用 MMDeploy 1.x 版本转换了 2300 个 onnx/ncnn/trt/openvino 模型，可免费搜索下载。系统内置真实的服务端/嵌入式硬件，用户可以在线完成模型转和速度测试。
## 介绍
MMDeploy 是 [OpenMMLab](https://openmmlab.com/) 模型部署工具箱，**为各算法库提供统一的部署体验**。基于 MMDeploy，开发者可以轻松从训练 repo 生成指定硬件所需 SDK，省去大量适配时间。
## 架构简析
<div align="center">
<img src="resources/introduction.png"/>
</div>
## 特性简介
### 支持超多 OpenMMLab 算法库
- [mmpretrain](docs/zh_cn/04-supported-codebases/mmpretrain.md)
- [mmdet](docs/zh_cn/04-supported-codebases/mmdet.md)
- [mmseg](docs/zh_cn/04-supported-codebases/mmseg.md)
- [mmagic](docs/zh_cn/04-supported-codebases/mmagic.md)
- [mmocr](docs/zh_cn/04-supported-codebases/mmocr.md)
- [mmpose](docs/zh_cn/04-supported-codebases/mmpose.md)
- [mmdet3d](docs/zh_cn/04-supported-codebases/mmdet3d.md)
- [mmrotate](docs/zh_cn/04-supported-codebases/mmrotate.md)
- [mmaction2](docs/zh_cn/04-supported-codebases/mmaction2.md)
### 支持多种推理后端
支持的设备平台和推理引擎如下表所示。benchmark请参考[这里](docs/zh_cn/03-benchmark/benchmark.md)
<div style="width: fit-content; margin: auto;">
<table>
<tr>
<th>Device / <br> Platform</th>
<th>Linux</th>
<th>Windows</th>
<th>macOS</th>
<th>Android</th>
</tr>
<tr>
<th>x86_64 <br> CPU</th>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-ort.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-ort.yml"></a></sub> <sub>onnxruntime</sub> <br>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-pplnn.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-pplnn.yml"></a></sub> <sub>pplnn</sub> <br>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-ncnn.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-ncnn.yml"></a></sub> <sub>ncnn</sub> <br>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-torchscript.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-torchscript.yml"></a></sub> <sub>LibTorch</sub> <br>
<sub><img src="https://img.shields.io/badge/build-no%20status-lightgrey"></sub> <sub>OpenVINO</sub> <br>
<sub><img src="https://img.shields.io/badge/build-no%20status-lightgrey"></sub> <sub>TVM</sub> <br>
</td>
<td>
<sub><img src="https://img.shields.io/badge/build-no%20status-lightgrey"></sub> <sub>onnxruntime</sub> <br>
<sub><img src="https://img.shields.io/badge/build-no%20status-lightgrey"></sub> <sub>OpenVINO</sub> <br>
<sub><img src="https://img.shields.io/badge/build-no%20status-lightgrey"></sub> <sub>ncnn</sub> <br>
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
</tr>
<tr>
<th>ARM <br> CPU</th>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/build.yml"><img src="https://byob.yarr.is/open-mmlab/mmdeploy/cross_build_aarch64"></a></sub> <sub>ncnn</sub> <br>
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td align="center">
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-ncnn.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-ncnn.yml"></a></sub> <sub>ncnn</sub> <br>
</td>
</tr>
<tr>
<th>RISC-V</th>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/linux-riscv64-gcc.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/linux-riscv64-gcc.yml"></a></sub> <sub>ncnn</sub> <br>
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
</tr>
<tr>
<th>NVIDIA <br> GPU</th>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/build.yml"><img src="https://byob.yarr.is/open-mmlab/mmdeploy/build_cuda113_linux"></a></sub> <sub>onnxruntime</sub> <br>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/build.yml"><img src="https://byob.yarr.is/open-mmlab/mmdeploy/build_cuda113_linux"></a></sub> <sub>TensorRT</sub> <br>
<sub><img src="https://img.shields.io/badge/build-no%20status-lightgrey"></sub> <sub>LibTorch</sub> <br>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-pplnn.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-pplnn.yml"></a></sub> <sub>pplnn</sub> <br>
</td>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/build.yml"><img src="https://byob.yarr.is/open-mmlab/mmdeploy/build_cuda113_windows"></a></sub> <sub>onnxruntime</sub> <br>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/build.yml"><img src="https://byob.yarr.is/open-mmlab/mmdeploy/build_cuda113_windows"></a></sub> <sub>TensorRT</sub> <br>
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
</tr>
<tr>
<th>NVIDIA <br> Jetson</th>
<td>
<sub><img src="https://img.shields.io/badge/build-no%20status-lightgrey"></sub> <sub>TensorRT</sub> <br>
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
</tr>
<tr>
<th>Huawei <br> ascend310</th>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-ascend.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-ascend.yml"></a></sub> <sub>CANN</sub> <br>
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
</tr>
<tr>
<th>Rockchip</th>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-rknn.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-rknn.yml"></a></sub> <sub>RKNN</sub> <br>
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
</tr>
<tr>
<th>Apple M1</th>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-coreml.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-coreml.yml"></a></sub> <sub>CoreML</sub> <br>
</td>
<td align="center">
-
</td>
</tr>
<tr>
<th>Adreno <br> GPU</th>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-snpe.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-snpe.yml"></a></sub> <sub>SNPE</sub> <br>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-ncnn.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-ncnn.yml"></a></sub> <sub>ncnn</sub> <br>
</td>
</tr>
<tr>
<th>Hexagon <br> DSP</th>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td align="center">
-
</td>
<td>
<sub><a href="https://github.com/open-mmlab/mmdeploy/actions/workflows/backend-snpe.yml"><img src="https://img.shields.io/github/actions/workflow/status/open-mmlab/mmdeploy/backend-snpe.yml"></a></sub> <sub>SNPE</sub> <br>
</td>
</tr>
</table>
</div>
### SDK 可高度定制化
- Transform 数据预处理
- Net 推理
- Module 后处理
## [中文文档](https://mmdeploy.readthedocs.io/zh_CN/latest/)
- [快速上手](docs/zh_cn/get_started.md)
- [编译](docs/zh_cn/01-how-to-build/build_from_source.md)
- [一键式脚本安装](docs/zh_cn/01-how-to-build/build_from_script.md)
- [Build from Docker](docs/zh_cn/01-how-to-build/build_from_docker.md)
- [Build for Linux](docs/zh_cn/01-how-to-build/linux-x86_64.md)
- [Build for macOS](docs/zh_cn/01-how-to-build/macos-arm64.md)
- [Build for Win10](docs/zh_cn/01-how-to-build/windows.md)
- [Build for Android](docs/zh_cn/01-how-to-build/android.md)
- [Build for Jetson](docs/zh_cn/01-how-to-build/jetsons.md)
- [Build for SNPE](docs/zh_cn/01-how-to-build/snpe.md)
- [Cross Build for aarch64](docs/zh_cn/01-how-to-build/cross_build_ncnn_aarch64.md)
- 使用
- [把模型转换到推理 Backend](docs/zh_cn/02-how-to-run/convert_model.md)
- [配置转换参数](docs/zh_cn/02-how-to-run/write_config.md)
- [量化](docs/zh_cn/02-how-to-run/quantize_model.md)
- [测试转换完成的模型](docs/zh_cn/02-how-to-run/profile_model.md)
- [工具集介绍](docs/zh_cn/02-how-to-run/useful_tools.md)
- 开发指南
- [软件架构](docs/zh_cn/07-developer-guide/architecture.md)
- [支持新模型](docs/zh_cn/07-developer-guide/support_new_model.md)
- [增加推理 backend](docs/zh_cn/07-developer-guide/support_new_backend.md)
- [模型分块](docs/zh_cn/07-developer-guide/partition_model.md)
- [测试重写模型](docs/zh_cn/07-developer-guide/test_rewritten_models.md)
- [backend 算子测试](docs/zh_cn/07-developer-guide/add_backend_ops_unittest.md)
- [回归测试](docs/zh_cn/07-developer-guide/regression_test.md)
- 各 backend 自定义算子列表
- [ncnn](docs/zh_cn/06-custom-ops/ncnn.md)
- [onnxruntime](docs/zh_cn/06-custom-ops/onnxruntime.md)
- [tensorrt](docs/zh_cn/06-custom-ops/tensorrt.md)
- [FAQ](docs/zh_cn/faq.md)
- [贡献者手册](.github/CONTRIBUTING.md)
## 新人解说
- [01 术语解释、加载第一个模型](docs/zh_cn/tutorial/01_introduction_to_model_deployment.md)
- [02 部署常见问题](docs/zh_cn/tutorial/02_challenges.md)
- [03 torch转onnx](docs/zh_cn/tutorial/03_pytorch2onnx.md)
- [04 让torch支持更多onnx算子](docs/zh_cn/tutorial/04_onnx_custom_op.md)
- [05 调试onnx模型](docs/zh_cn/tutorial/05_onnx_model_editing.md)
## 基准与模型库
基准和支持的模型列表可以在[基准](https://mmdeploy.readthedocs.io/zh_CN/latest/03-benchmark/benchmark.html)和[模型列表](https://mmdeploy.readthedocs.io/en/latest/03-benchmark/supported_models.html)中获得。
## 贡献指南
我们感谢所有的贡献者为改进和提升 MMDeploy 所作出的努力。请参考[贡献指南](.github/CONTRIBUTING.md)来了解参与项目贡献的相关指引。
## 致谢
- [OpenPPL](https://github.com/openppl-public/ppl.nn): 高性能推理框架底层库
- [OpenVINO](https://github.com/openvinotoolkit/openvino): AI 推理优化和部署框架
- [ncnn](https://github.com/tencent/ncnn): 为手机端极致优化的高性能神经网络前向计算框架
## 引用
如果您在研究中使用了本项目的代码或者性能基准，请参考如下 bibtex 引用 MMDeploy:
```BibTeX
@misc{=mmdeploy,
title={OpenMMLab's Model Deployment Toolbox.},
author={MMDeploy Contributors},
howpublished = {\url{https://github.com/open-mmlab/mmdeploy}},
year={2021}
}
```
## 开源许可证
该项目采用 [Apache 2.0 开源许可证](LICENSE)。
## OpenMMLab 的其他项目
- [MMEngine](https://github.com/open-mmlab/mmengine): OpenMMLab 深度学习模型训练基础库
- [MMCV](https://github.com/open-mmlab/mmcv): OpenMMLab 计算机视觉基础库
- [MMPretrain](https://github.com/open-mmlab/mmpretrain): OpenMMLab 深度学习预训练工具箱
- [MMagic](https://github.com/open-mmlab/mmagic): OpenMMLab 新一代人工智能内容生成（AIGC）工具箱
- [MMDetection](https://github.com/open-mmlab/mmdetection): OpenMMLab 目标检测工具箱
- [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab 新一代通用 3D 目标检测平台
- [MMYOLO](https://github.com/open-mmlab/mmyolo): OpenMMLab YOLO 系列工具箱和基准测试
- [MMRotate](https://github.com/open-mmlab/mmrotate): OpenMMLab 旋转框检测工具箱与测试基准
- [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab 一体化视频目标感知平台
- [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab 语义分割工具箱
- [MMOCR](https://github.com/open-mmlab/mmocr): OpenMMLab 全流程文字检测识别理解工具包
- [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab 姿态估计工具箱
- [MMHuman3D](https://github.com/open-mmlab/mmhuman3d): OpenMMLab 人体参数化模型工具箱与测试基准
- [MMFewShot](https://github.com/open-mmlab/mmfewshot): OpenMMLab 少样本学习工具箱与测试基准
- [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab 新一代视频理解工具箱
- [MMFlow](https://github.com/open-mmlab/mmflow): OpenMMLab 光流估计工具箱与测试基准
- [MMDeploy](https://github.com/open-mmlab/mmdeploy): OpenMMLab 模型部署框架
- [MMRazor](https://github.com/open-mmlab/mmrazor): OpenMMLab 模型压缩工具箱与测试基准
- [MIM](https://github.com/open-mmlab/mim): OpenMMlab 项目、算法、模型的统一入口
- [Playground](https://github.com/open-mmlab/playground): 收集和展示 OpenMMLab 相关的前沿、有趣的社区项目
## 欢迎加入 OpenMMLab 社区
扫描下方的二维码可关注 OpenMMLab 团队的 [知乎官方账号](https://www.zhihu.com/people/openmmlab)，扫描下方微信二维码添加喵喵好友，进入 MMDeploy 微信交流社群。【加好友申请格式：研究方向+地区+学校/公司+姓名】
<div align="center">
<img src="https://user-images.githubusercontent.com/25839884/205870927-39f4946d-8751-4219-a4c0-740117558fd7.jpg" height="400" />
<img src="https://github.com/open-mmlab/mmdeploy/assets/62195058/a8f116ca-b567-42ce-b70e-38526a81c9a3" height="400" />
</div>
我们会在 OpenMMLab 社区为大家
- 📢 分享 AI 框架的前沿核心技术
- 💻 解读 PyTorch 常用模块源码
- 📰 发布 OpenMMLab 的相关新闻
- 🚀 介绍 OpenMMLab 开发的前沿算法
- 🏃 获取更高效的问题答疑和意见反馈
- 🔥 提供与各行各业开发者充分交流的平台
干货满满 📘，等您来撩 💗，OpenMMLab 社区期待您的加入 👬
docker/Base/Dockerfile 0 → 100644
View file @ 4353fa59
ARG CUDA_INT=118
FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu20.04 AS cuda-118
FROM nvidia/cuda:11.3.0-cudnn8-devel-ubuntu20.04 AS cuda-113
FROM cuda-${CUDA_INT} AS final
ARG TORCH_VERSION=2.0.0
ARG TORCHVISION_VERSION=0.15.1
# important dependencies
ARG OPENCV_VERSION==4.5.4.60
ARG PPLCV_VERSION=0.7.0
# backends
ARG ONNXRUNTIME_VERSION=1.15.1
ARG PPLNN_VERSION=0.8.1
ARG NCNN_VERSION=20230816
ARG TENSORRT_VERSION=8.6.1.6
ARG OPENVINO_VERSION=2022.3.0
# tensorrt tar file url
ARG TENSORRT_URL
USER root
WORKDIR /root/workspace
ENV DEBIAN_FRONTEND=nointeractive
ENV FORCE_CUDA="1"
RUN apt-get update && apt-get install -y --no-install-recommends \
apt-utils \
ca-certificates \
gcc-7 \
g++-7 \
git \
vim \
wget \
libopencv-dev \
libprotobuf-dev protobuf-compiler \
unzip \
python3-dev python3-pip \
&& rm -rf /var/lib/apt/lists/*
ENV CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda
ENV LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
# install jdk, onnxruntime, openvino, and other python packages
RUN wget https://download.java.net/java/GA/jdk18/43f95e8614114aeaa8e8a5fcf20a682d/36/GPL/openjdk-18_linux-x64_bin.tar.gz &&\
tar xvf openjdk-18_linux-x64_bin.tar.gz && rm -rf openjdk-18_linux-x64_bin.tar.gz && \
wget https://github.com/microsoft/onnxruntime/releases/download/v${ONNXRUNTIME_VERSION}/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz &&\
tar -xzvf onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz &&\
wget https://github.com/microsoft/onnxruntime/releases/download/v${ONNXRUNTIME_VERSION}/onnxruntime-linux-x64-gpu-${ONNXRUNTIME_VERSION}.tgz &&\
tar -xzvf onnxruntime-linux-x64-gpu-${ONNXRUNTIME_VERSION}.tgz && rm onnxruntime-*.tgz &&\
wget https://github.com/Kitware/CMake/releases/download/v3.25.2/cmake-3.25.2-linux-x86_64.tar.gz &&\
tar -xzvf cmake-3.25.2-linux-x86_64.tar.gz && rm cmake-*.tar.gz && mv cmake-* cmake &&\
export CUDA_INT=$(echo $CUDA_VERSION | awk '{split($0, a, "."); print a[1]a[2]}') &&\
python3 -m pip install --no-cache-dir --upgrade pip setuptools wheel &&\
python3 -m pip install --no-cache-dir onnxruntime-gpu==${ONNXRUNTIME_VERSION} &&\
python3 -m pip install --no-cache-dir openvino openvino-dev[onnx]==${OPENVINO_VERSION} &&\
python3 -m pip install --no-cache-dir opencv-python==${OPENCV_VERSION} opencv-python-headless==${OPENCV_VERSION} opencv-contrib-python==${OPENCV_VERSION} &&\
python3 -m pip install --no-cache-dir torch==${TORCH_VERSION}+cu${CUDA_INT} torchvision==${TORCHVISION_VERSION}+cu${CUDA_INT} -f https://download.pytorch.org/whl/torch_stable.html
# create env
ENV JAVA_HOME=/root/workspace/jdk-18
ENV PATH=$JAVA_HOME/bin:/root/workspace/cmake/bin:$PATH
ENV ONNXRUNTIME_DIR=/root/workspace/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}
ENV ONNXRUNTIME_GPU_DIR=/root/workspace/onnxruntime-linux-x64-gpu-${ONNXRUNTIME_VERSION}
ENV LD_LIBRARY_PATH=${ONNXRUNTIME_DIR}/lib:$LD_LIBRARY_PATH
### install ppl.nn
RUN git clone --depth 1 --branch v${PPLNN_VERSION} --recursive https://github.com/openppl-public/ppl.nn.git &&\
cd ppl.nn &&\
export PYTHON_INCLUDE_DIR=$(python3 -c 'import sysconfig;print(sysconfig.get_paths()["include"])') &&\
./build.sh -DPPLNN_USE_X86_64=ON -DPPLNN_USE_CUDA=ON -DPPLNN_ENABLE_PYTHON_API=ON -DPYTHON3_INCLUDE_DIRS=${PYTHON_INCLUDE_DIR} &&\
cd ./python/package && \
./build.sh && \
cd - && mv pplnn-build/install ./ && rm -rf pplnn-build &&\
cd /tmp/pyppl-package/dist && \
python3 -m pip install pyppl*.whl && rm *.whl
ENV pplnn_DIR=/root/workspace/ppl.nn/install/lib/cmake/ppl
ENV PYTHONPATH=/root/workspace/ppl.nn/install/lib:$PYTHONPATH
### build ncnn
RUN git clone --depth 1 --branch ${NCNN_VERSION} --recursive https://github.com/Tencent/ncnn.git &&\
python3 -m pip install pybind11 &&\
mkdir ncnn/build && cd ncnn/build &&\
cmake -DNCNN_VULKAN=OFF -DNCNN_PYTHON=ON -DNCNN_BUILD_TOOLS=OFF -DCMAKE_INSTALL_PREFIX=../install .. &&\
make -j $(nproc) && make install &&\
cd .. && python3 -m pip install . && rm -rf ./build
ENV ncnn_DIR=/root/workspace/ncnn/install/lib/cmake/ncnn
### install ppl.cv
RUN git clone --depth 1 --branch v${PPLCV_VERSION} https://github.com/openppl-public/ppl.cv.git &&\
cd ppl.cv &&\
./build.sh cuda && mv cuda-build/install ./ && rm -rf cuda-build
ENV pplcv_DIR=/root/workspace/ppl.cv/install/lib/cmake/ppl
### install tensorrt
RUN wget -c $TENSORRT_URL && \
tar -zxvf /root/workspace/TensorRT-${TENSORRT_VERSION}*.tar.gz -C /root/workspace &&\
rm -rf TensorRT-${TENSORRT_VERSION}*.tar.gz &&\
ln -sf /root/workspace/TensorRT-${TENSORRT_VERSION} /root/workspace/TensorRT &&\
cd /root/workspace/TensorRT && rm -rf data doc samples uff &&\
export PY_VERSION=$(python3 -V | awk '{print $2}' | awk '{split($0, a, "."); print a[1]a[2]}') &&\
python3 -m pip install ./python/tensorrt-*-cp${PY_VERSION}-none-linux_x86_64.whl
ENV TENSORRT_DIR=/root/workspace/TensorRT
ENV LD_LIBRARY_PATH=$TENSORRT_DIR/lib:$LD_LIBRARY_PATH
ENV PATH=$TENSORRT_DIR/bin:$PATH
# openvino
RUN wget https://storage.openvinotoolkit.org/repositories/openvino/packages/2022.3/linux/l_openvino_toolkit_ubuntu20_2022.3.0.9052.9752fafe8eb_x86_64.tgz &&\
tar -zxvf ./l_openvino_toolkit*.tgz &&\
rm ./l_openvino_toolkit*.tgz &&\
mv ./l_openvino* ./openvino_toolkit &&\
bash ./openvino_toolkit/install_dependencies/install_openvino_dependencies.sh
ENV OPENVINO_DIR=/root/workspace/openvino_toolkit
ENV InferenceEngine_DIR=$OPENVINO_DIR/runtime/cmake
docker/CPU/Dockerfile 0 → 100644
View file @ 4353fa59
FROM openvino/ubuntu20_dev:2022.3.0
ARG PYTHON_VERSION=3.8
ARG TORCH_VERSION=1.10.0
ARG TORCHVISION_VERSION=0.11.0
ARG ONNXRUNTIME_VERSION=1.8.1
ARG MMCV_VERSION=">=2.0.0rc2"
ARG MMENGINE_VERSION=">=0.3.0"
USER root
### change the system source for installing libs
ARG USE_SRC_INSIDE=false
RUN if [ ${USE_SRC_INSIDE} == true ] ; \
then \
sed -i s/archive.ubuntu.com/mirrors.aliyun.com/g /etc/apt/sources.list ; \
sed -i s/security.ubuntu.com/mirrors.aliyun.com/g /etc/apt/sources.list ; \
echo "Use aliyun source for installing libs" ; \
else \
echo "Keep the download source unchanged" ; \
fi
RUN apt-get update && apt-get install -y --no-install-recommends \
ca-certificates \
libopencv-dev libspdlog-dev \
gnupg \
libssl-dev \
libprotobuf-dev protobuf-compiler \
build-essential \
libjpeg-dev \
libpng-dev \
ccache \
cmake \
gcc \
g++ \
git \
vim \
wget \
curl \
&& rm -rf /var/lib/apt/lists/*
RUN curl -fsSL -v -o ~/miniconda.sh -O https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
chmod +x ~/miniconda.sh && \
bash ~/miniconda.sh -b -p /opt/conda && \
rm ~/miniconda.sh && \
/opt/conda/bin/conda install -y python=${PYTHON_VERSION} conda-build pyyaml numpy ipython cython typing typing_extensions mkl mkl-include ninja && \
/opt/conda/bin/conda clean -ya
### change the pip source for installing packages
RUN if [ ${USE_SRC_INSIDE} == true ] ; \
then \
/opt/conda/bin/pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple; \
echo "pip using tsinghua source" ; \
else \
echo "Keep pip the download source unchanged" ; \
fi
### pytorch mmcv onnxruntime and openvino
RUN /opt/conda/bin/pip install torch==${TORCH_VERSION}+cpu torchvision==${TORCHVISION_VERSION}+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html \
&& /opt/conda/bin/pip install --no-cache-dir openmim
RUN /opt/conda/bin/mim install --no-cache-dir "mmcv"${MMCV_VERSION} onnxruntime==${ONNXRUNTIME_VERSION} openvino-dev==2022.3.0 mmengine${MMENGINE_VERSION}
ENV PATH /opt/conda/bin:$PATH
WORKDIR /root/workspace
### get onnxruntime
RUN wget https://github.com/microsoft/onnxruntime/releases/download/v${ONNXRUNTIME_VERSION}/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz \
&& tar -zxvf onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz
ENV ONNXRUNTIME_DIR=/root/workspace/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}
### build ncnn
RUN git clone https://github.com/Tencent/ncnn.git &&\
cd ncnn &&\
export NCNN_DIR=$(pwd) &&\
git submodule update --init &&\
mkdir -p build && cd build &&\
cmake -DNCNN_VULKAN=OFF -DNCNN_SYSTEM_GLSLANG=ON -DNCNN_BUILD_EXAMPLES=ON -DNCNN_PYTHON=ON -DNCNN_BUILD_TOOLS=ON -DNCNN_BUILD_BENCHMARK=ON -DNCNN_BUILD_TESTS=ON .. &&\
make -j$(nproc) &&\
make install &&\
cd /root/workspace/ncnn/python &&\
/opt/conda/bin/mim install -e .
ENV PATH="/root/workspace/ncnn/build/tools/quantize/:${PATH}"
### install mmdeploy
WORKDIR /root/workspace
ARG VERSION
RUN git clone -b main https://github.com/open-mmlab/mmdeploy.git &&\
cd mmdeploy &&\
if [ -z ${VERSION} ] ; then echo "No MMDeploy version passed in, building on main" ; else git checkout tags/v${VERSION} -b tag_v${VERSION} ; fi &&\
git submodule update --init --recursive &&\
rm -rf build &&\
mkdir build &&\
cd build &&\
cmake -DMMDEPLOY_TARGET_BACKENDS=ncnn -Dncnn_DIR=/root/workspace/ncnn/build/install/lib/cmake/ncnn .. &&\
make -j$(nproc) &&\
cmake -DMMDEPLOY_TARGET_BACKENDS=ort .. &&\
make -j$(nproc) &&\
cd .. &&\
/opt/conda/bin/mim install -e .
### build SDK
ENV LD_LIBRARY_PATH="/root/workspace/mmdeploy/build/lib:${LD_LIBRARY_PATH}"
RUN cd mmdeploy && rm -rf build/CM* && mkdir -p build && cd build && cmake .. \
-DMMDEPLOY_BUILD_SDK=ON \
-DMMDEPLOY_BUILD_EXAMPLES=ON \
-DCMAKE_CXX_COMPILER=g++-9 \
-DONNXRUNTIME_DIR=${ONNXRUNTIME_DIR} \
-Dncnn_DIR=/root/workspace/ncnn/build/install/lib/cmake/ncnn \
-DInferenceEngine_DIR=/opt/intel/openvino/runtime/cmake \
-DMMDEPLOY_TARGET_DEVICES=cpu \
-DMMDEPLOY_BUILD_SDK_PYTHON_API=ON \
-DMMDEPLOY_TARGET_BACKENDS="ort;ncnn;openvino" \
-DMMDEPLOY_CODEBASES=all &&\
cmake --build . -- -j$(nproc) && cmake --install . &&\
export SPDLOG_LEVEL=warn &&\
if [ -z ${VERSION} ] ; then echo "Built MMDeploy main for CPU devices successfully!" ; else echo "Built MMDeploy version v${VERSION} for CPU devices successfully!" ; fi
docker/GPU/Dockerfile 0 → 100644
View file @ 4353fa59
FROM nvcr.io/nvidia/tensorrt:22.04-py3
ARG CUDA=11.3
ARG PYTHON_VERSION=3.8
ARG TORCH_VERSION=1.10.0
ARG TORCHVISION_VERSION=0.11.0
ARG ONNXRUNTIME_VERSION=1.8.1
ARG PPLCV_VERSION=0.7.0
ENV FORCE_CUDA="1"
ARG MMCV_VERSION=">=2.0.0rc2"
ARG MMENGINE_VERSION=">=0.3.0"
ENV DEBIAN_FRONTEND=noninteractive
### change the system source for installing libs
ARG USE_SRC_INSIDE=false
RUN if [ ${USE_SRC_INSIDE} == true ] ; \
then \
sed -i s/archive.ubuntu.com/mirrors.aliyun.com/g /etc/apt/sources.list ; \
sed -i s/security.ubuntu.com/mirrors.aliyun.com/g /etc/apt/sources.list ; \
echo "Use aliyun source for installing libs" ; \
else \
echo "Keep the download source unchanged" ; \
fi
### update apt and install libs
RUN apt-get update &&\
apt-get install -y vim libsm6 libxext6 libxrender-dev libgl1-mesa-glx git wget libssl-dev libopencv-dev libspdlog-dev --no-install-recommends &&\
rm -rf /var/lib/apt/lists/*
RUN curl -fsSL -v -o ~/miniconda.sh -O https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
chmod +x ~/miniconda.sh && \
bash ~/miniconda.sh -b -p /opt/conda && \
rm ~/miniconda.sh && \
/opt/conda/bin/conda install -y python=${PYTHON_VERSION} conda-build pyyaml numpy ipython cython typing typing_extensions mkl mkl-include ninja && \
/opt/conda/bin/conda clean -ya
### change the pip source for installing packages
RUN if [ ${USE_SRC_INSIDE} == true ] ; \
then \
/opt/conda/bin/pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple; \
echo "pip using tsinghua source" ; \
else \
echo "Keep pip the download source unchanged" ; \
fi
### install pytorch openmim
RUN /opt/conda/bin/conda install pytorch==${TORCH_VERSION} torchvision==${TORCHVISION_VERSION} cudatoolkit=${CUDA} -c pytorch -c conda-forge -y \
&& /opt/conda/bin/pip install --no-cache-dir openmim
### pytorch mmcv onnxruntime
RUN /opt/conda/bin/mim install --no-cache-dir "mmcv"${MMCV_VERSION} onnxruntime-gpu==${ONNXRUNTIME_VERSION} mmengine${MMENGINE_VERSION}
ENV PATH /opt/conda/bin:$PATH
WORKDIR /root/workspace
### get onnxruntime
RUN wget https://github.com/microsoft/onnxruntime/releases/download/v${ONNXRUNTIME_VERSION}/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz \
&& tar -zxvf onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz
### cp trt from pip to conda
RUN cp -r /usr/local/lib/python${PYTHON_VERSION}/dist-packages/tensorrt* /opt/conda/lib/python${PYTHON_VERSION}/site-packages/
### install mmdeploy
ENV ONNXRUNTIME_DIR=/root/workspace/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}
ENV TENSORRT_DIR=/workspace/tensorrt
ARG VERSION
RUN git clone -b main https://github.com/open-mmlab/mmdeploy &&\
cd mmdeploy &&\
if [ -z ${VERSION} ] ; then echo "No MMDeploy version passed in, building on main" ; else git checkout tags/v${VERSION} -b tag_v${VERSION} ; fi &&\
git submodule update --init --recursive &&\
mkdir -p build &&\
cd build &&\
cmake -DMMDEPLOY_TARGET_BACKENDS="ort;trt" .. &&\
make -j$(nproc) &&\
cd .. &&\
/opt/conda/bin/mim install -e .
### build sdk
RUN git clone https://github.com/openppl-public/ppl.cv.git &&\
cd ppl.cv &&\
git checkout tags/v${PPLCV_VERSION} -b v${PPLCV_VERSION} &&\
./build.sh cuda
ENV BACKUP_LD_LIBRARY_PATH=$LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/cuda/compat/lib.real/:$LD_LIBRARY_PATH
RUN cd /root/workspace/mmdeploy &&\
rm -rf build/CM* build/cmake-install.cmake build/Makefile build/csrc &&\
mkdir -p build && cd build &&\
cmake .. \
-DMMDEPLOY_BUILD_SDK=ON \
-DMMDEPLOY_BUILD_EXAMPLES=ON \
-DCMAKE_CXX_COMPILER=g++ \
-Dpplcv_DIR=/root/workspace/ppl.cv/cuda-build/install/lib/cmake/ppl \
-DTENSORRT_DIR=${TENSORRT_DIR} \
-DONNXRUNTIME_DIR=${ONNXRUNTIME_DIR} \
-DMMDEPLOY_BUILD_SDK_PYTHON_API=ON \
-DMMDEPLOY_TARGET_DEVICES="cuda;cpu" \
-DMMDEPLOY_TARGET_BACKENDS="ort;trt" \
-DMMDEPLOY_CODEBASES=all &&\
make -j$(nproc) && make install &&\
export SPDLOG_LEVEL=warn &&\
if [ -z ${VERSION} ] ; then echo "Built MMDeploy for GPU devices successfully!" ; else echo "Built MMDeploy version v${VERSION} for GPU devices successfully!" ; fi
ENV LD_LIBRARY_PATH="/root/workspace/mmdeploy/build/lib:${BACKUP_LD_LIBRARY_PATH}"
docker/Release/Dockerfile 0 → 100644
View file @ 4353fa59
FROM openmmlab/mmdeploy:ubuntu20.04-cuda11.8
ARG MMDEPLOY_VERSION=main
ENV BACKUP_LD_LIBRARY_PATH=$LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/cuda/compat:$LD_LIBRARY_PATH
# build mmdeploy
RUN git clone --recursive -b $MMDEPLOY_VERSION --depth 1 https://github.com/open-mmlab/mmdeploy.git &&\
export Torch_DIR=$(python3 -c "import torch;print(torch.utils.cmake_prefix_path + '/Torch')") &&\
bash mmdeploy/.github/scripts/linux/build.sh "cpu;cuda" "ort;trt;ncnn;torchscript;openvino" \
-DMMDEPLOY_BUILD_EXAMPLES=ON \
-Dpplcv_DIR=${pplcv_DIR} \
-DTENSORRT_DIR=${TENSORRT_DIR} \
-DInferenceEngine_DIR=${InferenceEngine_DIR} \
-DONNXRUNTIME_DIR=${ONNXRUNTIME_DIR} \
-Dncnn_DIR=${ncnn_DIR} \
-DTorch_DIR=${Torch_DIR} &&\
cd mmdeploy &&\
python3 -m pip install -U openmim pycuda &&\
python3 -m mim install "mmcv>=2.0.0" &&\
python3 -m pip install -r requirements.txt &&\
python3 -m pip install -e . --user
ENV MMDeploy_DIR="/root/workspace/mmdeploy/build/install/lib/cmake/MMDeploy"
ENV LD_LIBRARY_PATH="/root/workspace/mmdeploy/build/lib:${BACKUP_LD_LIBRARY_PATH}"
ENV PATH="/root/workspace/mmdeploy/build/bin:${PATH}"
ENV PYTHONPATH="/root/workspace/mmdeploy/build/lib:${PYTHONPATH}"
docker/prebuild/Dockerfile 0 → 100644
View file @ 4353fa59
FROM quay.io/pypa/manylinux2014_x86_64
# package urls
ARG CUDA_URL
ARG CUDNN_URL
ARG TENSORRT_URL
ARG CUDA_VERSION=11.8
# important dependencies
ARG OPENCV_VERSION=4.5.5
ARG PPLCV_VERSION=0.7.0
# backends
ARG ONNXRUNTIME_VERSION=1.15.1
ARG TENSORRT_VERSION=8.6.1.6
# torch
ARG TORCH_VERSION=2.0.0
ARG TORCHVISION_VERSION=0.15.0
ARG TOOLSET_VERSION=7
USER root
WORKDIR /root/workspace
ENV FORCE_CUDA="1"
# install toolset
RUN yum install centos-release-scl devtoolset-${TOOLSET_VERSION}-gcc* -y
ENV TOOLSET_DIR=/opt/rh/devtoolset-${TOOLSET_VERSION}/root/usr
ENV PATH=$TOOLSET_DIR/bin:$PATH
ENV LD_LIBRARY_PATH=$TOOLSET_DIR/lib:$TOOLSET_DIR/lib64:/usr/local/lib64
# install cuda cudnn
RUN curl -fsSL -v -o ./cuda_install.run -O $CUDA_URL &&\
chmod +x ./cuda_install.run &&\
./cuda_install.run --silent --toolkit &&\
rm -f ./cuda_install.run &&\
curl -fsSL -v -o ./cudnn.tgz -O $CUDNN_URL &&\
tar -xzvf ./cudnn.tgz &&\
rm -f ./cudnn.tgz &&\
mv cu* /opt/cudnn
# install ort, trt
RUN curl -fsSL -v -o ./onnxruntime.tgz -O https://github.com/microsoft/onnxruntime/releases/download/v${ONNXRUNTIME_VERSION}/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz &&\
tar -xzvf onnxruntime.tgz &&\
rm onnxruntime.tgz &&\
mv onnxruntime* /opt/onnxruntime &&\
curl -fsSL -v -o ./onnxruntime.tgz -O https://github.com/microsoft/onnxruntime/releases/download/v${ONNXRUNTIME_VERSION}/onnxruntime-linux-x64-gpu-${ONNXRUNTIME_VERSION}.tgz &&\
tar -xzvf onnxruntime.tgz &&\
rm onnxruntime.tgz &&\
mv onnxruntime* /opt/onnxruntime-gpu &&\
curl -fsSL -v -o ./tensorrt.tgz -O $TENSORRT_URL &&\
tar -xzvf ./tensorrt.tgz &&\
rm -f ./tensorrt.tgz &&\
mv ./TensorRT* /opt/TensorRT &&\
cd /opt/TensorRT &&\
rm -rf data doc samples uff
ENV CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda
ENV CUDNN_DIR=/opt/cudnn
ENV ONNXRUNTIME_DIR=/opt/onnxruntime
ENV ONNXRUNTIME_GPU_DIR=/opt/onnxruntime-gpu
ENV TENSORRT_DIR=/opt/TensorRT
ENV LD_LIBRARY_PATH=$CUDA_TOOLKIT_ROOT_DIR/lib64:$CUDNN_DIR/lib64:$LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=${ONNXRUNTIME_GPU_DIR}/lib:$TENSORRT_DIR/lib:$LD_LIBRARY_PATH
ENV PATH=$TENSORRT_DIR/bin:$PATH
### install ppl.cv
RUN git clone --depth 1 --branch v${PPLCV_VERSION} https://github.com/openppl-public/ppl.cv.git &&\
cd ppl.cv &&\
./build.sh cuda &&\
mv cuda-build/install ./ &&\
rm -rf cuda-build
ENV pplcv_DIR=/root/workspace/ppl.cv/install/lib/cmake/ppl
# build opencv as static lib
RUN curl -fsSL -v -o ./opencv.tgz -O https://github.com/opencv/opencv/archive/refs/tags/${OPENCV_VERSION}.tar.gz &&\
tar -xzvf ./opencv.tgz &&\
rm -f ./opencv.tgz &&\
cd opencv-${OPENCV_VERSION} &&\
mkdir build && cd build &&\
cmake .. \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_INSTALL_PREFIX=/usr/local \
-DOPENCV_FORCE_3RDPARTY_BUILD=ON \
-DBUILD_TESTS=OFF \
-DBUILD_PERF_TESTS=OFF \
-DBUILD_SHARED_LIBS=OFF &&\
make -j$(nproc) && make install
ENV OpenCV_DIR=/usr/local/lib64/cmake/opencv4
# install conda env
RUN curl -fsSL -v -o ~/miniconda.sh -O https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh &&\
chmod +x ~/miniconda.sh &&\
bash ~/miniconda.sh -b -p /opt/conda &&\
rm ~/miniconda.sh &&\
/opt/conda/bin/conda create -n mmdeploy-3.6 python=3.6 -y &&\
/opt/conda/bin/conda create -n mmdeploy-3.7 python=3.7 -y &&\
/opt/conda/bin/conda create -n mmdeploy-3.8 python=3.8 -y &&\
/opt/conda/bin/conda create -n mmdeploy-3.9 python=3.9 -y &&\
/opt/conda/bin/conda create -n mmdeploy-3.10 python=3.10 -y &&\
/opt/conda/bin/conda create -n mmdeploy-3.11 python=3.11 -y &&\
export CUDA_INT=$(echo $CUDA_VERSION | awk '{split($0, a, "."); print a[1]a[2]}') &&\
/opt/conda/bin/conda create -n torch${TORCH_VERSION} python=3.8 -y &&\
/opt/conda/envs/mmdeploy-3.6/bin/pip install --no-cache-dir setuptools wheel pyyaml packaging &&\
/opt/conda/envs/torch${TORCH_VERSION}/bin/pip install --no-cache-dir onnxruntime-gpu==${ONNXRUNTIME_VERSION} &&\
/opt/conda/envs/torch${TORCH_VERSION}/bin/pip install ${TENSORRT_DIR}/python/tensorrt-*-cp38-none-linux_x86_64.whl &&\
/opt/conda/envs/torch${TORCH_VERSION}/bin/pip install --no-cache-dir torch==${TORCH_VERSION}+cu${CUDA_INT} \
torchvision==${TORCHVISION_VERSION}+cu${CUDA_INT} -f https://download.pytorch.org/whl/torch_stable.html &&\
/opt/conda/bin/conda init bash &&\
/opt/conda/bin/conda clean -ya
ENV CONDA=/opt/conda
ENV PATH=$CONDA/bin:$PATH
docker/prebuild/Dockerfile.cxx11abi 0 → 100644
View file @ 4353fa59
FROM nvidia/cuda:11.3.1-cudnn8-devel-ubuntu16.04
ARG CUDA_URL
ARG CUDNN_URL
ARG TENSORRT_URL
ARG CUDA_VERSION=11.8
ARG OPENCV_VERSION=4.5.5
ARG PPLCV_VERSION=0.7.0
ARG TENSORRT_VERSION=8.6.1.6
ARG ONNXRUNTIME_VERSION=1.15.1
USER root
ENV WORK_DIR=/root/workspace
WORKDIR $WORK_DIR
RUN apt-get update && apt-get install software-properties-common -y &&\
add-apt-repository ppa:git-core/ppa -y &&\
add-apt-repository ppa:ubuntu-toolchain-r/test -y &&\
apt-get update && apt-get install git wget curl g++-7 -y &&\
update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-7 10 &&\
update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-7 10 &&\
apt-get clean
RUN wget https://github.com/Kitware/CMake/releases/download/v3.25.3/cmake-3.25.3-linux-x86_64.sh &&\
bash cmake-3.25.3-linux-x86_64.sh --skip-license --prefix=/usr &&\
rm -rf cmake-3.25.3-linux-x86_64.sh
# install cuda cudnn
RUN curl -fsSL -v -o ./cuda_install.run -O $CUDA_URL &&\
chmod +x ./cuda_install.run &&\
./cuda_install.run --silent --toolkit &&\
rm -f ./cuda_install.run &&\
curl -fsSL -v -o ./cudnn.tgz -O $CUDNN_URL &&\
tar -xvf ./cudnn.tgz &&\
rm -f ./cudnn.tgz &&\
mv cu* /opt/cudnn
# install ort, trt
RUN curl -fsSL -v -o ./onnxruntime.tgz -O https://github.com/microsoft/onnxruntime/releases/download/v${ONNXRUNTIME_VERSION}/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz &&\
tar -xzvf onnxruntime.tgz &&\
rm onnxruntime.tgz &&\
mv onnxruntime* /opt/onnxruntime &&\
curl -fsSL -v -o ./onnxruntime.tgz -O https://github.com/microsoft/onnxruntime/releases/download/v${ONNXRUNTIME_VERSION}/onnxruntime-linux-x64-gpu-${ONNXRUNTIME_VERSION}.tgz &&\
tar -xzvf onnxruntime.tgz &&\
rm onnxruntime.tgz &&\
mv onnxruntime* /opt/onnxruntime-gpu &&\
curl -fsSL -v -o ./tensorrt.tgz -O $TENSORRT_URL &&\
tar -xzvf ./tensorrt.tgz &&\
rm -f ./tensorrt.tgz &&\
mv ./TensorRT* /opt/TensorRT &&\
cd /opt/TensorRT &&\
rm -rf data doc samples uff
ENV CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-${CUDA_VERSION}
ENV CUDNN_DIR=/opt/cudnn
ENV ONNXRUNTIME_DIR=/opt/onnxruntime
ENV ONNXRUNTIME_GPU_DIR=/opt/onnxruntime-gpu
ENV TENSORRT_DIR=/opt/TensorRT
ENV LD_LIBRARY_PATH=$CUDA_TOOLKIT_ROOT_DIR/lib64:$CUDNN_DIR/lib64:$LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=${ONNXRUNTIME_GPU_DIR}/lib:$TENSORRT_DIR/lib:$LD_LIBRARY_PATH
ENV PATH=$TENSORRT_DIR/bin:$PATH
RUN wget https://github.com/opencv/opencv/archive/refs/tags/${OPENCV_VERSION}.tar.gz -O ./opencv.tgz &&\
tar -xzvf ./opencv.tgz &&\
rm -f ./opencv.tgz &&\
cd opencv-${OPENCV_VERSION} &&\
mkdir build && cd build &&\
cmake .. \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_INSTALL_PREFIX=../install \
-DOPENCV_FORCE_3RDPARTY_BUILD=ON \
-DBUILD_TESTS=OFF \
-DBUILD_PERF_TESTS=OFF \
-DBUILD_opencv_python2=OFF \
-DBUILD_opencv_python3=OFF \
-DBUILD_SHARED_LIBS=OFF &&\
make -j$(nproc) && make install &&\
cd ../ && rm -rf build
ENV OpenCV_DIR=/root/workspace/opencv-${OPENCV_VERSION}/install/lib/cmake/opencv4
RUN git clone --depth 1 --branch v${PPLCV_VERSION} https://github.com/openppl-public/ppl.cv.git &&\
cd ppl.cv &&\
./build.sh cuda &&\
mv cuda-build/install ./ &&\
rm -rf cuda-build
ENV pplcv_DIR=/root/workspace/ppl.cv/install/lib/cmake/ppl
RUN wget https://repo.anaconda.com/miniconda/Miniconda3-py38_23.1.0-1-Linux-x86_64.sh -O ~/miniconda.sh &&\
chmod +x ~/miniconda.sh &&\
bash ~/miniconda.sh -b -p /opt/conda &&\
rm ~/miniconda.sh
ENV PATH=/opt/conda/bin:$PATH
RUN pip install packaging pyyaml
ENTRYPOINT ["/bin/bash"]
docs/cppapi/Doxyfile 0 → 100644
View file @ 4353fa59
# Doxyfile 1.9.7
# This file describes the settings to be used by the documentation system
# doxygen (www.doxygen.org) for a project.
#
# All text after a double hash (##) is considered a comment and is placed in
# front of the TAG it is preceding.
#
# All text after a single hash (#) is considered a comment and will be ignored.
# The format is:
# TAG = value [value, ...]
# For lists, items can also be appended using:
# TAG += value [value, ...]
# Values that contain spaces should be placed between quotes (\" \").
#
# Note:
#
# Use doxygen to compare the used configuration file with the template
# configuration file:
# doxygen -x [configFile]
# Use doxygen to compare the used configuration file with the template
# configuration file without replacing the environment variables or CMake type
# replacement variables:
# doxygen -x_noenv [configFile]
#---------------------------------------------------------------------------
# Project related configuration options
#---------------------------------------------------------------------------
# This tag specifies the encoding used for all characters in the configuration
# file that follow. The default is UTF-8 which is also the encoding used for all
# text before the first occurrence of this tag. Doxygen uses libiconv (or the
# iconv built into libc) for the transcoding. See
# https://www.gnu.org/software/libiconv/ for the list of possible encodings.
# The default value is: UTF-8.
DOXYFILE_ENCODING = UTF-8
# The PROJECT_NAME tag is a single word (or a sequence of words surrounded by
# double-quotes, unless you are using Doxywizard) that should identify the
# project for which the documentation is generated. This name is used in the
# title of most generated pages and in a few other places.
# The default value is: My Project.
PROJECT_NAME = MMDeploy
# The PROJECT_NUMBER tag can be used to enter a project or revision number. This
# could be handy for archiving the generated documentation or if some version
# control system is used.
PROJECT_NUMBER = latest
# Using the PROJECT_BRIEF tag one can provide an optional one line description
# for a project that appears at the top of each page and should give viewer a
# quick idea about the purpose of the project. Keep the description short.
PROJECT_BRIEF =
# With the PROJECT_LOGO tag one can specify a logo or an icon that is included
# in the documentation. The maximum height of the logo should not exceed 55
# pixels and the maximum width should not exceed 200 pixels. Doxygen will copy
# the logo to the output directory.
PROJECT_LOGO =
# The OUTPUT_DIRECTORY tag is used to specify the (relative or absolute) path
# into which the generated documentation will be written. If a relative path is
# entered, it will be relative to the location where doxygen was started. If
# left blank the current directory will be used.
OUTPUT_DIRECTORY = ./docs
# If the CREATE_SUBDIRS tag is set to YES then doxygen will create up to 4096
# sub-directories (in 2 levels) under the output directory of each output format
# and will distribute the generated files over these directories. Enabling this
# option can be useful when feeding doxygen a huge amount of source files, where
# putting all generated files in the same directory would otherwise causes
# performance problems for the file system. Adapt CREATE_SUBDIRS_LEVEL to
# control the number of sub-directories.
# The default value is: NO.
CREATE_SUBDIRS = NO
# Controls the number of sub-directories that will be created when
# CREATE_SUBDIRS tag is set to YES. Level 0 represents 16 directories, and every
# level increment doubles the number of directories, resulting in 4096
# directories at level 8 which is the default and also the maximum value. The
# sub-directories are organized in 2 levels, the first level always has a fixed
# number of 16 directories.
# Minimum value: 0, maximum value: 8, default value: 8.
# This tag requires that the tag CREATE_SUBDIRS is set to YES.
CREATE_SUBDIRS_LEVEL = 8
# If the ALLOW_UNICODE_NAMES tag is set to YES, doxygen will allow non-ASCII
# characters to appear in the names of generated files. If set to NO, non-ASCII
# characters will be escaped, for example _xE3_x81_x84 will be used for Unicode
# U+3044.
# The default value is: NO.
ALLOW_UNICODE_NAMES = NO
# The OUTPUT_LANGUAGE tag is used to specify the language in which all
# documentation generated by doxygen is written. Doxygen will use this
# information to generate all constant output in the proper language.
# Possible values are: Afrikaans, Arabic, Armenian, Brazilian, Bulgarian,
# Catalan, Chinese, Chinese-Traditional, Croatian, Czech, Danish, Dutch, English
# (United States), Esperanto, Farsi (Persian), Finnish, French, German, Greek,
# Hindi, Hungarian, Indonesian, Italian, Japanese, Japanese-en (Japanese with
# English messages), Korean, Korean-en (Korean with English messages), Latvian,
# Lithuanian, Macedonian, Norwegian, Persian (Farsi), Polish, Portuguese,
# Romanian, Russian, Serbian, Serbian-Cyrillic, Slovak, Slovene, Spanish,
# Swedish, Turkish, Ukrainian and Vietnamese.
# The default value is: English.
OUTPUT_LANGUAGE = English
# If the BRIEF_MEMBER_DESC tag is set to YES, doxygen will include brief member
# descriptions after the members that are listed in the file and class
# documentation (similar to Javadoc). Set to NO to disable this.
# The default value is: YES.
BRIEF_MEMBER_DESC = YES
# If the REPEAT_BRIEF tag is set to YES, doxygen will prepend the brief
# description of a member or function before the detailed description
#
# Note: If both HIDE_UNDOC_MEMBERS and BRIEF_MEMBER_DESC are set to NO, the
# brief descriptions will be completely suppressed.
# The default value is: YES.
REPEAT_BRIEF = YES
# This tag implements a quasi-intelligent brief description abbreviator that is
# used to form the text in various listings. Each string in this list, if found
# as the leading text of the brief description, will be stripped from the text
# and the result, after processing the whole list, is used as the annotated
# text. Otherwise, the brief description is used as-is. If left blank, the
# following values are used ($name is automatically replaced with the name of
# the entity):The $name class, The $name widget, The $name file, is, provides,
# specifies, contains, represents, a, an and the.
ABBREVIATE_BRIEF = "The $name class" \
"The $name widget" \
"The $name file" \
is \
provides \
specifies \
contains \
represents \
a \
an \
the
# If the ALWAYS_DETAILED_SEC and REPEAT_BRIEF tags are both set to YES then
# doxygen will generate a detailed section even if there is only a brief
# description.
# The default value is: NO.
ALWAYS_DETAILED_SEC = NO
# If the INLINE_INHERITED_MEMB tag is set to YES, doxygen will show all
# inherited members of a class in the documentation of that class as if those
# members were ordinary class members. Constructors, destructors and assignment
# operators of the base classes will not be shown.
# The default value is: NO.
INLINE_INHERITED_MEMB = NO
# If the FULL_PATH_NAMES tag is set to YES, doxygen will prepend the full path
# before files name in the file list and in the header files. If set to NO the
# shortest path that makes the file name unique will be used
# The default value is: YES.
FULL_PATH_NAMES = YES
# The STRIP_FROM_PATH tag can be used to strip a user-defined part of the path.
# Stripping is only done if one of the specified strings matches the left-hand
# part of the path. The tag can be used to show relative paths in the file list.
# If left blank the directory from which doxygen is run is used as the path to
# strip.
#
# Note that you can specify absolute paths here, but also relative paths, which
# will be relative from the directory where doxygen is started.
# This tag requires that the tag FULL_PATH_NAMES is set to YES.
STRIP_FROM_PATH = ../../csrc/mmdeploy/apis
# The STRIP_FROM_INC_PATH tag can be used to strip a user-defined part of the
# path mentioned in the documentation of a class, which tells the reader which
# header file to include in order to use a class. If left blank only the name of
# the header file containing the class definition is used. Otherwise one should
# specify the list of include paths that are normally passed to the compiler
# using the -I flag.
STRIP_FROM_INC_PATH =
# If the SHORT_NAMES tag is set to YES, doxygen will generate much shorter (but
# less readable) file names. This can be useful is your file systems doesn't
# support long names like on DOS, Mac, or CD-ROM.
# The default value is: NO.
SHORT_NAMES = NO
# If the JAVADOC_AUTOBRIEF tag is set to YES then doxygen will interpret the
# first line (until the first dot) of a Javadoc-style comment as the brief
# description. If set to NO, the Javadoc-style will behave just like regular Qt-
# style comments (thus requiring an explicit @brief command for a brief
# description.)
# The default value is: NO.
JAVADOC_AUTOBRIEF = NO
# If the JAVADOC_BANNER tag is set to YES then doxygen will interpret a line
# such as
# /***************
# as being the beginning of a Javadoc-style comment "banner". If set to NO, the
# Javadoc-style will behave just like regular comments and it will not be
# interpreted by doxygen.
# The default value is: NO.
JAVADOC_BANNER = NO
# If the QT_AUTOBRIEF tag is set to YES then doxygen will interpret the first
# line (until the first dot) of a Qt-style comment as the brief description. If
# set to NO, the Qt-style will behave just like regular Qt-style comments (thus
# requiring an explicit \brief command for a brief description.)
# The default value is: NO.
QT_AUTOBRIEF = NO
# The MULTILINE_CPP_IS_BRIEF tag can be set to YES to make doxygen treat a
# multi-line C++ special comment block (i.e. a block of //! or /// comments) as
# a brief description. This used to be the default behavior. The new default is
# to treat a multi-line C++ comment block as a detailed description. Set this
# tag to YES if you prefer the old behavior instead.
#
# Note that setting this tag to YES also means that rational rose comments are
# not recognized any more.
# The default value is: NO.
MULTILINE_CPP_IS_BRIEF = NO
# By default Python docstrings are displayed as preformatted text and doxygen's
# special commands cannot be used. By setting PYTHON_DOCSTRING to NO the
# doxygen's special commands can be used and the contents of the docstring
# documentation blocks is shown as doxygen documentation.
# The default value is: YES.
PYTHON_DOCSTRING = YES
# If the INHERIT_DOCS tag is set to YES then an undocumented member inherits the
# documentation from any documented member that it re-implements.
# The default value is: YES.
INHERIT_DOCS = YES
# If the SEPARATE_MEMBER_PAGES tag is set to YES then doxygen will produce a new
# page for each member. If set to NO, the documentation of a member will be part
# of the file/class/namespace that contains it.
# The default value is: NO.
SEPARATE_MEMBER_PAGES = NO
# The TAB_SIZE tag can be used to set the number of spaces in a tab. Doxygen
# uses this value to replace tabs by spaces in code fragments.
# Minimum value: 1, maximum value: 16, default value: 4.
TAB_SIZE = 4
# This tag can be used to specify a number of aliases that act as commands in
# the documentation. An alias has the form:
# name=value
# For example adding
# "sideeffect=@par Side Effects:^^"
# will allow you to put the command \sideeffect (or @sideeffect) in the
# documentation, which will result in a user-defined paragraph with heading
# "Side Effects:". Note that you cannot put \n's in the value part of an alias
# to insert newlines (in the resulting output). You can put ^^ in the value part
# of an alias to insert a newline as if a physical newline was in the original
# file. When you need a literal { or } or , in the value part of an alias you
# have to escape them by means of a backslash (\), this can lead to conflicts
# with the commands \{ and \} for these it is advised to use the version @{ and
# @} or use a double escape (\\{ and \\})
ALIASES =
# Set the OPTIMIZE_OUTPUT_FOR_C tag to YES if your project consists of C sources
# only. Doxygen will then generate output that is more tailored for C. For
# instance, some of the names that are used will be different. The list of all
# members will be omitted, etc.
# The default value is: NO.
OPTIMIZE_OUTPUT_FOR_C = NO
# Set the OPTIMIZE_OUTPUT_JAVA tag to YES if your project consists of Java or
# Python sources only. Doxygen will then generate output that is more tailored
# for that language. For instance, namespaces will be presented as packages,
# qualified scopes will look different, etc.
# The default value is: NO.
OPTIMIZE_OUTPUT_JAVA = NO
# Set the OPTIMIZE_FOR_FORTRAN tag to YES if your project consists of Fortran
# sources. Doxygen will then generate output that is tailored for Fortran.
# The default value is: NO.
OPTIMIZE_FOR_FORTRAN = NO
# Set the OPTIMIZE_OUTPUT_VHDL tag to YES if your project consists of VHDL
# sources. Doxygen will then generate output that is tailored for VHDL.
# The default value is: NO.
OPTIMIZE_OUTPUT_VHDL = NO
# Set the OPTIMIZE_OUTPUT_SLICE tag to YES if your project consists of Slice
# sources only. Doxygen will then generate output that is more tailored for that
# language. For instance, namespaces will be presented as modules, types will be
# separated into more groups, etc.
# The default value is: NO.
OPTIMIZE_OUTPUT_SLICE = NO
# Doxygen selects the parser to use depending on the extension of the files it
# parses. With this tag you can assign which parser to use for a given
# extension. Doxygen has a built-in mapping, but you can override or extend it
# using this tag. The format is ext=language, where ext is a file extension, and
# language is one of the parsers supported by doxygen: IDL, Java, JavaScript,
# Csharp (C#), C, C++, Lex, D, PHP, md (Markdown), Objective-C, Python, Slice,
# VHDL, Fortran (fixed format Fortran: FortranFixed, free formatted Fortran:
# FortranFree, unknown formatted Fortran: Fortran. In the later case the parser
# tries to guess whether the code is fixed or free formatted code, this is the
# default for Fortran type files). For instance to make doxygen treat .inc files
# as Fortran files (default is PHP), and .f files as C (default is Fortran),
# use: inc=Fortran f=C.
#
# Note: For files without extension you can use no_extension as a placeholder.
#
# Note that for custom extensions you also need to set FILE_PATTERNS otherwise
# the files are not read by doxygen. When specifying no_extension you should add
# * to the FILE_PATTERNS.
#
# Note see also the list of default file extension mappings.
EXTENSION_MAPPING =
# If the MARKDOWN_SUPPORT tag is enabled then doxygen pre-processes all comments
# according to the Markdown format, which allows for more readable
# documentation. See https://daringfireball.net/projects/markdown/ for details.
# The output of markdown processing is further processed by doxygen, so you can
# mix doxygen, HTML, and XML commands with Markdown formatting. Disable only in
# case of backward compatibilities issues.
# The default value is: YES.
MARKDOWN_SUPPORT = YES
# When the TOC_INCLUDE_HEADINGS tag is set to a non-zero value, all headings up
# to that level are automatically included in the table of contents, even if
# they do not have an id attribute.
# Note: This feature currently applies only to Markdown headings.
# Minimum value: 0, maximum value: 99, default value: 5.
# This tag requires that the tag MARKDOWN_SUPPORT is set to YES.
TOC_INCLUDE_HEADINGS = 5
# The MARKDOWN_ID_STYLE tag can be used to specify the algorithm used to
# generate identifiers for the Markdown headings. Note: Every identifier is
# unique.
# Possible values are: DOXYGEN Use a fixed 'autotoc_md' string followed by a
# sequence number starting at 0. and GITHUB Use the lower case version of title
# with any whitespace replaced by '-' and punctations characters removed..
# The default value is: DOXYGEN.
# This tag requires that the tag MARKDOWN_SUPPORT is set to YES.
MARKDOWN_ID_STYLE = DOXYGEN
# When enabled doxygen tries to link words that correspond to documented
# classes, or namespaces to their corresponding documentation. Such a link can
# be prevented in individual cases by putting a % sign in front of the word or
# globally by setting AUTOLINK_SUPPORT to NO.
# The default value is: YES.
AUTOLINK_SUPPORT = YES
# If you use STL classes (i.e. std::string, std::vector, etc.) but do not want
# to include (a tag file for) the STL sources as input, then you should set this
# tag to YES in order to let doxygen match functions declarations and
# definitions whose arguments contain STL classes (e.g. func(std::string);
# versus func(std::string) {}). This also make the inheritance and collaboration
# diagrams that involve STL classes more complete and accurate.
# The default value is: NO.
BUILTIN_STL_SUPPORT = NO
# If you use Microsoft's C++/CLI language, you should set this option to YES to
# enable parsing support.
# The default value is: NO.
CPP_CLI_SUPPORT = NO
# Set the SIP_SUPPORT tag to YES if your project consists of sip (see:
# https://www.riverbankcomputing.com/software/sip/intro) sources only. Doxygen
# will parse them like normal C++ but will assume all classes use public instead
# of private inheritance when no explicit protection keyword is present.
# The default value is: NO.
SIP_SUPPORT = NO
# For Microsoft's IDL there are propget and propput attributes to indicate
# getter and setter methods for a property. Setting this option to YES will make
# doxygen to replace the get and set methods by a property in the documentation.
# This will only work if the methods are indeed getting or setting a simple
# type. If this is not the case, or you want to show the methods anyway, you
# should set this option to NO.
# The default value is: YES.
IDL_PROPERTY_SUPPORT = YES
# If member grouping is used in the documentation and the DISTRIBUTE_GROUP_DOC
# tag is set to YES then doxygen will reuse the documentation of the first
# member in the group (if any) for the other members of the group. By default
# all members of a group must be documented explicitly.
# The default value is: NO.
DISTRIBUTE_GROUP_DOC = NO
# If one adds a struct or class to a group and this option is enabled, then also
# any nested class or struct is added to the same group. By default this option
# is disabled and one has to add nested compounds explicitly via \ingroup.
# The default value is: NO.
GROUP_NESTED_COMPOUNDS = NO
# Set the SUBGROUPING tag to YES to allow class member groups of the same type
# (for instance a group of public functions) to be put as a subgroup of that
# type (e.g. under the Public Functions section). Set it to NO to prevent
# subgrouping. Alternatively, this can be done per class using the
# \nosubgrouping command.
# The default value is: YES.
SUBGROUPING = YES
# When the INLINE_GROUPED_CLASSES tag is set to YES, classes, structs and unions
# are shown inside the group in which they are included (e.g. using \ingroup)
# instead of on a separate page (for HTML and Man pages) or section (for LaTeX
# and RTF).
#
# Note that this feature does not work in combination with
# SEPARATE_MEMBER_PAGES.
# The default value is: NO.
INLINE_GROUPED_CLASSES = NO
# When the INLINE_SIMPLE_STRUCTS tag is set to YES, structs, classes, and unions
# with only public data fields or simple typedef fields will be shown inline in
# the documentation of the scope in which they are defined (i.e. file,
# namespace, or group documentation), provided this scope is documented. If set
# to NO, structs, classes, and unions are shown on a separate page (for HTML and
# Man pages) or section (for LaTeX and RTF).
# The default value is: NO.
INLINE_SIMPLE_STRUCTS = NO
# When TYPEDEF_HIDES_STRUCT tag is enabled, a typedef of a struct, union, or
# enum is documented as struct, union, or enum with the name of the typedef. So
# typedef struct TypeS {} TypeT, will appear in the documentation as a struct
# with name TypeT. When disabled the typedef will appear as a member of a file,
# namespace, or class. And the struct will be named TypeS. This can typically be
# useful for C code in case the coding convention dictates that all compound
# types are typedef'ed and only the typedef is referenced, never the tag name.
# The default value is: NO.
TYPEDEF_HIDES_STRUCT = NO
# The size of the symbol lookup cache can be set using LOOKUP_CACHE_SIZE. This
# cache is used to resolve symbols given their name and scope. Since this can be
# an expensive process and often the same symbol appears multiple times in the
# code, doxygen keeps a cache of pre-resolved symbols. If the cache is too small
# doxygen will become slower. If the cache is too large, memory is wasted. The
# cache size is given by this formula: 2^(16+LOOKUP_CACHE_SIZE). The valid range
# is 0..9, the default is 0, corresponding to a cache size of 2^16=65536
# symbols. At the end of a run doxygen will report the cache usage and suggest
# the optimal cache size from a speed point of view.
# Minimum value: 0, maximum value: 9, default value: 0.
LOOKUP_CACHE_SIZE = 0
# The NUM_PROC_THREADS specifies the number of threads doxygen is allowed to use
# during processing. When set to 0 doxygen will based this on the number of
# cores available in the system. You can set it explicitly to a value larger
# than 0 to get more control over the balance between CPU load and processing
# speed. At this moment only the input processing can be done using multiple
# threads. Since this is still an experimental feature the default is set to 1,
# which effectively disables parallel processing. Please report any issues you
# encounter. Generating dot graphs in parallel is controlled by the
# DOT_NUM_THREADS setting.
# Minimum value: 0, maximum value: 32, default value: 1.
NUM_PROC_THREADS = 1
# If the TIMESTAMP tag is set different from NO then each generated page will
# contain the date or date and time when the page was generated. Setting this to
# NO can help when comparing the output of multiple runs.
# Possible values are: YES, NO, DATETIME and DATE.
# The default value is: NO.
TIMESTAMP = NO
#---------------------------------------------------------------------------
# Build related configuration options
#---------------------------------------------------------------------------
# If the EXTRACT_ALL tag is set to YES, doxygen will assume all entities in
# documentation are documented, even if no documentation was available. Private
# class members and static file members will be hidden unless the
# EXTRACT_PRIVATE respectively EXTRACT_STATIC tags are set to YES.
# Note: This will also disable the warnings about undocumented members that are
# normally produced when WARNINGS is set to YES.
# The default value is: NO.
EXTRACT_ALL = NO
# If the EXTRACT_PRIVATE tag is set to YES, all private members of a class will
# be included in the documentation.
# The default value is: NO.
EXTRACT_PRIVATE = NO
# If the EXTRACT_PRIV_VIRTUAL tag is set to YES, documented private virtual
# methods of a class will be included in the documentation.
# The default value is: NO.
EXTRACT_PRIV_VIRTUAL = NO
# If the EXTRACT_PACKAGE tag is set to YES, all members with package or internal
# scope will be included in the documentation.
# The default value is: NO.
EXTRACT_PACKAGE = NO
# If the EXTRACT_STATIC tag is set to YES, all static members of a file will be
# included in the documentation.
# The default value is: NO.
EXTRACT_STATIC = NO
# If the EXTRACT_LOCAL_CLASSES tag is set to YES, classes (and structs) defined
# locally in source files will be included in the documentation. If set to NO,
# only classes defined in header files are included. Does not have any effect
# for Java sources.
# The default value is: YES.
EXTRACT_LOCAL_CLASSES = YES
# This flag is only useful for Objective-C code. If set to YES, local methods,
# which are defined in the implementation section but not in the interface are
# included in the documentation. If set to NO, only methods in the interface are
# included.
# The default value is: NO.
EXTRACT_LOCAL_METHODS = NO
# If this flag is set to YES, the members of anonymous namespaces will be
# extracted and appear in the documentation as a namespace called
# 'anonymous_namespace{file}', where file will be replaced with the base name of
# the file that contains the anonymous namespace. By default anonymous namespace
# are hidden.
# The default value is: NO.
EXTRACT_ANON_NSPACES = NO
# If this flag is set to YES, the name of an unnamed parameter in a declaration
# will be determined by the corresponding definition. By default unnamed
# parameters remain unnamed in the output.
# The default value is: YES.
RESOLVE_UNNAMED_PARAMS = YES
# If the HIDE_UNDOC_MEMBERS tag is set to YES, doxygen will hide all
# undocumented members inside documented classes or files. If set to NO these
# members will be included in the various overviews, but no documentation
# section is generated. This option has no effect if EXTRACT_ALL is enabled.
# The default value is: NO.
HIDE_UNDOC_MEMBERS = NO
# If the HIDE_UNDOC_CLASSES tag is set to YES, doxygen will hide all
# undocumented classes that are normally visible in the class hierarchy. If set
# to NO, these classes will be included in the various overviews. This option
# will also hide undocumented C++ concepts if enabled. This option has no effect
# if EXTRACT_ALL is enabled.
# The default value is: NO.
HIDE_UNDOC_CLASSES = NO
# If the HIDE_FRIEND_COMPOUNDS tag is set to YES, doxygen will hide all friend
# declarations. If set to NO, these declarations will be included in the
# documentation.
# The default value is: NO.
HIDE_FRIEND_COMPOUNDS = NO
# If the HIDE_IN_BODY_DOCS tag is set to YES, doxygen will hide any
# documentation blocks found inside the body of a function. If set to NO, these
# blocks will be appended to the function's detailed documentation block.
# The default value is: NO.
HIDE_IN_BODY_DOCS = NO
# The INTERNAL_DOCS tag determines if documentation that is typed after a
# \internal command is included. If the tag is set to NO then the documentation
# will be excluded. Set it to YES to include the internal documentation.
# The default value is: NO.
INTERNAL_DOCS = NO
# With the correct setting of option CASE_SENSE_NAMES doxygen will better be
# able to match the capabilities of the underlying filesystem. In case the
# filesystem is case sensitive (i.e. it supports files in the same directory
# whose names only differ in casing), the option must be set to YES to properly
# deal with such files in case they appear in the input. For filesystems that
# are not case sensitive the option should be set to NO to properly deal with
# output files written for symbols that only differ in casing, such as for two
# classes, one named CLASS and the other named Class, and to also support
# references to files without having to specify the exact matching casing. On
# Windows (including Cygwin) and MacOS, users should typically set this option
# to NO, whereas on Linux or other Unix flavors it should typically be set to
# YES.
# Possible values are: SYSTEM, NO and YES.
# The default value is: SYSTEM.
CASE_SENSE_NAMES = SYSTEM
# If the HIDE_SCOPE_NAMES tag is set to NO then doxygen will show members with
# their full class and namespace scopes in the documentation. If set to YES, the
# scope will be hidden.
# The default value is: NO.
HIDE_SCOPE_NAMES = NO
# If the HIDE_COMPOUND_REFERENCE tag is set to NO (default) then doxygen will
# append additional text to a page's title, such as Class Reference. If set to
# YES the compound reference will be hidden.
# The default value is: NO.
HIDE_COMPOUND_REFERENCE= NO
# If the SHOW_HEADERFILE tag is set to YES then the documentation for a class
# will show which file needs to be included to use the class.
# The default value is: YES.
SHOW_HEADERFILE = YES
# If the SHOW_INCLUDE_FILES tag is set to YES then doxygen will put a list of
# the files that are included by a file in the documentation of that file.
# The default value is: YES.
SHOW_INCLUDE_FILES = YES
# If the SHOW_GROUPED_MEMB_INC tag is set to YES then Doxygen will add for each
# grouped member an include statement to the documentation, telling the reader
# which file to include in order to use the member.
# The default value is: NO.
SHOW_GROUPED_MEMB_INC = NO
# If the FORCE_LOCAL_INCLUDES tag is set to YES then doxygen will list include
# files with double quotes in the documentation rather than with sharp brackets.
# The default value is: NO.
FORCE_LOCAL_INCLUDES = NO
# If the INLINE_INFO tag is set to YES then a tag [inline] is inserted in the
# documentation for inline members.
# The default value is: YES.
INLINE_INFO = YES
# If the SORT_MEMBER_DOCS tag is set to YES then doxygen will sort the
# (detailed) documentation of file and class members alphabetically by member
# name. If set to NO, the members will appear in declaration order.
# The default value is: YES.
SORT_MEMBER_DOCS = YES
# If the SORT_BRIEF_DOCS tag is set to YES then doxygen will sort the brief
# descriptions of file, namespace and class members alphabetically by member
# name. If set to NO, the members will appear in declaration order. Note that
# this will also influence the order of the classes in the class list.
# The default value is: NO.
SORT_BRIEF_DOCS = NO
# If the SORT_MEMBERS_CTORS_1ST tag is set to YES then doxygen will sort the
# (brief and detailed) documentation of class members so that constructors and
# destructors are listed first. If set to NO the constructors will appear in the
# respective orders defined by SORT_BRIEF_DOCS and SORT_MEMBER_DOCS.
# Note: If SORT_BRIEF_DOCS is set to NO this option is ignored for sorting brief
# member documentation.
# Note: If SORT_MEMBER_DOCS is set to NO this option is ignored for sorting
# detailed member documentation.
# The default value is: NO.
SORT_MEMBERS_CTORS_1ST = NO
# If the SORT_GROUP_NAMES tag is set to YES then doxygen will sort the hierarchy
# of group names into alphabetical order. If set to NO the group names will
# appear in their defined order.
# The default value is: NO.
SORT_GROUP_NAMES = NO
# If the SORT_BY_SCOPE_NAME tag is set to YES, the class list will be sorted by
# fully-qualified names, including namespaces. If set to NO, the class list will
# be sorted only by class name, not including the namespace part.
# Note: This option is not very useful if HIDE_SCOPE_NAMES is set to YES.
# Note: This option applies only to the class list, not to the alphabetical
# list.
# The default value is: NO.
SORT_BY_SCOPE_NAME = NO
# If the STRICT_PROTO_MATCHING option is enabled and doxygen fails to do proper
# type resolution of all parameters of a function it will reject a match between
# the prototype and the implementation of a member function even if there is
# only one candidate or it is obvious which candidate to choose by doing a
# simple string match. By disabling STRICT_PROTO_MATCHING doxygen will still
# accept a match between prototype and implementation in such cases.
# The default value is: NO.
STRICT_PROTO_MATCHING = NO
# The GENERATE_TODOLIST tag can be used to enable (YES) or disable (NO) the todo
# list. This list is created by putting \todo commands in the documentation.
# The default value is: YES.
GENERATE_TODOLIST = YES
# The GENERATE_TESTLIST tag can be used to enable (YES) or disable (NO) the test
# list. This list is created by putting \test commands in the documentation.
# The default value is: YES.
GENERATE_TESTLIST = YES
# The GENERATE_BUGLIST tag can be used to enable (YES) or disable (NO) the bug
# list. This list is created by putting \bug commands in the documentation.
# The default value is: YES.
GENERATE_BUGLIST = YES
# The GENERATE_DEPRECATEDLIST tag can be used to enable (YES) or disable (NO)
# the deprecated list. This list is created by putting \deprecated commands in
# the documentation.
# The default value is: YES.
GENERATE_DEPRECATEDLIST= YES
# The ENABLED_SECTIONS tag can be used to enable conditional documentation
# sections, marked by \if <section_label> ... \endif and \cond <section_label>
# ... \endcond blocks.
ENABLED_SECTIONS =
# The MAX_INITIALIZER_LINES tag determines the maximum number of lines that the
# initial value of a variable or macro / define can have for it to appear in the
# documentation. If the initializer consists of more lines than specified here
# it will be hidden. Use a value of 0 to hide initializers completely. The
# appearance of the value of individual variables and macros / defines can be
# controlled using \showinitializer or \hideinitializer command in the
# documentation regardless of this setting.
# Minimum value: 0, maximum value: 10000, default value: 30.
MAX_INITIALIZER_LINES = 30
# Set the SHOW_USED_FILES tag to NO to disable the list of files generated at
# the bottom of the documentation of classes and structs. If set to YES, the
# list will mention the files that were used to generate the documentation.
# The default value is: YES.
SHOW_USED_FILES = YES
# Set the SHOW_FILES tag to NO to disable the generation of the Files page. This
# will remove the Files entry from the Quick Index and from the Folder Tree View
# (if specified).
# The default value is: YES.
SHOW_FILES = YES
# Set the SHOW_NAMESPACES tag to NO to disable the generation of the Namespaces
# page. This will remove the Namespaces entry from the Quick Index and from the
# Folder Tree View (if specified).
# The default value is: YES.
SHOW_NAMESPACES = YES
# The FILE_VERSION_FILTER tag can be used to specify a program or script that
# doxygen should invoke to get the current version for each file (typically from
# the version control system). Doxygen will invoke the program by executing (via
# popen()) the command command input-file, where command is the value of the
# FILE_VERSION_FILTER tag, and input-file is the name of an input file provided
# by doxygen. Whatever the program writes to standard output is used as the file
# version. For an example see the documentation.
FILE_VERSION_FILTER =
# The LAYOUT_FILE tag can be used to specify a layout file which will be parsed
# by doxygen. The layout file controls the global structure of the generated
# output files in an output format independent way. To create the layout file
# that represents doxygen's defaults, run doxygen with the -l option. You can
# optionally specify a file name after the option, if omitted DoxygenLayout.xml
# will be used as the name of the layout file. See also section "Changing the
# layout of pages" for information.
#
# Note that if you run doxygen from a directory containing a file called
# DoxygenLayout.xml, doxygen will parse it automatically even if the LAYOUT_FILE
# tag is left empty.
LAYOUT_FILE =
# The CITE_BIB_FILES tag can be used to specify one or more bib files containing
# the reference definitions. This must be a list of .bib files. The .bib
# extension is automatically appended if omitted. This requires the bibtex tool
# to be installed. See also https://en.wikipedia.org/wiki/BibTeX for more info.
# For LaTeX the style of the bibliography can be controlled using
# LATEX_BIB_STYLE. To use this feature you need bibtex and perl available in the
# search path. See also \cite for info how to create references.
CITE_BIB_FILES =
#---------------------------------------------------------------------------
# Configuration options related to warning and progress messages
#---------------------------------------------------------------------------
# The QUIET tag can be used to turn on/off the messages that are generated to
# standard output by doxygen. If QUIET is set to YES this implies that the
# messages are off.
# The default value is: NO.
QUIET = NO
# The WARNINGS tag can be used to turn on/off the warning messages that are
# generated to standard error (stderr) by doxygen. If WARNINGS is set to YES
# this implies that the warnings are on.
#
# Tip: Turn warnings on while writing the documentation.
# The default value is: YES.
WARNINGS = YES
# If the WARN_IF_UNDOCUMENTED tag is set to YES then doxygen will generate
# warnings for undocumented members. If EXTRACT_ALL is set to YES then this flag
# will automatically be disabled.
# The default value is: YES.
WARN_IF_UNDOCUMENTED = NO
# If the WARN_IF_DOC_ERROR tag is set to YES, doxygen will generate warnings for
# potential errors in the documentation, such as documenting some parameters in
# a documented function twice, or documenting parameters that don't exist or
# using markup commands wrongly.
# The default value is: YES.
WARN_IF_DOC_ERROR = YES
# If WARN_IF_INCOMPLETE_DOC is set to YES, doxygen will warn about incomplete
# function parameter documentation. If set to NO, doxygen will accept that some
# parameters have no documentation without warning.
# The default value is: YES.
WARN_IF_INCOMPLETE_DOC = YES
# This WARN_NO_PARAMDOC option can be enabled to get warnings for functions that
# are documented, but have no documentation for their parameters or return
# value. If set to NO, doxygen will only warn about wrong parameter
# documentation, but not about the absence of documentation. If EXTRACT_ALL is
# set to YES then this flag will automatically be disabled. See also
# WARN_IF_INCOMPLETE_DOC
# The default value is: NO.
WARN_NO_PARAMDOC = NO
# If WARN_IF_UNDOC_ENUM_VAL option is set to YES, doxygen will warn about
# undocumented enumeration values. If set to NO, doxygen will accept
# undocumented enumeration values. If EXTRACT_ALL is set to YES then this flag
# will automatically be disabled.
# The default value is: NO.
WARN_IF_UNDOC_ENUM_VAL = NO
# If the WARN_AS_ERROR tag is set to YES then doxygen will immediately stop when
# a warning is encountered. If the WARN_AS_ERROR tag is set to FAIL_ON_WARNINGS
# then doxygen will continue running as if WARN_AS_ERROR tag is set to NO, but
# at the end of the doxygen process doxygen will return with a non-zero status.
# If the WARN_AS_ERROR tag is set to FAIL_ON_WARNINGS_PRINT then doxygen behaves
# like FAIL_ON_WARNINGS but in case no WARN_LOGFILE is defined doxygen will not
# write the warning messages in between other messages but write them at the end
# of a run, in case a WARN_LOGFILE is defined the warning messages will be
# besides being in the defined file also be shown at the end of a run, unless
# the WARN_LOGFILE is defined as - i.e. standard output (stdout) in that case
# the behavior will remain as with the setting FAIL_ON_WARNINGS.
# Possible values are: NO, YES, FAIL_ON_WARNINGS and FAIL_ON_WARNINGS_PRINT.
# The default value is: NO.
WARN_AS_ERROR = NO
# The WARN_FORMAT tag determines the format of the warning messages that doxygen
# can produce. The string should contain the $file, $line, and $text tags, which
# will be replaced by the file and line number from which the warning originated
# and the warning text. Optionally the format may contain $version, which will
# be replaced by the version of the file (if it could be obtained via
# FILE_VERSION_FILTER)
# See also: WARN_LINE_FORMAT
# The default value is: $file:$line: $text.
WARN_FORMAT = "$file:$line: $text"
# In the $text part of the WARN_FORMAT command it is possible that a reference
# to a more specific place is given. To make it easier to jump to this place
# (outside of doxygen) the user can define a custom "cut" / "paste" string.
# Example:
# WARN_LINE_FORMAT = "'vi $file +$line'"
# See also: WARN_FORMAT
# The default value is: at line $line of file $file.
WARN_LINE_FORMAT = "at line $line of file $file"
# The WARN_LOGFILE tag can be used to specify a file to which warning and error
# messages should be written. If left blank the output is written to standard
# error (stderr). In case the file specified cannot be opened for writing the
# warning and error messages are written to standard error. When as file - is
# specified the warning and error messages are written to standard output
# (stdout).
WARN_LOGFILE =
#---------------------------------------------------------------------------
# Configuration options related to the input files
#---------------------------------------------------------------------------
# The INPUT tag is used to specify the files and/or directories that contain
# documented source files. You may enter file names like myfile.cpp or
# directories like /usr/src/myproject. Separate the files or directories with
# spaces. See also FILE_PATTERNS and EXTENSION_MAPPING
# Note: If this tag is empty the current directory is searched.
INPUT = \
../../csrc/mmdeploy/apis/cxx \
../../csrc/mmdeploy/apis/c
# This tag can be used to specify the character encoding of the source files
# that doxygen parses. Internally doxygen uses the UTF-8 encoding. Doxygen uses
# libiconv (or the iconv built into libc) for the transcoding. See the libiconv
# documentation (see:
# https://www.gnu.org/software/libiconv/) for the list of possible encodings.
# See also: INPUT_FILE_ENCODING
# The default value is: UTF-8.
INPUT_ENCODING = UTF-8
# This tag can be used to specify the character encoding of the source files
# that doxygen parses The INPUT_FILE_ENCODING tag can be used to specify
# character encoding on a per file pattern basis. Doxygen will compare the file
# name with each pattern and apply the encoding instead of the default
# INPUT_ENCODING) if there is a match. The character encodings are a list of the
# form: pattern=encoding (like *.php=ISO-8859-1). See cfg_input_encoding
# "INPUT_ENCODING" for further information on supported encodings.
INPUT_FILE_ENCODING =
# If the value of the INPUT tag contains directories, you can use the
# FILE_PATTERNS tag to specify one or more wildcard patterns (like *.cpp and
# *.h) to filter out the source-files in the directories.
#
# Note that for custom extensions or not directly supported extensions you also
# need to set EXTENSION_MAPPING for the extension otherwise the files are not
# read by doxygen.
#
# Note the list of default checked file patterns might differ from the list of
# default file extension mappings.
#
# If left blank the following patterns are tested:*.c, *.cc, *.cxx, *.cpp,
# *.c++, *.java, *.ii, *.ixx, *.ipp, *.i++, *.inl, *.idl, *.ddl, *.odl, *.h,
# *.hh, *.hxx, *.hpp, *.h++, *.l, *.cs, *.d, *.php, *.php4, *.php5, *.phtml,
# *.inc, *.m, *.markdown, *.md, *.mm, *.dox (to be provided as doxygen C
# comment), *.py, *.pyw, *.f90, *.f95, *.f03, *.f08, *.f18, *.f, *.for, *.vhd,
# *.vhdl, *.ucf, *.qsf and *.ice.
FILE_PATTERNS = *.c \
*.cc \
*.cxx \
*.cpp \
*.c++ \
*.java \
*.ii \
*.ixx \
*.ipp \
*.i++ \
*.inl \
*.idl \
*.ddl \
*.odl \
*.h \
*.hh \
*.hxx \
*.hpp \
*.h++ \
*.l \
*.cs \
*.d \
*.php \
*.php4 \
*.php5 \
*.phtml \
*.inc \
*.m \
*.markdown \
*.md \
*.mm \
*.dox \
*.py \
*.pyw \
*.f90 \
*.f95 \
*.f03 \
*.f08 \
*.f18 \
*.f \
*.for \
*.vhd \
*.vhdl \
*.ucf \
*.qsf \
*.ice
# The RECURSIVE tag can be used to specify whether or not subdirectories should
# be searched for input files as well.
# The default value is: NO.
RECURSIVE = YES
# The EXCLUDE tag can be used to specify files and/or directories that should be
# excluded from the INPUT source files. This way you can easily exclude a
# subdirectory from a directory tree whose root is specified with the INPUT tag.
#
# Note that relative paths are relative to the directory from which doxygen is
# run.
EXCLUDE =
# The EXCLUDE_SYMLINKS tag can be used to select whether or not files or
# directories that are symbolic links (a Unix file system feature) are excluded
# from the input.
# The default value is: NO.
EXCLUDE_SYMLINKS = NO
# If the value of the INPUT tag contains directories, you can use the
# EXCLUDE_PATTERNS tag to specify one or more wildcard patterns to exclude
# certain files from those directories.
#
# Note that the wildcards are matched against the file with absolute path, so to
# exclude all test directories for example use the pattern */test/*
EXCLUDE_PATTERNS =
# The EXCLUDE_SYMBOLS tag can be used to specify one or more symbol names
# (namespaces, classes, functions, etc.) that should be excluded from the
# output. The symbol name can be a fully qualified name, a word, or if the
# wildcard * is used, a substring. Examples: ANamespace, AClass,
# ANamespace::AClass, ANamespace::*Test
EXCLUDE_SYMBOLS =
# The EXAMPLE_PATH tag can be used to specify one or more files or directories
# that contain example code fragments that are included (see the \include
# command).
EXAMPLE_PATH =
# If the value of the EXAMPLE_PATH tag contains directories, you can use the
# EXAMPLE_PATTERNS tag to specify one or more wildcard pattern (like *.cpp and
# *.h) to filter out the source-files in the directories. If left blank all
# files are included.
EXAMPLE_PATTERNS = *
# If the EXAMPLE_RECURSIVE tag is set to YES then subdirectories will be
# searched for input files to be used with the \include or \dontinclude commands
# irrespective of the value of the RECURSIVE tag.
# The default value is: NO.
EXAMPLE_RECURSIVE = NO
# The IMAGE_PATH tag can be used to specify one or more files or directories
# that contain images that are to be included in the documentation (see the
# \image command).
IMAGE_PATH =
# The INPUT_FILTER tag can be used to specify a program that doxygen should
# invoke to filter for each input file. Doxygen will invoke the filter program
# by executing (via popen()) the command:
#
# <filter> <input-file>
#
# where <filter> is the value of the INPUT_FILTER tag, and <input-file> is the
# name of an input file. Doxygen will then use the output that the filter
# program writes to standard output. If FILTER_PATTERNS is specified, this tag
# will be ignored.
#
# Note that the filter must not add or remove lines; it is applied before the
# code is scanned, but not when the output code is generated. If lines are added
# or removed, the anchors will not be placed correctly.
#
# Note that doxygen will use the data processed and written to standard output
# for further processing, therefore nothing else, like debug statements or used
# commands (so in case of a Windows batch file always use @echo OFF), should be
# written to standard output.
#
# Note that for custom extensions or not directly supported extensions you also
# need to set EXTENSION_MAPPING for the extension otherwise the files are not
# properly processed by doxygen.
INPUT_FILTER =
# The FILTER_PATTERNS tag can be used to specify filters on a per file pattern
# basis. Doxygen will compare the file name with each pattern and apply the
# filter if there is a match. The filters are a list of the form: pattern=filter
# (like *.cpp=my_cpp_filter). See INPUT_FILTER for further information on how
# filters are used. If the FILTER_PATTERNS tag is empty or if none of the
# patterns match the file name, INPUT_FILTER is applied.
#
# Note that for custom extensions or not directly supported extensions you also
# need to set EXTENSION_MAPPING for the extension otherwise the files are not
# properly processed by doxygen.
FILTER_PATTERNS =
# If the FILTER_SOURCE_FILES tag is set to YES, the input filter (if set using
# INPUT_FILTER) will also be used to filter the input files that are used for
# producing the source files to browse (i.e. when SOURCE_BROWSER is set to YES).
# The default value is: NO.
FILTER_SOURCE_FILES = NO
# The FILTER_SOURCE_PATTERNS tag can be used to specify source filters per file
# pattern. A pattern will override the setting for FILTER_PATTERN (if any) and
# it is also possible to disable source filtering for a specific pattern using
# *.ext= (so without naming a filter).
# This tag requires that the tag FILTER_SOURCE_FILES is set to YES.
FILTER_SOURCE_PATTERNS =
# If the USE_MDFILE_AS_MAINPAGE tag refers to the name of a markdown file that
# is part of the input, its contents will be placed on the main page
# (index.html). This can be useful if you have a project on for instance GitHub
# and want to reuse the introduction page also for the doxygen output.
USE_MDFILE_AS_MAINPAGE =
# The Fortran standard specifies that for fixed formatted Fortran code all
# characters from position 72 are to be considered as comment. A common
# extension is to allow longer lines before the automatic comment starts. The
# setting FORTRAN_COMMENT_AFTER will also make it possible that longer lines can
# be processed before the automatic comment starts.
# Minimum value: 7, maximum value: 10000, default value: 72.
FORTRAN_COMMENT_AFTER = 72
#---------------------------------------------------------------------------
# Configuration options related to source browsing
#---------------------------------------------------------------------------
# If the SOURCE_BROWSER tag is set to YES then a list of source files will be
# generated. Documented entities will be cross-referenced with these sources.
#
# Note: To get rid of all source code in the generated output, make sure that
# also VERBATIM_HEADERS is set to NO.
# The default value is: NO.
SOURCE_BROWSER = NO
# Setting the INLINE_SOURCES tag to YES will include the body of functions,
# classes and enums directly into the documentation.
# The default value is: NO.
INLINE_SOURCES = NO
# Setting the STRIP_CODE_COMMENTS tag to YES will instruct doxygen to hide any
# special comment blocks from generated source code fragments. Normal C, C++ and
# Fortran comments will always remain visible.
# The default value is: YES.
STRIP_CODE_COMMENTS = YES
# If the REFERENCED_BY_RELATION tag is set to YES then for each documented
# entity all documented functions referencing it will be listed.
# The default value is: NO.
REFERENCED_BY_RELATION = NO
# If the REFERENCES_RELATION tag is set to YES then for each documented function
# all documented entities called/used by that function will be listed.
# The default value is: NO.
REFERENCES_RELATION = NO
# If the REFERENCES_LINK_SOURCE tag is set to YES and SOURCE_BROWSER tag is set
# to YES then the hyperlinks from functions in REFERENCES_RELATION and
# REFERENCED_BY_RELATION lists will link to the source code. Otherwise they will
# link to the documentation.
# The default value is: YES.
REFERENCES_LINK_SOURCE = YES
# If SOURCE_TOOLTIPS is enabled (the default) then hovering a hyperlink in the
# source code will show a tooltip with additional information such as prototype,
# brief description and links to the definition and documentation. Since this
# will make the HTML file larger and loading of large files a bit slower, you
# can opt to disable this feature.
# The default value is: YES.
# This tag requires that the tag SOURCE_BROWSER is set to YES.
SOURCE_TOOLTIPS = YES
# If the USE_HTAGS tag is set to YES then the references to source code will
# point to the HTML generated by the htags(1) tool instead of doxygen built-in
# source browser. The htags tool is part of GNU's global source tagging system
# (see https://www.gnu.org/software/global/global.html). You will need version
# 4.8.6 or higher.
#
# To use it do the following:
# - Install the latest version of global
# - Enable SOURCE_BROWSER and USE_HTAGS in the configuration file
# - Make sure the INPUT points to the root of the source tree
# - Run doxygen as normal
#
# Doxygen will invoke htags (and that will in turn invoke gtags), so these
# tools must be available from the command line (i.e. in the search path).
#
# The result: instead of the source browser generated by doxygen, the links to
# source code will now point to the output of htags.
# The default value is: NO.
# This tag requires that the tag SOURCE_BROWSER is set to YES.
USE_HTAGS = NO
# If the VERBATIM_HEADERS tag is set the YES then doxygen will generate a
# verbatim copy of the header file for each class for which an include is
# specified. Set to NO to disable this.
# See also: Section \class.
# The default value is: YES.
VERBATIM_HEADERS = YES
# If the CLANG_ASSISTED_PARSING tag is set to YES then doxygen will use the
# clang parser (see:
# http://clang.llvm.org/) for more accurate parsing at the cost of reduced
# performance. This can be particularly helpful with template rich C++ code for
# which doxygen's built-in parser lacks the necessary type information.
# Note: The availability of this option depends on whether or not doxygen was
# generated with the -Duse_libclang=ON option for CMake.
# The default value is: NO.
CLANG_ASSISTED_PARSING = NO
# If the CLANG_ASSISTED_PARSING tag is set to YES and the CLANG_ADD_INC_PATHS
# tag is set to YES then doxygen will add the directory of each input to the
# include path.
# The default value is: YES.
# This tag requires that the tag CLANG_ASSISTED_PARSING is set to YES.
CLANG_ADD_INC_PATHS = YES
# If clang assisted parsing is enabled you can provide the compiler with command
# line options that you would normally use when invoking the compiler. Note that
# the include paths will already be set by doxygen for the files and directories
# specified with INPUT and INCLUDE_PATH.
# This tag requires that the tag CLANG_ASSISTED_PARSING is set to YES.
CLANG_OPTIONS =
# If clang assisted parsing is enabled you can provide the clang parser with the
# path to the directory containing a file called compile_commands.json. This
# file is the compilation database (see:
# http://clang.llvm.org/docs/HowToSetupToolingForLLVM.html) containing the
# options used when the source files were built. This is equivalent to
# specifying the -p option to a clang tool, such as clang-check. These options
# will then be passed to the parser. Any options specified with CLANG_OPTIONS
# will be added as well.
# Note: The availability of this option depends on whether or not doxygen was
# generated with the -Duse_libclang=ON option for CMake.
CLANG_DATABASE_PATH =
#---------------------------------------------------------------------------
# Configuration options related to the alphabetical class index
#---------------------------------------------------------------------------
# If the ALPHABETICAL_INDEX tag is set to YES, an alphabetical index of all
# compounds will be generated. Enable this if the project contains a lot of
# classes, structs, unions or interfaces.
# The default value is: YES.
ALPHABETICAL_INDEX = YES
# The IGNORE_PREFIX tag can be used to specify a prefix (or a list of prefixes)
# that should be ignored while generating the index headers. The IGNORE_PREFIX
# tag works for classes, function and member names. The entity will be placed in
# the alphabetical list under the first letter of the entity name that remains
# after removing the prefix.
# This tag requires that the tag ALPHABETICAL_INDEX is set to YES.
IGNORE_PREFIX =
#---------------------------------------------------------------------------
# Configuration options related to the HTML output
#---------------------------------------------------------------------------
# If the GENERATE_HTML tag is set to YES, doxygen will generate HTML output
# The default value is: YES.
GENERATE_HTML = YES
# The HTML_OUTPUT tag is used to specify where the HTML docs will be put. If a
# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of
# it.
# The default directory is: html.
# This tag requires that the tag GENERATE_HTML is set to YES.
HTML_OUTPUT = html
# The HTML_FILE_EXTENSION tag can be used to specify the file extension for each
# generated HTML page (for example: .htm, .php, .asp).
# The default value is: .html.
# This tag requires that the tag GENERATE_HTML is set to YES.
HTML_FILE_EXTENSION = .html
# The HTML_HEADER tag can be used to specify a user-defined HTML header file for
# each generated HTML page. If the tag is left blank doxygen will generate a
# standard header.
#
# To get valid HTML the header file that includes any scripts and style sheets
# that doxygen needs, which is dependent on the configuration options used (e.g.
# the setting GENERATE_TREEVIEW). It is highly recommended to start with a
# default header using
# doxygen -w html new_header.html new_footer.html new_stylesheet.css
# YourConfigFile
# and then modify the file new_header.html. See also section "Doxygen usage"
# for information on how to generate the default header that doxygen normally
# uses.
# Note: The header is subject to change so you typically have to regenerate the
# default header when upgrading to a newer version of doxygen. For a description
# of the possible markers and block names see the documentation.
# This tag requires that the tag GENERATE_HTML is set to YES.
HTML_HEADER =
# The HTML_FOOTER tag can be used to specify a user-defined HTML footer for each
# generated HTML page. If the tag is left blank doxygen will generate a standard
# footer. See HTML_HEADER for more information on how to generate a default
# footer and what special commands can be used inside the footer. See also
# section "Doxygen usage" for information on how to generate the default footer
# that doxygen normally uses.
# This tag requires that the tag GENERATE_HTML is set to YES.
HTML_FOOTER =
# The HTML_STYLESHEET tag can be used to specify a user-defined cascading style
# sheet that is used by each HTML page. It can be used to fine-tune the look of
# the HTML output. If left blank doxygen will generate a default style sheet.
# See also section "Doxygen usage" for information on how to generate the style
# sheet that doxygen normally uses.
# Note: It is recommended to use HTML_EXTRA_STYLESHEET instead of this tag, as
# it is more robust and this tag (HTML_STYLESHEET) will in the future become
# obsolete.
# This tag requires that the tag GENERATE_HTML is set to YES.
HTML_STYLESHEET =
# The HTML_EXTRA_STYLESHEET tag can be used to specify additional user-defined
# cascading style sheets that are included after the standard style sheets
# created by doxygen. Using this option one can overrule certain style aspects.
# This is preferred over using HTML_STYLESHEET since it does not replace the
# standard style sheet and is therefore more robust against future updates.
# Doxygen will copy the style sheet files to the output directory.
# Note: The order of the extra style sheet files is of importance (e.g. the last
# style sheet in the list overrules the setting of the previous ones in the
# list).
# Note: Since the styling of scrollbars can currently not be overruled in
# Webkit/Chromium, the styling will be left out of the default doxygen.css if
# one or more extra stylesheets have been specified. So if scrollbar
# customization is desired it has to be added explicitly. For an example see the
# documentation.
# This tag requires that the tag GENERATE_HTML is set to YES.
HTML_EXTRA_STYLESHEET =
# The HTML_EXTRA_FILES tag can be used to specify one or more extra images or
# other source files which should be copied to the HTML output directory. Note
# that these files will be copied to the base HTML output directory. Use the
# $relpath^ marker in the HTML_HEADER and/or HTML_FOOTER files to load these
# files. In the HTML_STYLESHEET file, use the file name only. Also note that the
# files will be copied as-is; there are no commands or markers available.
# This tag requires that the tag GENERATE_HTML is set to YES.
HTML_EXTRA_FILES =
# The HTML_COLORSTYLE tag can be used to specify if the generated HTML output
# should be rendered with a dark or light theme.
# Possible values are: LIGHT always generate light mode output, DARK always
# generate dark mode output, AUTO_LIGHT automatically set the mode according to
# the user preference, use light mode if no preference is set (the default),
# AUTO_DARK automatically set the mode according to the user preference, use
# dark mode if no preference is set and TOGGLE allow to user to switch between
# light and dark mode via a button.
# The default value is: AUTO_LIGHT.
# This tag requires that the tag GENERATE_HTML is set to YES.
HTML_COLORSTYLE = AUTO_LIGHT
# The HTML_COLORSTYLE_HUE tag controls the color of the HTML output. Doxygen
# will adjust the colors in the style sheet and background images according to
# this color. Hue is specified as an angle on a color-wheel, see
# https://en.wikipedia.org/wiki/Hue for more information. For instance the value
# 0 represents red, 60 is yellow, 120 is green, 180 is cyan, 240 is blue, 300
# purple, and 360 is red again.
# Minimum value: 0, maximum value: 359, default value: 220.
# This tag requires that the tag GENERATE_HTML is set to YES.
HTML_COLORSTYLE_HUE = 220
# The HTML_COLORSTYLE_SAT tag controls the purity (or saturation) of the colors
# in the HTML output. For a value of 0 the output will use gray-scales only. A
# value of 255 will produce the most vivid colors.
# Minimum value: 0, maximum value: 255, default value: 100.
# This tag requires that the tag GENERATE_HTML is set to YES.
HTML_COLORSTYLE_SAT = 100
# The HTML_COLORSTYLE_GAMMA tag controls the gamma correction applied to the
# luminance component of the colors in the HTML output. Values below 100
# gradually make the output lighter, whereas values above 100 make the output
# darker. The value divided by 100 is the actual gamma applied, so 80 represents
# a gamma of 0.8, The value 220 represents a gamma of 2.2, and 100 does not
# change the gamma.
# Minimum value: 40, maximum value: 240, default value: 80.
# This tag requires that the tag GENERATE_HTML is set to YES.
HTML_COLORSTYLE_GAMMA = 80
# If the HTML_DYNAMIC_MENUS tag is set to YES then the generated HTML
# documentation will contain a main index with vertical navigation menus that
# are dynamically created via JavaScript. If disabled, the navigation index will
# consists of multiple levels of tabs that are statically embedded in every HTML
# page. Disable this option to support browsers that do not have JavaScript,
# like the Qt help browser.
# The default value is: YES.
# This tag requires that the tag GENERATE_HTML is set to YES.
HTML_DYNAMIC_MENUS = YES
# If the HTML_DYNAMIC_SECTIONS tag is set to YES then the generated HTML
# documentation will contain sections that can be hidden and shown after the
# page has loaded.
# The default value is: NO.
# This tag requires that the tag GENERATE_HTML is set to YES.
HTML_DYNAMIC_SECTIONS = NO
# With HTML_INDEX_NUM_ENTRIES one can control the preferred number of entries
# shown in the various tree structured indices initially; the user can expand
# and collapse entries dynamically later on. Doxygen will expand the tree to
# such a level that at most the specified number of entries are visible (unless
# a fully collapsed tree already exceeds this amount). So setting the number of
# entries 1 will produce a full collapsed tree by default. 0 is a special value
# representing an infinite number of entries and will result in a full expanded
# tree by default.
# Minimum value: 0, maximum value: 9999, default value: 100.
# This tag requires that the tag GENERATE_HTML is set to YES.
HTML_INDEX_NUM_ENTRIES = 100
# If the GENERATE_DOCSET tag is set to YES, additional index files will be
# generated that can be used as input for Apple's Xcode 3 integrated development
# environment (see:
# https://developer.apple.com/xcode/), introduced with OSX 10.5 (Leopard). To
# create a documentation set, doxygen will generate a Makefile in the HTML
# output directory. Running make will produce the docset in that directory and
# running make install will install the docset in
# ~/Library/Developer/Shared/Documentation/DocSets so that Xcode will find it at
# startup. See https://developer.apple.com/library/archive/featuredarticles/Doxy
# genXcode/_index.html for more information.
# The default value is: NO.
# This tag requires that the tag GENERATE_HTML is set to YES.
GENERATE_DOCSET = NO
# This tag determines the name of the docset feed. A documentation feed provides
# an umbrella under which multiple documentation sets from a single provider
# (such as a company or product suite) can be grouped.
# The default value is: Doxygen generated docs.
# This tag requires that the tag GENERATE_DOCSET is set to YES.
DOCSET_FEEDNAME = "Doxygen generated docs"
# This tag determines the URL of the docset feed. A documentation feed provides
# an umbrella under which multiple documentation sets from a single provider
# (such as a company or product suite) can be grouped.
# This tag requires that the tag GENERATE_DOCSET is set to YES.
DOCSET_FEEDURL =
# This tag specifies a string that should uniquely identify the documentation
# set bundle. This should be a reverse domain-name style string, e.g.
# com.mycompany.MyDocSet. Doxygen will append .docset to the name.
# The default value is: org.doxygen.Project.
# This tag requires that the tag GENERATE_DOCSET is set to YES.
DOCSET_BUNDLE_ID = org.doxygen.Project
# The DOCSET_PUBLISHER_ID tag specifies a string that should uniquely identify
# the documentation publisher. This should be a reverse domain-name style
# string, e.g. com.mycompany.MyDocSet.documentation.
# The default value is: org.doxygen.Publisher.
# This tag requires that the tag GENERATE_DOCSET is set to YES.
DOCSET_PUBLISHER_ID = org.doxygen.Publisher
# The DOCSET_PUBLISHER_NAME tag identifies the documentation publisher.
# The default value is: Publisher.
# This tag requires that the tag GENERATE_DOCSET is set to YES.
DOCSET_PUBLISHER_NAME = Publisher
# If the GENERATE_HTMLHELP tag is set to YES then doxygen generates three
# additional HTML index files: index.hhp, index.hhc, and index.hhk. The
# index.hhp is a project file that can be read by Microsoft's HTML Help Workshop
# on Windows. In the beginning of 2021 Microsoft took the original page, with
# a.o. the download links, offline the HTML help workshop was already many years
# in maintenance mode). You can download the HTML help workshop from the web
# archives at Installation executable (see:
# http://web.archive.org/web/20160201063255/http://download.microsoft.com/downlo
# ad/0/A/9/0A939EF6-E31C-430F-A3DF-DFAE7960D564/htmlhelp.exe).
#
# The HTML Help Workshop contains a compiler that can convert all HTML output
# generated by doxygen into a single compiled HTML file (.chm). Compiled HTML
# files are now used as the Windows 98 help format, and will replace the old
# Windows help format (.hlp) on all Windows platforms in the future. Compressed
# HTML files also contain an index, a table of contents, and you can search for
# words in the documentation. The HTML workshop also contains a viewer for
# compressed HTML files.
# The default value is: NO.
# This tag requires that the tag GENERATE_HTML is set to YES.
GENERATE_HTMLHELP = NO
# The CHM_FILE tag can be used to specify the file name of the resulting .chm
# file. You can add a path in front of the file if the result should not be
# written to the html output directory.
# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
CHM_FILE =
# The HHC_LOCATION tag can be used to specify the location (absolute path
# including file name) of the HTML help compiler (hhc.exe). If non-empty,
# doxygen will try to run the HTML help compiler on the generated index.hhp.
# The file has to be specified with full path.
# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
HHC_LOCATION =
# The GENERATE_CHI flag controls if a separate .chi index file is generated
# (YES) or that it should be included in the main .chm file (NO).
# The default value is: NO.
# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
GENERATE_CHI = NO
# The CHM_INDEX_ENCODING is used to encode HtmlHelp index (hhk), content (hhc)
# and project file content.
# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
CHM_INDEX_ENCODING =
# The BINARY_TOC flag controls whether a binary table of contents is generated
# (YES) or a normal table of contents (NO) in the .chm file. Furthermore it
# enables the Previous and Next buttons.
# The default value is: NO.
# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
BINARY_TOC = NO
# The TOC_EXPAND flag can be set to YES to add extra items for group members to
# the table of contents of the HTML help documentation and to the tree view.
# The default value is: NO.
# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
TOC_EXPAND = NO
# The SITEMAP_URL tag is used to specify the full URL of the place where the
# generated documentation will be placed on the server by the user during the
# deployment of the documentation. The generated sitemap is called sitemap.xml
# and placed on the directory specified by HTML_OUTPUT. In case no SITEMAP_URL
# is specified no sitemap is generated. For information about the sitemap
# protocol see https://www.sitemaps.org
# This tag requires that the tag GENERATE_HTML is set to YES.
SITEMAP_URL =
# If the GENERATE_QHP tag is set to YES and both QHP_NAMESPACE and
# QHP_VIRTUAL_FOLDER are set, an additional index file will be generated that
# can be used as input for Qt's qhelpgenerator to generate a Qt Compressed Help
# (.qch) of the generated HTML documentation.
# The default value is: NO.
# This tag requires that the tag GENERATE_HTML is set to YES.
GENERATE_QHP = NO
# If the QHG_LOCATION tag is specified, the QCH_FILE tag can be used to specify
# the file name of the resulting .qch file. The path specified is relative to
# the HTML output folder.
# This tag requires that the tag GENERATE_QHP is set to YES.
QCH_FILE =
# The QHP_NAMESPACE tag specifies the namespace to use when generating Qt Help
# Project output. For more information please see Qt Help Project / Namespace
# (see:
# https://doc.qt.io/archives/qt-4.8/qthelpproject.html#namespace).
# The default value is: org.doxygen.Project.
# This tag requires that the tag GENERATE_QHP is set to YES.
QHP_NAMESPACE = org.doxygen.Project
# The QHP_VIRTUAL_FOLDER tag specifies the namespace to use when generating Qt
# Help Project output. For more information please see Qt Help Project / Virtual
# Folders (see:
# https://doc.qt.io/archives/qt-4.8/qthelpproject.html#virtual-folders).
# The default value is: doc.
# This tag requires that the tag GENERATE_QHP is set to YES.
QHP_VIRTUAL_FOLDER = doc
# If the QHP_CUST_FILTER_NAME tag is set, it specifies the name of a custom
# filter to add. For more information please see Qt Help Project / Custom
# Filters (see:
# https://doc.qt.io/archives/qt-4.8/qthelpproject.html#custom-filters).
# This tag requires that the tag GENERATE_QHP is set to YES.
QHP_CUST_FILTER_NAME =
# The QHP_CUST_FILTER_ATTRS tag specifies the list of the attributes of the
# custom filter to add. For more information please see Qt Help Project / Custom
# Filters (see:
# https://doc.qt.io/archives/qt-4.8/qthelpproject.html#custom-filters).
# This tag requires that the tag GENERATE_QHP is set to YES.
QHP_CUST_FILTER_ATTRS =
# The QHP_SECT_FILTER_ATTRS tag specifies the list of the attributes this
# project's filter section matches. Qt Help Project / Filter Attributes (see:
# https://doc.qt.io/archives/qt-4.8/qthelpproject.html#filter-attributes).
# This tag requires that the tag GENERATE_QHP is set to YES.
QHP_SECT_FILTER_ATTRS =
# The QHG_LOCATION tag can be used to specify the location (absolute path
# including file name) of Qt's qhelpgenerator. If non-empty doxygen will try to
# run qhelpgenerator on the generated .qhp file.
# This tag requires that the tag GENERATE_QHP is set to YES.
QHG_LOCATION =
# If the GENERATE_ECLIPSEHELP tag is set to YES, additional index files will be
# generated, together with the HTML files, they form an Eclipse help plugin. To
# install this plugin and make it available under the help contents menu in
# Eclipse, the contents of the directory containing the HTML and XML files needs
# to be copied into the plugins directory of eclipse. The name of the directory
# within the plugins directory should be the same as the ECLIPSE_DOC_ID value.
# After copying Eclipse needs to be restarted before the help appears.
# The default value is: NO.
# This tag requires that the tag GENERATE_HTML is set to YES.
GENERATE_ECLIPSEHELP = NO
# A unique identifier for the Eclipse help plugin. When installing the plugin
# the directory name containing the HTML and XML files should also have this
# name. Each documentation set should have its own identifier.
# The default value is: org.doxygen.Project.
# This tag requires that the tag GENERATE_ECLIPSEHELP is set to YES.
ECLIPSE_DOC_ID = org.doxygen.Project
# If you want full control over the layout of the generated HTML pages it might
# be necessary to disable the index and replace it with your own. The
# DISABLE_INDEX tag can be used to turn on/off the condensed index (tabs) at top
# of each HTML page. A value of NO enables the index and the value YES disables
# it. Since the tabs in the index contain the same information as the navigation
# tree, you can set this option to YES if you also set GENERATE_TREEVIEW to YES.
# The default value is: NO.
# This tag requires that the tag GENERATE_HTML is set to YES.
DISABLE_INDEX = NO
# The GENERATE_TREEVIEW tag is used to specify whether a tree-like index
# structure should be generated to display hierarchical information. If the tag
# value is set to YES, a side panel will be generated containing a tree-like
# index structure (just like the one that is generated for HTML Help). For this
# to work a browser that supports JavaScript, DHTML, CSS and frames is required
# (i.e. any modern browser). Windows users are probably better off using the
# HTML help feature. Via custom style sheets (see HTML_EXTRA_STYLESHEET) one can
# further fine tune the look of the index (see "Fine-tuning the output"). As an
# example, the default style sheet generated by doxygen has an example that
# shows how to put an image at the root of the tree instead of the PROJECT_NAME.
# Since the tree basically has the same information as the tab index, you could
# consider setting DISABLE_INDEX to YES when enabling this option.
# The default value is: NO.
# This tag requires that the tag GENERATE_HTML is set to YES.
GENERATE_TREEVIEW = NO
# When both GENERATE_TREEVIEW and DISABLE_INDEX are set to YES, then the
# FULL_SIDEBAR option determines if the side bar is limited to only the treeview
# area (value NO) or if it should extend to the full height of the window (value
# YES). Setting this to YES gives a layout similar to
# https://docs.readthedocs.io with more room for contents, but less room for the
# project logo, title, and description. If either GENERATE_TREEVIEW or
# DISABLE_INDEX is set to NO, this option has no effect.
# The default value is: NO.
# This tag requires that the tag GENERATE_HTML is set to YES.
FULL_SIDEBAR = NO
# The ENUM_VALUES_PER_LINE tag can be used to set the number of enum values that
# doxygen will group on one line in the generated HTML documentation.
#
# Note that a value of 0 will completely suppress the enum values from appearing
# in the overview section.
# Minimum value: 0, maximum value: 20, default value: 4.
# This tag requires that the tag GENERATE_HTML is set to YES.
ENUM_VALUES_PER_LINE = 4
# If the treeview is enabled (see GENERATE_TREEVIEW) then this tag can be used
# to set the initial width (in pixels) of the frame in which the tree is shown.
# Minimum value: 0, maximum value: 1500, default value: 250.
# This tag requires that the tag GENERATE_HTML is set to YES.
TREEVIEW_WIDTH = 250
# If the EXT_LINKS_IN_WINDOW option is set to YES, doxygen will open links to
# external symbols imported via tag files in a separate window.
# The default value is: NO.
# This tag requires that the tag GENERATE_HTML is set to YES.
EXT_LINKS_IN_WINDOW = NO
# If the OBFUSCATE_EMAILS tag is set to YES, doxygen will obfuscate email
# addresses.
# The default value is: YES.
# This tag requires that the tag GENERATE_HTML is set to YES.
OBFUSCATE_EMAILS = YES
# If the HTML_FORMULA_FORMAT option is set to svg, doxygen will use the pdf2svg
# tool (see https://github.com/dawbarton/pdf2svg) or inkscape (see
# https://inkscape.org) to generate formulas as SVG images instead of PNGs for
# the HTML output. These images will generally look nicer at scaled resolutions.
# Possible values are: png (the default) and svg (looks nicer but requires the
# pdf2svg or inkscape tool).
# The default value is: png.
# This tag requires that the tag GENERATE_HTML is set to YES.
HTML_FORMULA_FORMAT = png
# Use this tag to change the font size of LaTeX formulas included as images in
# the HTML documentation. When you change the font size after a successful
# doxygen run you need to manually remove any form_*.png images from the HTML
# output directory to force them to be regenerated.
# Minimum value: 8, maximum value: 50, default value: 10.
# This tag requires that the tag GENERATE_HTML is set to YES.
FORMULA_FONTSIZE = 10
# The FORMULA_MACROFILE can contain LaTeX \newcommand and \renewcommand commands
# to create new LaTeX commands to be used in formulas as building blocks. See
# the section "Including formulas" for details.
FORMULA_MACROFILE =
# Enable the USE_MATHJAX option to render LaTeX formulas using MathJax (see
# https://www.mathjax.org) which uses client side JavaScript for the rendering
# instead of using pre-rendered bitmaps. Use this if you do not have LaTeX
# installed or if you want to formulas look prettier in the HTML output. When
# enabled you may also need to install MathJax separately and configure the path
# to it using the MATHJAX_RELPATH option.
# The default value is: NO.
# This tag requires that the tag GENERATE_HTML is set to YES.
USE_MATHJAX = NO
# With MATHJAX_VERSION it is possible to specify the MathJax version to be used.
# Note that the different versions of MathJax have different requirements with
# regards to the different settings, so it is possible that also other MathJax
# settings have to be changed when switching between the different MathJax
# versions.
# Possible values are: MathJax_2 and MathJax_3.
# The default value is: MathJax_2.
# This tag requires that the tag USE_MATHJAX is set to YES.
MATHJAX_VERSION = MathJax_2
# When MathJax is enabled you can set the default output format to be used for
# the MathJax output. For more details about the output format see MathJax
# version 2 (see:
# http://docs.mathjax.org/en/v2.7-latest/output.html) and MathJax version 3
# (see:
# http://docs.mathjax.org/en/latest/web/components/output.html).
# Possible values are: HTML-CSS (which is slower, but has the best
# compatibility. This is the name for Mathjax version 2, for MathJax version 3
# this will be translated into chtml), NativeMML (i.e. MathML. Only supported
# for NathJax 2. For MathJax version 3 chtml will be used instead.), chtml (This
# is the name for Mathjax version 3, for MathJax version 2 this will be
# translated into HTML-CSS) and SVG.
# The default value is: HTML-CSS.
# This tag requires that the tag USE_MATHJAX is set to YES.
MATHJAX_FORMAT = HTML-CSS
# When MathJax is enabled you need to specify the location relative to the HTML
# output directory using the MATHJAX_RELPATH option. The destination directory
# should contain the MathJax.js script. For instance, if the mathjax directory
# is located at the same level as the HTML output directory, then
# MATHJAX_RELPATH should be ../mathjax. The default value points to the MathJax
# Content Delivery Network so you can quickly see the result without installing
# MathJax. However, it is strongly recommended to install a local copy of
# MathJax from https://www.mathjax.org before deployment. The default value is:
# - in case of MathJax version 2: https://cdn.jsdelivr.net/npm/mathjax@2
# - in case of MathJax version 3: https://cdn.jsdelivr.net/npm/mathjax@3
# This tag requires that the tag USE_MATHJAX is set to YES.
MATHJAX_RELPATH =
# The MATHJAX_EXTENSIONS tag can be used to specify one or more MathJax
# extension names that should be enabled during MathJax rendering. For example
# for MathJax version 2 (see
# https://docs.mathjax.org/en/v2.7-latest/tex.html#tex-and-latex-extensions):
# MATHJAX_EXTENSIONS = TeX/AMSmath TeX/AMSsymbols
# For example for MathJax version 3 (see
# http://docs.mathjax.org/en/latest/input/tex/extensions/index.html):
# MATHJAX_EXTENSIONS = ams
# This tag requires that the tag USE_MATHJAX is set to YES.
MATHJAX_EXTENSIONS =
# The MATHJAX_CODEFILE tag can be used to specify a file with javascript pieces
# of code that will be used on startup of the MathJax code. See the MathJax site
# (see:
# http://docs.mathjax.org/en/v2.7-latest/output.html) for more details. For an
# example see the documentation.
# This tag requires that the tag USE_MATHJAX is set to YES.
MATHJAX_CODEFILE =
# When the SEARCHENGINE tag is enabled doxygen will generate a search box for
# the HTML output. The underlying search engine uses javascript and DHTML and
# should work on any modern browser. Note that when using HTML help
# (GENERATE_HTMLHELP), Qt help (GENERATE_QHP), or docsets (GENERATE_DOCSET)
# there is already a search function so this one should typically be disabled.
# For large projects the javascript based search engine can be slow, then
# enabling SERVER_BASED_SEARCH may provide a better solution. It is possible to
# search using the keyboard; to jump to the search box use <access key> + S
# (what the <access key> is depends on the OS and browser, but it is typically
# <CTRL>, <ALT>/<option>, or both). Inside the search box use the <cursor down
# key> to jump into the search results window, the results can be navigated
# using the <cursor keys>. Press <Enter> to select an item or <escape> to cancel
# the search. The filter options can be selected when the cursor is inside the
# search box by pressing <Shift>+<cursor down>. Also here use the <cursor keys>
# to select a filter and <Enter> or <escape> to activate or cancel the filter
# option.
# The default value is: YES.
# This tag requires that the tag GENERATE_HTML is set to YES.
SEARCHENGINE = YES
# When the SERVER_BASED_SEARCH tag is enabled the search engine will be
# implemented using a web server instead of a web client using JavaScript. There
# are two flavors of web server based searching depending on the EXTERNAL_SEARCH
# setting. When disabled, doxygen will generate a PHP script for searching and
# an index file used by the script. When EXTERNAL_SEARCH is enabled the indexing
# and searching needs to be provided by external tools. See the section
# "External Indexing and Searching" for details.
# The default value is: NO.
# This tag requires that the tag SEARCHENGINE is set to YES.
SERVER_BASED_SEARCH = NO
# When EXTERNAL_SEARCH tag is enabled doxygen will no longer generate the PHP
# script for searching. Instead the search results are written to an XML file
# which needs to be processed by an external indexer. Doxygen will invoke an
# external search engine pointed to by the SEARCHENGINE_URL option to obtain the
# search results.
#
# Doxygen ships with an example indexer (doxyindexer) and search engine
# (doxysearch.cgi) which are based on the open source search engine library
# Xapian (see:
# https://xapian.org/).
#
# See the section "External Indexing and Searching" for details.
# The default value is: NO.
# This tag requires that the tag SEARCHENGINE is set to YES.
EXTERNAL_SEARCH = NO
# The SEARCHENGINE_URL should point to a search engine hosted by a web server
# which will return the search results when EXTERNAL_SEARCH is enabled.
#
# Doxygen ships with an example indexer (doxyindexer) and search engine
# (doxysearch.cgi) which are based on the open source search engine library
# Xapian (see:
# https://xapian.org/). See the section "External Indexing and Searching" for
# details.
# This tag requires that the tag SEARCHENGINE is set to YES.
SEARCHENGINE_URL =
# When SERVER_BASED_SEARCH and EXTERNAL_SEARCH are both enabled the unindexed
# search data is written to a file for indexing by an external tool. With the
# SEARCHDATA_FILE tag the name of this file can be specified.
# The default file is: searchdata.xml.
# This tag requires that the tag SEARCHENGINE is set to YES.
SEARCHDATA_FILE = searchdata.xml
# When SERVER_BASED_SEARCH and EXTERNAL_SEARCH are both enabled the
# EXTERNAL_SEARCH_ID tag can be used as an identifier for the project. This is
# useful in combination with EXTRA_SEARCH_MAPPINGS to search through multiple
# projects and redirect the results back to the right project.
# This tag requires that the tag SEARCHENGINE is set to YES.
EXTERNAL_SEARCH_ID =
# The EXTRA_SEARCH_MAPPINGS tag can be used to enable searching through doxygen
# projects other than the one defined by this configuration file, but that are
# all added to the same external search index. Each project needs to have a
# unique id set via EXTERNAL_SEARCH_ID. The search mapping then maps the id of
# to a relative location where the documentation can be found. The format is:
# EXTRA_SEARCH_MAPPINGS = tagname1=loc1 tagname2=loc2 ...
# This tag requires that the tag SEARCHENGINE is set to YES.
EXTRA_SEARCH_MAPPINGS =
#---------------------------------------------------------------------------
# Configuration options related to the LaTeX output
#---------------------------------------------------------------------------
# If the GENERATE_LATEX tag is set to YES, doxygen will generate LaTeX output.
# The default value is: YES.
GENERATE_LATEX = NO
# The LATEX_OUTPUT tag is used to specify where the LaTeX docs will be put. If a
# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of
# it.
# The default directory is: latex.
# This tag requires that the tag GENERATE_LATEX is set to YES.
LATEX_OUTPUT = latex
# The LATEX_CMD_NAME tag can be used to specify the LaTeX command name to be
# invoked.
#
# Note that when not enabling USE_PDFLATEX the default is latex when enabling
# USE_PDFLATEX the default is pdflatex and when in the later case latex is
# chosen this is overwritten by pdflatex. For specific output languages the
# default can have been set differently, this depends on the implementation of
# the output language.
# This tag requires that the tag GENERATE_LATEX is set to YES.
LATEX_CMD_NAME =
# The MAKEINDEX_CMD_NAME tag can be used to specify the command name to generate
# index for LaTeX.
# Note: This tag is used in the Makefile / make.bat.
# See also: LATEX_MAKEINDEX_CMD for the part in the generated output file
# (.tex).
# The default file is: makeindex.
# This tag requires that the tag GENERATE_LATEX is set to YES.
MAKEINDEX_CMD_NAME = makeindex
# The LATEX_MAKEINDEX_CMD tag can be used to specify the command name to
# generate index for LaTeX. In case there is no backslash (\) as first character
# it will be automatically added in the LaTeX code.
# Note: This tag is used in the generated output file (.tex).
# See also: MAKEINDEX_CMD_NAME for the part in the Makefile / make.bat.
# The default value is: makeindex.
# This tag requires that the tag GENERATE_LATEX is set to YES.
LATEX_MAKEINDEX_CMD = makeindex
# If the COMPACT_LATEX tag is set to YES, doxygen generates more compact LaTeX
# documents. This may be useful for small projects and may help to save some
# trees in general.
# The default value is: NO.
# This tag requires that the tag GENERATE_LATEX is set to YES.
COMPACT_LATEX = NO
# The PAPER_TYPE tag can be used to set the paper type that is used by the
# printer.
# Possible values are: a4 (210 x 297 mm), letter (8.5 x 11 inches), legal (8.5 x
# 14 inches) and executive (7.25 x 10.5 inches).
# The default value is: a4.
# This tag requires that the tag GENERATE_LATEX is set to YES.
PAPER_TYPE = a4
# The EXTRA_PACKAGES tag can be used to specify one or more LaTeX package names
# that should be included in the LaTeX output. The package can be specified just
# by its name or with the correct syntax as to be used with the LaTeX
# \usepackage command. To get the times font for instance you can specify :
# EXTRA_PACKAGES=times or EXTRA_PACKAGES={times}
# To use the option intlimits with the amsmath package you can specify:
# EXTRA_PACKAGES=[intlimits]{amsmath}
# If left blank no extra packages will be included.
# This tag requires that the tag GENERATE_LATEX is set to YES.
EXTRA_PACKAGES =
# The LATEX_HEADER tag can be used to specify a user-defined LaTeX header for
# the generated LaTeX document. The header should contain everything until the
# first chapter. If it is left blank doxygen will generate a standard header. It
# is highly recommended to start with a default header using
# doxygen -w latex new_header.tex new_footer.tex new_stylesheet.sty
# and then modify the file new_header.tex. See also section "Doxygen usage" for
# information on how to generate the default header that doxygen normally uses.
#
# Note: Only use a user-defined header if you know what you are doing!
# Note: The header is subject to change so you typically have to regenerate the
# default header when upgrading to a newer version of doxygen. The following
# commands have a special meaning inside the header (and footer): For a
# description of the possible markers and block names see the documentation.
# This tag requires that the tag GENERATE_LATEX is set to YES.
LATEX_HEADER =
# The LATEX_FOOTER tag can be used to specify a user-defined LaTeX footer for
# the generated LaTeX document. The footer should contain everything after the
# last chapter. If it is left blank doxygen will generate a standard footer. See
# LATEX_HEADER for more information on how to generate a default footer and what
# special commands can be used inside the footer. See also section "Doxygen
# usage" for information on how to generate the default footer that doxygen
# normally uses. Note: Only use a user-defined footer if you know what you are
# doing!
# This tag requires that the tag GENERATE_LATEX is set to YES.
LATEX_FOOTER =
# The LATEX_EXTRA_STYLESHEET tag can be used to specify additional user-defined
# LaTeX style sheets that are included after the standard style sheets created
# by doxygen. Using this option one can overrule certain style aspects. Doxygen
# will copy the style sheet files to the output directory.
# Note: The order of the extra style sheet files is of importance (e.g. the last
# style sheet in the list overrules the setting of the previous ones in the
# list).
# This tag requires that the tag GENERATE_LATEX is set to YES.
LATEX_EXTRA_STYLESHEET =
# The LATEX_EXTRA_FILES tag can be used to specify one or more extra images or
# other source files which should be copied to the LATEX_OUTPUT output
# directory. Note that the files will be copied as-is; there are no commands or
# markers available.
# This tag requires that the tag GENERATE_LATEX is set to YES.
LATEX_EXTRA_FILES =
# If the PDF_HYPERLINKS tag is set to YES, the LaTeX that is generated is
# prepared for conversion to PDF (using ps2pdf or pdflatex). The PDF file will
# contain links (just like the HTML output) instead of page references. This
# makes the output suitable for online browsing using a PDF viewer.
# The default value is: YES.
# This tag requires that the tag GENERATE_LATEX is set to YES.
PDF_HYPERLINKS = YES
# If the USE_PDFLATEX tag is set to YES, doxygen will use the engine as
# specified with LATEX_CMD_NAME to generate the PDF file directly from the LaTeX
# files. Set this option to YES, to get a higher quality PDF documentation.
#
# See also section LATEX_CMD_NAME for selecting the engine.
# The default value is: YES.
# This tag requires that the tag GENERATE_LATEX is set to YES.
USE_PDFLATEX = YES
# The LATEX_BATCHMODE tag ignals the behavior of LaTeX in case of an error.
# Possible values are: NO same as ERROR_STOP, YES same as BATCH, BATCH In batch
# mode nothing is printed on the terminal, errors are scrolled as if <return> is
# hit at every error; missing files that TeX tries to input or request from
# keyboard input (\read on a not open input stream) cause the job to abort,
# NON_STOP In nonstop mode the diagnostic message will appear on the terminal,
# but there is no possibility of user interaction just like in batch mode,
# SCROLL In scroll mode, TeX will stop only for missing files to input or if
# keyboard input is necessary and ERROR_STOP In errorstop mode, TeX will stop at
# each error, asking for user intervention.
# The default value is: NO.
# This tag requires that the tag GENERATE_LATEX is set to YES.
LATEX_BATCHMODE = NO
# If the LATEX_HIDE_INDICES tag is set to YES then doxygen will not include the
# index chapters (such as File Index, Compound Index, etc.) in the output.
# The default value is: NO.
# This tag requires that the tag GENERATE_LATEX is set to YES.
LATEX_HIDE_INDICES = NO
# The LATEX_BIB_STYLE tag can be used to specify the style to use for the
# bibliography, e.g. plainnat, or ieeetr. See
# https://en.wikipedia.org/wiki/BibTeX and \cite for more info.
# The default value is: plain.
# This tag requires that the tag GENERATE_LATEX is set to YES.
LATEX_BIB_STYLE = plain
# The LATEX_EMOJI_DIRECTORY tag is used to specify the (relative or absolute)
# path from which the emoji images will be read. If a relative path is entered,
# it will be relative to the LATEX_OUTPUT directory. If left blank the
# LATEX_OUTPUT directory will be used.
# This tag requires that the tag GENERATE_LATEX is set to YES.
LATEX_EMOJI_DIRECTORY =
#---------------------------------------------------------------------------
# Configuration options related to the RTF output
#---------------------------------------------------------------------------
# If the GENERATE_RTF tag is set to YES, doxygen will generate RTF output. The
# RTF output is optimized for Word 97 and may not look too pretty with other RTF
# readers/editors.
# The default value is: NO.
GENERATE_RTF = NO
# The RTF_OUTPUT tag is used to specify where the RTF docs will be put. If a
# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of
# it.
# The default directory is: rtf.
# This tag requires that the tag GENERATE_RTF is set to YES.
RTF_OUTPUT = rtf
# If the COMPACT_RTF tag is set to YES, doxygen generates more compact RTF
# documents. This may be useful for small projects and may help to save some
# trees in general.
# The default value is: NO.
# This tag requires that the tag GENERATE_RTF is set to YES.
COMPACT_RTF = NO
# If the RTF_HYPERLINKS tag is set to YES, the RTF that is generated will
# contain hyperlink fields. The RTF file will contain links (just like the HTML
# output) instead of page references. This makes the output suitable for online
# browsing using Word or some other Word compatible readers that support those
# fields.
#
# Note: WordPad (write) and others do not support links.
# The default value is: NO.
# This tag requires that the tag GENERATE_RTF is set to YES.
RTF_HYPERLINKS = NO
# Load stylesheet definitions from file. Syntax is similar to doxygen's
# configuration file, i.e. a series of assignments. You only have to provide
# replacements, missing definitions are set to their default value.
#
# See also section "Doxygen usage" for information on how to generate the
# default style sheet that doxygen normally uses.
# This tag requires that the tag GENERATE_RTF is set to YES.
RTF_STYLESHEET_FILE =
# Set optional variables used in the generation of an RTF document. Syntax is
# similar to doxygen's configuration file. A template extensions file can be
# generated using doxygen -e rtf extensionFile.
# This tag requires that the tag GENERATE_RTF is set to YES.
RTF_EXTENSIONS_FILE =
#---------------------------------------------------------------------------
# Configuration options related to the man page output
#---------------------------------------------------------------------------
# If the GENERATE_MAN tag is set to YES, doxygen will generate man pages for
# classes and files.
# The default value is: NO.
GENERATE_MAN = NO
# The MAN_OUTPUT tag is used to specify where the man pages will be put. If a
# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of
# it. A directory man3 will be created inside the directory specified by
# MAN_OUTPUT.
# The default directory is: man.
# This tag requires that the tag GENERATE_MAN is set to YES.
MAN_OUTPUT = man
# The MAN_EXTENSION tag determines the extension that is added to the generated
# man pages. In case the manual section does not start with a number, the number
# 3 is prepended. The dot (.) at the beginning of the MAN_EXTENSION tag is
# optional.
# The default value is: .3.
# This tag requires that the tag GENERATE_MAN is set to YES.
MAN_EXTENSION = .3
# The MAN_SUBDIR tag determines the name of the directory created within
# MAN_OUTPUT in which the man pages are placed. If defaults to man followed by
# MAN_EXTENSION with the initial . removed.
# This tag requires that the tag GENERATE_MAN is set to YES.
MAN_SUBDIR =
# If the MAN_LINKS tag is set to YES and doxygen generates man output, then it
# will generate one additional man file for each entity documented in the real
# man page(s). These additional files only source the real man page, but without
# them the man command would be unable to find the correct page.
# The default value is: NO.
# This tag requires that the tag GENERATE_MAN is set to YES.
MAN_LINKS = NO
#---------------------------------------------------------------------------
# Configuration options related to the XML output
#---------------------------------------------------------------------------
# If the GENERATE_XML tag is set to YES, doxygen will generate an XML file that
# captures the structure of the code including all documentation.
# The default value is: NO.
GENERATE_XML = YES
# The XML_OUTPUT tag is used to specify where the XML pages will be put. If a
# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of
# it.
# The default directory is: xml.
# This tag requires that the tag GENERATE_XML is set to YES.
XML_OUTPUT = xml
# If the XML_PROGRAMLISTING tag is set to YES, doxygen will dump the program
# listings (including syntax highlighting and cross-referencing information) to
# the XML output. Note that enabling this will significantly increase the size
# of the XML output.
# The default value is: YES.
# This tag requires that the tag GENERATE_XML is set to YES.
XML_PROGRAMLISTING = YES
# If the XML_NS_MEMB_FILE_SCOPE tag is set to YES, doxygen will include
# namespace members in file scope as well, matching the HTML output.
# The default value is: NO.
# This tag requires that the tag GENERATE_XML is set to YES.
XML_NS_MEMB_FILE_SCOPE = NO
#---------------------------------------------------------------------------
# Configuration options related to the DOCBOOK output
#---------------------------------------------------------------------------
# If the GENERATE_DOCBOOK tag is set to YES, doxygen will generate Docbook files
# that can be used to generate PDF.
# The default value is: NO.
GENERATE_DOCBOOK = NO
# The DOCBOOK_OUTPUT tag is used to specify where the Docbook pages will be put.
# If a relative path is entered the value of OUTPUT_DIRECTORY will be put in
# front of it.
# The default directory is: docbook.
# This tag requires that the tag GENERATE_DOCBOOK is set to YES.
DOCBOOK_OUTPUT = docbook
#---------------------------------------------------------------------------
# Configuration options for the AutoGen Definitions output
#---------------------------------------------------------------------------
# If the GENERATE_AUTOGEN_DEF tag is set to YES, doxygen will generate an
# AutoGen Definitions (see https://autogen.sourceforge.net/) file that captures
# the structure of the code including all documentation. Note that this feature
# is still experimental and incomplete at the moment.
# The default value is: NO.
GENERATE_AUTOGEN_DEF = NO
#---------------------------------------------------------------------------
# Configuration options related to Sqlite3 output
#---------------------------------------------------------------------------
#---------------------------------------------------------------------------
# Configuration options related to the Perl module output
#---------------------------------------------------------------------------
# If the GENERATE_PERLMOD tag is set to YES, doxygen will generate a Perl module
# file that captures the structure of the code including all documentation.
#
# Note that this feature is still experimental and incomplete at the moment.
# The default value is: NO.
GENERATE_PERLMOD = NO
# If the PERLMOD_LATEX tag is set to YES, doxygen will generate the necessary
# Makefile rules, Perl scripts and LaTeX code to be able to generate PDF and DVI
# output from the Perl module output.
# The default value is: NO.
# This tag requires that the tag GENERATE_PERLMOD is set to YES.
PERLMOD_LATEX = NO
# If the PERLMOD_PRETTY tag is set to YES, the Perl module output will be nicely
# formatted so it can be parsed by a human reader. This is useful if you want to
# understand what is going on. On the other hand, if this tag is set to NO, the
# size of the Perl module output will be much smaller and Perl will parse it
# just the same.
# The default value is: YES.
# This tag requires that the tag GENERATE_PERLMOD is set to YES.
PERLMOD_PRETTY = YES
# The names of the make variables in the generated doxyrules.make file are
# prefixed with the string contained in PERLMOD_MAKEVAR_PREFIX. This is useful
# so different doxyrules.make files included by the same Makefile don't
# overwrite each other's variables.
# This tag requires that the tag GENERATE_PERLMOD is set to YES.
PERLMOD_MAKEVAR_PREFIX =
#---------------------------------------------------------------------------
# Configuration options related to the preprocessor
#---------------------------------------------------------------------------
# If the ENABLE_PREPROCESSING tag is set to YES, doxygen will evaluate all
# C-preprocessor directives found in the sources and include files.
# The default value is: YES.
ENABLE_PREPROCESSING = YES
# If the MACRO_EXPANSION tag is set to YES, doxygen will expand all macro names
# in the source code. If set to NO, only conditional compilation will be
# performed. Macro expansion can be done in a controlled way by setting
# EXPAND_ONLY_PREDEF to YES.
# The default value is: NO.
# This tag requires that the tag ENABLE_PREPROCESSING is set to YES.
MACRO_EXPANSION = YES
# If the EXPAND_ONLY_PREDEF and MACRO_EXPANSION tags are both set to YES then
# the macro expansion is limited to the macros specified with the PREDEFINED and
# EXPAND_AS_DEFINED tags.
# The default value is: NO.
# This tag requires that the tag ENABLE_PREPROCESSING is set to YES.
EXPAND_ONLY_PREDEF = YES
# If the SEARCH_INCLUDES tag is set to YES, the include files in the
# INCLUDE_PATH will be searched if a #include is found.
# The default value is: YES.
# This tag requires that the tag ENABLE_PREPROCESSING is set to YES.
SEARCH_INCLUDES = YES
# The INCLUDE_PATH tag can be used to specify one or more directories that
# contain include files that are not input files but should be processed by the
# preprocessor. Note that the INCLUDE_PATH is not recursive, so the setting of
# RECURSIVE has no effect here.
# This tag requires that the tag SEARCH_INCLUDES is set to YES.
INCLUDE_PATH =
# You can use the INCLUDE_FILE_PATTERNS tag to specify one or more wildcard
# patterns (like *.h and *.hpp) to filter out the header-files in the
# directories. If left blank, the patterns specified with FILE_PATTERNS will be
# used.
# This tag requires that the tag ENABLE_PREPROCESSING is set to YES.
INCLUDE_FILE_PATTERNS =
# The PREDEFINED tag can be used to specify one or more macro names that are
# defined before the preprocessor is started (similar to the -D option of e.g.
# gcc). The argument of the tag is a list of macros of the form: name or
# name=definition (no spaces). If the definition and the "=" are omitted, "=1"
# is assumed. To prevent a macro definition from being undefined via #undef or
# recursively expanded use the := operator instead of the = operator.
# This tag requires that the tag ENABLE_PREPROCESSING is set to YES.
PREDEFINED = MMDEPLOY_API=
# If the MACRO_EXPANSION and EXPAND_ONLY_PREDEF tags are set to YES then this
# tag can be used to specify a list of macro names that should be expanded. The
# macro definition that is found in the sources will be used. Use the PREDEFINED
# tag if you want to use a different macro definition that overrules the
# definition found in the source code.
# This tag requires that the tag ENABLE_PREPROCESSING is set to YES.
EXPAND_AS_DEFINED =
# If the SKIP_FUNCTION_MACROS tag is set to YES then doxygen's preprocessor will
# remove all references to function-like macros that are alone on a line, have
# an all uppercase name, and do not end with a semicolon. Such function macros
# are typically used for boiler-plate code, and will confuse the parser if not
# removed.
# The default value is: YES.
# This tag requires that the tag ENABLE_PREPROCESSING is set to YES.
SKIP_FUNCTION_MACROS = YES
#---------------------------------------------------------------------------
# Configuration options related to external references
#---------------------------------------------------------------------------
# The TAGFILES tag can be used to specify one or more tag files. For each tag
# file the location of the external documentation should be added. The format of
# a tag file without this location is as follows:
# TAGFILES = file1 file2 ...
# Adding location for the tag files is done as follows:
# TAGFILES = file1=loc1 "file2 = loc2" ...
# where loc1 and loc2 can be relative or absolute paths or URLs. See the
# section "Linking to external documentation" for more information about the use
# of tag files.
# Note: Each tag file must have a unique name (where the name does NOT include
# the path). If a tag file is not located in the directory in which doxygen is
# run, you must also specify the path to the tagfile here.
TAGFILES =
# When a file name is specified after GENERATE_TAGFILE, doxygen will create a
# tag file that is based on the input files it reads. See section "Linking to
# external documentation" for more information about the usage of tag files.
GENERATE_TAGFILE =
# If the ALLEXTERNALS tag is set to YES, all external class will be listed in
# the class index. If set to NO, only the inherited external classes will be
# listed.
# The default value is: NO.
ALLEXTERNALS = NO
# If the EXTERNAL_GROUPS tag is set to YES, all external groups will be listed
# in the modules index. If set to NO, only the current project's groups will be
# listed.
# The default value is: YES.
EXTERNAL_GROUPS = YES
# If the EXTERNAL_PAGES tag is set to YES, all external pages will be listed in
# the related pages index. If set to NO, only the current project's pages will
# be listed.
# The default value is: YES.
EXTERNAL_PAGES = YES
#---------------------------------------------------------------------------
# Configuration options related to diagram generator tools
#---------------------------------------------------------------------------
# If set to YES the inheritance and collaboration graphs will hide inheritance
# and usage relations if the target is undocumented or is not a class.
# The default value is: YES.
HIDE_UNDOC_RELATIONS = YES
# If you set the HAVE_DOT tag to YES then doxygen will assume the dot tool is
# available from the path. This tool is part of Graphviz (see:
# https://www.graphviz.org/), a graph visualization toolkit from AT&T and Lucent
# Bell Labs. The other options in this section have no effect if this option is
# set to NO
# The default value is: NO.
HAVE_DOT = NO
# The DOT_NUM_THREADS specifies the number of dot invocations doxygen is allowed
# to run in parallel. When set to 0 doxygen will base this on the number of
# processors available in the system. You can set it explicitly to a value
# larger than 0 to get control over the balance between CPU load and processing
# speed.
# Minimum value: 0, maximum value: 32, default value: 0.
# This tag requires that the tag HAVE_DOT is set to YES.
DOT_NUM_THREADS = 0
# DOT_COMMON_ATTR is common attributes for nodes, edges and labels of
# subgraphs. When you want a differently looking font in the dot files that
# doxygen generates you can specify fontname, fontcolor and fontsize attributes.
# For details please see <a href=https://graphviz.org/doc/info/attrs.html>Node,
# Edge and Graph Attributes specification</a> You need to make sure dot is able
# to find the font, which can be done by putting it in a standard location or by
# setting the DOTFONTPATH environment variable or by setting DOT_FONTPATH to the
# directory containing the font. Default graphviz fontsize is 14.
# The default value is: fontname=Helvetica,fontsize=10.
# This tag requires that the tag HAVE_DOT is set to YES.
DOT_COMMON_ATTR = "fontname=Helvetica,fontsize=10"
# DOT_EDGE_ATTR is concatenated with DOT_COMMON_ATTR. For elegant style you can
# add 'arrowhead=open, arrowtail=open, arrowsize=0.5'. <a
# href=https://graphviz.org/doc/info/arrows.html>Complete documentation about
# arrows shapes.</a>
# The default value is: labelfontname=Helvetica,labelfontsize=10.
# This tag requires that the tag HAVE_DOT is set to YES.
DOT_EDGE_ATTR = "labelfontname=Helvetica,labelfontsize=10"
# DOT_NODE_ATTR is concatenated with DOT_COMMON_ATTR. For view without boxes
# around nodes set 'shape=plain' or 'shape=plaintext' <a
# href=https://www.graphviz.org/doc/info/shapes.html>Shapes specification</a>
# The default value is: shape=box,height=0.2,width=0.4.
# This tag requires that the tag HAVE_DOT is set to YES.
DOT_NODE_ATTR = "shape=box,height=0.2,width=0.4"
# You can set the path where dot can find font specified with fontname in
# DOT_COMMON_ATTR and others dot attributes.
# This tag requires that the tag HAVE_DOT is set to YES.
DOT_FONTPATH =
# If the CLASS_GRAPH tag is set to YES or GRAPH or BUILTIN then doxygen will
# generate a graph for each documented class showing the direct and indirect
# inheritance relations. In case the CLASS_GRAPH tag is set to YES or GRAPH and
# HAVE_DOT is enabled as well, then dot will be used to draw the graph. In case
# the CLASS_GRAPH tag is set to YES and HAVE_DOT is disabled or if the
# CLASS_GRAPH tag is set to BUILTIN, then the built-in generator will be used.
# If the CLASS_GRAPH tag is set to TEXT the direct and indirect inheritance
# relations will be shown as texts / links.
# Possible values are: NO, YES, TEXT, GRAPH and BUILTIN.
# The default value is: YES.
CLASS_GRAPH = YES
# If the COLLABORATION_GRAPH tag is set to YES then doxygen will generate a
# graph for each documented class showing the direct and indirect implementation
# dependencies (inheritance, containment, and class references variables) of the
# class with other documented classes.
# The default value is: YES.
# This tag requires that the tag HAVE_DOT is set to YES.
COLLABORATION_GRAPH = YES
# If the GROUP_GRAPHS tag is set to YES then doxygen will generate a graph for
# groups, showing the direct groups dependencies. See also the chapter Grouping
# in the manual.
# The default value is: YES.
# This tag requires that the tag HAVE_DOT is set to YES.
GROUP_GRAPHS = YES
# If the UML_LOOK tag is set to YES, doxygen will generate inheritance and
# collaboration diagrams in a style similar to the OMG's Unified Modeling
# Language.
# The default value is: NO.
# This tag requires that the tag HAVE_DOT is set to YES.
UML_LOOK = NO
# If the UML_LOOK tag is enabled, the fields and methods are shown inside the
# class node. If there are many fields or methods and many nodes the graph may
# become too big to be useful. The UML_LIMIT_NUM_FIELDS threshold limits the
# number of items for each type to make the size more manageable. Set this to 0
# for no limit. Note that the threshold may be exceeded by 50% before the limit
# is enforced. So when you set the threshold to 10, up to 15 fields may appear,
# but if the number exceeds 15, the total amount of fields shown is limited to
# 10.
# Minimum value: 0, maximum value: 100, default value: 10.
# This tag requires that the tag UML_LOOK is set to YES.
UML_LIMIT_NUM_FIELDS = 10
# If the DOT_UML_DETAILS tag is set to NO, doxygen will show attributes and
# methods without types and arguments in the UML graphs. If the DOT_UML_DETAILS
# tag is set to YES, doxygen will add type and arguments for attributes and
# methods in the UML graphs. If the DOT_UML_DETAILS tag is set to NONE, doxygen
# will not generate fields with class member information in the UML graphs. The
# class diagrams will look similar to the default class diagrams but using UML
# notation for the relationships.
# Possible values are: NO, YES and NONE.
# The default value is: NO.
# This tag requires that the tag UML_LOOK is set to YES.
DOT_UML_DETAILS = NO
# The DOT_WRAP_THRESHOLD tag can be used to set the maximum number of characters
# to display on a single line. If the actual line length exceeds this threshold
# significantly it will wrapped across multiple lines. Some heuristics are apply
# to avoid ugly line breaks.
# Minimum value: 0, maximum value: 1000, default value: 17.
# This tag requires that the tag HAVE_DOT is set to YES.
DOT_WRAP_THRESHOLD = 17
# If the TEMPLATE_RELATIONS tag is set to YES then the inheritance and
# collaboration graphs will show the relations between templates and their
# instances.
# The default value is: NO.
# This tag requires that the tag HAVE_DOT is set to YES.
TEMPLATE_RELATIONS = NO
# If the INCLUDE_GRAPH, ENABLE_PREPROCESSING and SEARCH_INCLUDES tags are set to
# YES then doxygen will generate a graph for each documented file showing the
# direct and indirect include dependencies of the file with other documented
# files.
# The default value is: YES.
# This tag requires that the tag HAVE_DOT is set to YES.
INCLUDE_GRAPH = YES
# If the INCLUDED_BY_GRAPH, ENABLE_PREPROCESSING and SEARCH_INCLUDES tags are
# set to YES then doxygen will generate a graph for each documented file showing
# the direct and indirect include dependencies of the file with other documented
# files.
# The default value is: YES.
# This tag requires that the tag HAVE_DOT is set to YES.
INCLUDED_BY_GRAPH = YES
# If the CALL_GRAPH tag is set to YES then doxygen will generate a call
# dependency graph for every global function or class method.
#
# Note that enabling this option will significantly increase the time of a run.
# So in most cases it will be better to enable call graphs for selected
# functions only using the \callgraph command. Disabling a call graph can be
# accomplished by means of the command \hidecallgraph.
# The default value is: NO.
# This tag requires that the tag HAVE_DOT is set to YES.
CALL_GRAPH = NO
# If the CALLER_GRAPH tag is set to YES then doxygen will generate a caller
# dependency graph for every global function or class method.
#
# Note that enabling this option will significantly increase the time of a run.
# So in most cases it will be better to enable caller graphs for selected
# functions only using the \callergraph command. Disabling a caller graph can be
# accomplished by means of the command \hidecallergraph.
# The default value is: NO.
# This tag requires that the tag HAVE_DOT is set to YES.
CALLER_GRAPH = NO
# If the GRAPHICAL_HIERARCHY tag is set to YES then doxygen will graphical
# hierarchy of all classes instead of a textual one.
# The default value is: YES.
# This tag requires that the tag HAVE_DOT is set to YES.
GRAPHICAL_HIERARCHY = YES
# If the DIRECTORY_GRAPH tag is set to YES then doxygen will show the
# dependencies a directory has on other directories in a graphical way. The
# dependency relations are determined by the #include relations between the
# files in the directories.
# The default value is: YES.
# This tag requires that the tag HAVE_DOT is set to YES.
DIRECTORY_GRAPH = YES
# The DIR_GRAPH_MAX_DEPTH tag can be used to limit the maximum number of levels
# of child directories generated in directory dependency graphs by dot.
# Minimum value: 1, maximum value: 25, default value: 1.
# This tag requires that the tag DIRECTORY_GRAPH is set to YES.
DIR_GRAPH_MAX_DEPTH = 1
# The DOT_IMAGE_FORMAT tag can be used to set the image format of the images
# generated by dot. For an explanation of the image formats see the section
# output formats in the documentation of the dot tool (Graphviz (see:
# https://www.graphviz.org/)).
# Note: If you choose svg you need to set HTML_FILE_EXTENSION to xhtml in order
# to make the SVG files visible in IE 9+ (other browsers do not have this
# requirement).
# Possible values are: png, jpg, gif, svg, png:gd, png:gd:gd, png:cairo,
# png:cairo:gd, png:cairo:cairo, png:cairo:gdiplus, png:gdiplus and
# png:gdiplus:gdiplus.
# The default value is: png.
# This tag requires that the tag HAVE_DOT is set to YES.
DOT_IMAGE_FORMAT = png
# If DOT_IMAGE_FORMAT is set to svg, then this option can be set to YES to
# enable generation of interactive SVG images that allow zooming and panning.
#
# Note that this requires a modern browser other than Internet Explorer. Tested
# and working are Firefox, Chrome, Safari, and Opera.
# Note: For IE 9+ you need to set HTML_FILE_EXTENSION to xhtml in order to make
# the SVG files visible. Older versions of IE do not have SVG support.
# The default value is: NO.
# This tag requires that the tag HAVE_DOT is set to YES.
INTERACTIVE_SVG = NO
# The DOT_PATH tag can be used to specify the path where the dot tool can be
# found. If left blank, it is assumed the dot tool can be found in the path.
# This tag requires that the tag HAVE_DOT is set to YES.
DOT_PATH =
# The DOTFILE_DIRS tag can be used to specify one or more directories that
# contain dot files that are included in the documentation (see the \dotfile
# command).
# This tag requires that the tag HAVE_DOT is set to YES.
DOTFILE_DIRS =
# You can include diagrams made with dia in doxygen documentation. Doxygen will
# then run dia to produce the diagram and insert it in the documentation. The
# DIA_PATH tag allows you to specify the directory where the dia binary resides.
# If left empty dia is assumed to be found in the default search path.
DIA_PATH =
# The DIAFILE_DIRS tag can be used to specify one or more directories that
# contain dia files that are included in the documentation (see the \diafile
# command).
DIAFILE_DIRS =
# When using plantuml, the PLANTUML_JAR_PATH tag should be used to specify the
# path where java can find the plantuml.jar file or to the filename of jar file
# to be used. If left blank, it is assumed PlantUML is not used or called during
# a preprocessing step. Doxygen will generate a warning when it encounters a
# \startuml command in this case and will not generate output for the diagram.
PLANTUML_JAR_PATH =
# When using plantuml, the PLANTUML_CFG_FILE tag can be used to specify a
# configuration file for plantuml.
PLANTUML_CFG_FILE =
# When using plantuml, the specified paths are searched for files specified by
# the !include statement in a plantuml block.
PLANTUML_INCLUDE_PATH =
# The DOT_GRAPH_MAX_NODES tag can be used to set the maximum number of nodes
# that will be shown in the graph. If the number of nodes in a graph becomes
# larger than this value, doxygen will truncate the graph, which is visualized
# by representing a node as a red box. Note that doxygen if the number of direct
# children of the root node in a graph is already larger than
# DOT_GRAPH_MAX_NODES then the graph will not be shown at all. Also note that
# the size of a graph can be further restricted by MAX_DOT_GRAPH_DEPTH.
# Minimum value: 0, maximum value: 10000, default value: 50.
# This tag requires that the tag HAVE_DOT is set to YES.
DOT_GRAPH_MAX_NODES = 50
# The MAX_DOT_GRAPH_DEPTH tag can be used to set the maximum depth of the graphs
# generated by dot. A depth value of 3 means that only nodes reachable from the
# root by following a path via at most 3 edges will be shown. Nodes that lay
# further from the root node will be omitted. Note that setting this option to 1
# or 2 may greatly reduce the computation time needed for large code bases. Also
# note that the size of a graph can be further restricted by
# DOT_GRAPH_MAX_NODES. Using a depth of 0 means no depth restriction.
# Minimum value: 0, maximum value: 1000, default value: 0.
# This tag requires that the tag HAVE_DOT is set to YES.
MAX_DOT_GRAPH_DEPTH = 0
# Set the DOT_MULTI_TARGETS tag to YES to allow dot to generate multiple output
# files in one run (i.e. multiple -o and -T options on the command line). This
# makes dot run faster, but since only newer versions of dot (>1.8.10) support
# this, this feature is disabled by default.
# The default value is: NO.
# This tag requires that the tag HAVE_DOT is set to YES.
DOT_MULTI_TARGETS = NO
# If the GENERATE_LEGEND tag is set to YES doxygen will generate a legend page
# explaining the meaning of the various boxes and arrows in the dot generated
# graphs.
# Note: This tag requires that UML_LOOK isn't set, i.e. the doxygen internal
# graphical representation for inheritance and collaboration diagrams is used.
# The default value is: YES.
# This tag requires that the tag HAVE_DOT is set to YES.
GENERATE_LEGEND = YES
# If the DOT_CLEANUP tag is set to YES, doxygen will remove the intermediate
# files that are used to generate the various graphs.
#
# Note: This setting is not only used for dot files but also for msc temporary
# files.
# The default value is: YES.
DOT_CLEANUP = YES
# You can define message sequence charts within doxygen comments using the \msc
# command. If the MSCGEN_TOOL tag is left empty (the default), then doxygen will
# use a built-in version of mscgen tool to produce the charts. Alternatively,
# the MSCGEN_TOOL tag can also specify the name an external tool. For instance,
# specifying prog as the value, doxygen will call the tool as prog -T
# <outfile_format> -o <outputfile> <inputfile>. The external tool should support
# output file formats "png", "eps", "svg", and "ismap".
MSCGEN_TOOL =
# The MSCFILE_DIRS tag can be used to specify one or more directories that
# contain msc files that are included in the documentation (see the \mscfile
# command).
MSCFILE_DIRS =
docs/en/01-how-to-build/android.md 0 → 100644
View file @ 4353fa59
# Build for Android
- [Build for Android](#build-for-android)
- [Build From Source](#build-from-source)
- [Install Toolchains](#install-toolchains)
- [Install Dependencies](#install-dependencies)
- [Install Dependencies for SDK](#install-dependencies-for-sdk)
- [Build MMDeploy](#build-mmdeploy)
- [Build SDK and Demos](#build-sdk-and-demos)
______________________________________________________________________
MMDeploy provides cross compile for android platform.
Model converter is executed on linux platform, and SDK is executed on android platform.
Here are two steps for android build.
1. Build model converter on linux, please refer to [How to build linux](linux-x86_64.md)
2. Build SDK using android toolchain on linux.
This doc is only for how to build SDK using android toolchain on linux.
## Build From Source
### Install Toolchains
- cmake
**Make sure cmake version >= 3.14.0**. If not, you can follow instructions below to install cmake 3.20.0. For more versions of cmake, please refer to [cmake website](https://cmake.org/install).
```bash
wget https://github.com/Kitware/CMake/releases/download/v3.20.0/cmake-3.20.0-linux-x86_64.tar.gz
tar -xzvf cmake-3.20.0-linux-x86_64.tar.gz
sudo ln -sf $(pwd)/cmake-3.20.0-linux-x86_64/bin/* /usr/bin/
```
- ANDROID NDK 19+
**Make sure android ndk version >= 19.0**. If not, you can follow instructions below to install android ndk r23c. For more versions of android ndk, please refer to [android ndk website](https://developer.android.com/ndk/downloads).
```bash
wget https://dl.google.com/android/repository/android-ndk-r23c-linux.zip
unzip android-ndk-r23c-linux.zip
cd android-ndk-r23c
export NDK_PATH=${PWD}
```
### Install Dependencies
#### Install Dependencies for SDK
You can skip this chapter if only interested in model converter.
<table>
<thead>
<tr>
<th>NAME </th>
<th>INSTALLATION </th>
</tr>
</thead>
<tbody>
<tr>
<td>OpenCV<br>(>=3.0) </td>
<td>
<pre><code>
export OPENCV_VERSION=4.6.0
wget https://github.com/opencv/opencv/releases/download/${OPENCV_VERSION}/opencv-${OPENCV_VERSION}-android-sdk.zip
unzip opencv-${OPENCV_VERSION}-android-sdk.zip
export OPENCV_ANDROID_SDK_DIR=${PWD}/OpenCV-android-sdk
</code></pre>
</td>
</tr>
<tr>
<td>ncnn </td>
<td>A high-performance neural network inference computing framework supporting for android.</br>
<b> Now, MMDeploy supports 20220721 and has to use <code>git clone</code> to download it. For supported android ABI, see <a href='https://github.com/Tencent/ncnn/releases'> here </a>. </b><br>
<pre><code>
git clone -b 20220721 https://github.com/Tencent/ncnn.git
cd ncnn
git submodule update --init
export NCNN_DIR=${PWD}
export ANDROID_ABI=arm64-v8a
mkdir -p build\_${ANDROID_ABI}
cd build\_${ANDROID_ABI}
cmake -DCMAKE_TOOLCHAIN_FILE=${NDK_PATH}/build/cmake/android.toolchain.cmake -DANDROID_ABI="${ANDROID_ABI}" -DANDROID_PLATFORM=android-30 -DNCNN_VULKAN=ON -DNCNN_DISABLE_EXCEPTION=OFF -DNCNN_DISABLE_RTTI=OFF -DANDROID_USE_LEGACY_TOOLCHAIN_FILE=False ..
make -j$(nproc) install
</code></pre>
</td>
</tr>
<tr>
<td>OpenJDK </td>
<td>It is necessary for building Java API.</br>
See <a href='https://github.com/open-mmlab/mmdeploy/tree/main/csrc/mmdeploy/apis/java/README.md'> Java API build </a> for building tutorials.
</td>
</tr>
</tbody>
</table>
### Build MMDeploy
#### Build SDK and Demos
MMDeploy provides a recipe as shown below for building SDK with ncnn as inference engine for android.
- cpu + ncnn
```Bash
export ANDROID_ABI=arm64-v8a
cd ${MMDEPLOY_DIR}
mkdir -p build_${ANDROID_ABI} && cd build_${ANDROID_ABI}
cmake .. \
-DMMDEPLOY_BUILD_SDK=ON \
-DMMDEPLOY_BUILD_SDK_JAVA_API=ON \
-DMMDEPLOY_BUILD_EXAMPLES=ON \
-DOpenCV_DIR=${OPENCV_ANDROID_SDK_DIR}/sdk/native/jni/abi-${ANDROID_ABI} \
-Dncnn_DIR=${NCNN_DIR}/build_${ANDROID_ABI}/install/lib/cmake/ncnn \
-DMMDEPLOY_TARGET_BACKENDS=ncnn \
-DMMDEPLOY_SHARED_LIBS=OFF \
-DCMAKE_TOOLCHAIN_FILE=${NDK_PATH}/build/cmake/android.toolchain.cmake \
-DANDROID_USE_LEGACY_TOOLCHAIN_FILE=False \
-DANDROID_ABI=${ANDROID_ABI} \
-DANDROID_PLATFORM=android-30 \
-DANDROID_CPP_FEATURES="rtti exceptions"
make -j$(nproc) && make install
```
Please check [cmake build option spec](cmake_option.md)
docs/en/01-how-to-build/build_from_docker.md 0 → 100644
View file @ 4353fa59
# Use Docker Image
This document guides how to install mmdeploy with [Docker](https://docs.docker.com/get-docker/).
## Get prebuilt docker images
MMDeploy provides prebuilt docker images for the convenience of its users on [Docker Hub](https://hub.docker.com/r/openmmlab/mmdeploy). The docker images are built on
the latest and released versions. For instance, the image with tag `openmmlab/mmdeploy:ubuntu20.04-cuda11.8-mmdeploy` is built on the latest mmdeploy and the image with tag `openmmlab/mmdeploy:ubuntu20.04-cuda11.8-mmdeploy1.2.0` is for `mmdeploy==1.2.0`.
The specifications of the Docker Image are shown below.
| Item | Version |
| :---------: | :---------: |
| OS | Ubuntu20.04 |
| CUDA | 11.8 |
| CUDNN | 8.9 |
| Python | 3.8.10 |
| Torch | 2.0.0 |
| TorchVision | 0.15.0 |
| TorchScript | 2.0.0 |
| TensorRT | 8.6.1.6 |
| ONNXRuntime | 1.15.1 |
| OpenVINO | 2022.3.0 |
| ncnn | 20230816 |
| openppl | 0.8.1 |
You can select a [tag](https://hub.docker.com/r/openmmlab/mmdeploy/tags) and run `docker pull` to get the docker image:
```shell
export TAG=openmmlab/mmdeploy:ubuntu20.04-cuda11.8-mmdeploy
docker pull $TAG
```
## Build docker images (optional)
If the prebuilt docker images do not meet your requirements,
then you can build your own image by running the following script.
The docker file is `docker/Release/Dockerfile`and its building argument is `MMDEPLOY_VERSION`,
which can be a [tag](https://github.com/open-mmlab/mmdeploy/tags) or a branch from [mmdeploy](https://github.com/open-mmlab/mmdeploy).
```shell
export MMDEPLOY_VERSION=main
export TAG=mmdeploy-${MMDEPLOY_VERSION}
docker build docker/Release/ -t ${TAG} --build-arg MMDEPLOY_VERSION=${MMDEPLOY_VERSION}
```
## Run docker container
After pulling or building the docker image, you can use `docker run` to launch the docker service:
```shell
export TAG=openmmlab/mmdeploy:ubuntu20.04-cuda11.8-mmdeploy
docker run --gpus=all -it --rm $TAG
```
## FAQs
1. CUDA error: the provided PTX was compiled with an unsupported toolchain:
As described [here](https://forums.developer.nvidia.com/t/cuda-error-the-provided-ptx-was-compiled-with-an-unsupported-toolchain/185754), update the GPU driver to the latest one for your GPU.
2. docker: Error response from daemon: could not select device driver "" with capabilities: [gpu].
```shell
# Add the package repositories
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
sudo systemctl restart docker
```
docs/en/01-how-to-build/build_from_script.md 0 → 100644
View file @ 4353fa59
# Build from Script
Through user investigation, we know that most users are already familiar with python and torch before using mmdeploy. Therefore we provide scripts to simplify mmdeploy installation.
Assuming you already have
- python3 -m pip (`conda` or `pyenv`)
- nvcc (depends on inference backend)
- torch (not compulsory)
run this script to install mmdeploy + ncnn backend, `nproc` is not compulsory.
```bash
$ cd /path/to/mmdeploy
$ python3 tools/scripts/build_ubuntu_x64_ncnn.py
..
```
A sudo password may be required during this time, and the script will try its best to build and install mmdeploy SDK and demo:
- Detect host OS version, `make` job number, whether use `root` and try to fix `python3 -m pip`
- Find the necessary basic tools, such as g++-7, cmake, wget, etc.
- Compile necessary dependencies, such as pyncnn, protobuf
The script will also try to avoid affecting host environment:
- The dependencies of source code compilation are placed in the `mmdeploy-dep` directory at the same level as mmdeploy
- The script would not modify variables such as PATH, LD_LIBRARY_PATH, PYTHONPATH, etc.
- The environment variables that need to be modified will be printed, **please pay attention to the final output**
The script will eventually execute `python3 tools/check_env.py`, the successful installation should display the version number of the corresponding backend and `ops_is_available: True`, for example:
```bash
$ python3 tools/check_env.py
..
2022-09-13 14:49:13,767 - mmdeploy - INFO - **********Backend information**********
2022-09-13 14:49:14,116 - mmdeploy - INFO - onnxruntime: 1.8.0 ops_is_avaliable : True
2022-09-13 14:49:14,131 - mmdeploy - INFO - tensorrt: 8.4.1.5 ops_is_avaliable : True
2022-09-13 14:49:14,139 - mmdeploy - INFO - ncnn: 1.0.20220901 ops_is_avaliable : True
2022-09-13 14:49:14,150 - mmdeploy - INFO - pplnn_is_avaliable: True
..
```
Here is the verified installation script. If you want mmdeploy to support multiple backends at the same time, you can execute each script once:
| script | OS version |
| :-----------------------------: | :-----------------: |
| build_ubuntu_x64_ncnn.py | 18.04/20.04 |
| build_ubuntu_x64_ort.py | 18.04/20.04 |
| build_ubuntu_x64_pplnn.py | 18.04/20.04 |
| build_ubuntu_x64_torchscript.py | 18.04/20.04 |
| build_ubuntu_x64_tvm.py | 18.04/20.04 |
| build_jetson_orin_python38.sh | JetPack5.0 L4T 34.1 |
docs/en/01-how-to-build/build_from_source.md 0 → 100644
View file @ 4353fa59
# Build from Source
## Download
```shell
git clone -b main git@github.com:open-mmlab/mmdeploy.git --recursive
```
Note:
- If fetching submodule fails, you could get submodule manually by following instructions:
```shell
cd mmdeploy
git clone git@github.com:NVIDIA/cub.git third_party/cub
cd third_party/cub
git checkout c3cceac115
# go back to third_party directory and git clone pybind11
cd ..
git clone git@github.com:pybind/pybind11.git pybind11
cd pybind11
git checkout 70a58c5
cd ..
git clone git@github.com:gabime/spdlog.git spdlog
cd spdlog
git checkout 9e8e52c048
```
- If it fails when `git clone` via `SSH`, you can try the `HTTPS` protocol like this:
```shell
git clone -b main https://github.com/open-mmlab/mmdeploy.git --recursive
```
## Build
Please visit the following links to find out how to build MMDeploy according to the target platform.
- [Linux-x86_64](linux-x86_64.md)
- [Windows](windows.md)
- [MacOS](macos-arm64.md)
- [Android-aarch64](android.md)
- [NVIDIA Jetson](jetsons.md)
- [SNPE](snpe.md)
- [RISC-V](riscv.md)
- [Rockchip](rockchip.md)
docs/en/01-how-to-build/cmake_option.md 0 → 100644
View file @ 4353fa59
# CMake Build Option Spec
<table class="docutils">
<thead>
<tr>
<th>NAME</th>
<th>VALUE</th>
<th>DEFAULT</th>
<th>REMARK</th>
</tr>
</thead>
<tbody>
<tr>
<td>MMDEPLOY_SHARED_LIBS</td>
<td>{ON, OFF}</td>
<td>ON</td>
<td>Switch to build shared libs</td>
</tr>
<tr>
<td>MMDEPLOY_BUILD_SDK</td>
<td>{ON, OFF}</td>
<td>OFF</td>
<td>Switch to build MMDeploy SDK</td>
</tr>
<tr>
<td>MMDEPLOY_BUILD_SDK_MONOLITHIC</td>
<td>{ON, OFF}</td>
<td>OFF</td>
<td>Build single lib</td>
</tr>
<tr>
<td>MMDEPLOY_BUILD_TEST</td>
<td>{ON, OFF}</td>
<td>OFF</td>
<td>Build unittest</td>
</tr>
<tr>
<td>MMDEPLOY_BUILD_SDK_PYTHON_API</td>
<td>{ON, OFF}</td>
<td>OFF</td>
<td>Switch to build MMDeploy SDK python package</td>
</tr>
<tr>
<td>MMDEPLOY_BUILD_SDK_CSHARP_API</td>
<td>{ON, OFF}</td>
<td>OFF</td>
<td>Build C# SDK API</td>
</tr>
<tr>
<td>MMDEPLOY_BUILD_SDK_JAVA_API</td>
<td>{ON, OFF}</td>
<td>OFF</td>
<td>Build Java SDK API</td>
</tr>
<tr>
<td>MMDEPLOY_BUILD_TEST</td>
<td>{ON, OFF}</td>
<td>OFF</td>
<td>Switch to build MMDeploy SDK unittest cases</td>
</tr>
<tr>
<td>MMDEPLOY_SPDLOG_EXTERNAL</td>
<td>{ON, OFF}</td>
<td>OFF</td>
<td>Build with spdlog installation package that comes with the system</td>
</tr>
<tr>
<td>MMDEPLOY_ZIP_MODEL</td>
<td>{ON, OFF}</td>
<td>OFF</td>
<td>Enable SDK with zip format</td>
</tr>
<tr>
<td>MMDEPLOY_COVERAGE</td>
<td>{ON, OFF}</td>
<td>OFF</td>
<td>Build for cplus code coverage report</td>
</tr>
<tr>
<td>MMDEPLOY_TARGET_DEVICES</td>
<td>{"cpu", "cuda"}</td>
<td>cpu</td>
<td>Enable target device. You can enable more by
passing a semicolon separated list of device names to <code>MMDEPLOY_TARGET_DEVICES</code> variable, e.g. <code>-DMMDEPLOY_TARGET_DEVICES="cpu;cuda"</code> </td>
</tr>
<tr>
<td>MMDEPLOY_TARGET_BACKENDS</td>
<td>{"trt", "ort", "pplnn", "ncnn", "openvino", "torchscript", "snpe", "tvm"}</td>
<td>N/A</td>
<td>Enabling inference engine. <b>By default, no target inference engine is set, since it highly depends on the use case.</b> When more than one engine are specified, it has to be set with a semicolon separated list of inference backend names, e.g. <pre><code>-DMMDEPLOY_TARGET_BACKENDS="trt;ort;pplnn;ncnn;openvino"</code></pre>
After specifying the inference engine, it's package path has to be passed to cmake as follows, <br>
1. <b>trt</b>: TensorRT. <code>TENSORRT_DIR</code> and <code>CUDNN_DIR</code> are needed.
<pre><code>
-DTENSORRT_DIR=${TENSORRT_DIR}
-DCUDNN_DIR=${CUDNN_DIR}
</code></pre>
2. <b>ort</b>: ONNXRuntime. <code>ONNXRUNTIME_DIR</code> is needed.
<pre><code>-DONNXRUNTIME_DIR=${ONNXRUNTIME_DIR}</code></pre>
3. <b>pplnn</b>: PPL.NN. <code>pplnn_DIR</code> is needed.
<pre><code>-Dpplnn_DIR=${PPLNN_DIR}</code></pre>
4. <b>ncnn</b>: ncnn. <code>ncnn_DIR</code> is needed.
<pre><code>-Dncnn_DIR=${NCNN_DIR}/build/install/lib/cmake/ncnn</code></pre>
5. <b>openvino</b>: OpenVINO. <code>InferenceEngine_DIR</code> is needed.
<pre><code>-DInferenceEngine_DIR=${INTEL_OPENVINO_DIR}/deployment_tools/inference_engine/share</code></pre>
6. <b>torchscript</b>: TorchScript. <code>Torch_DIR</code> is needed.
<pre><code>-DTorch_DIR=${Torch_DIR}</code></pre>
7. <b>snpe</b>: qcom snpe. <code>SNPE_ROOT</code> must existed in the environment variable because of C/S mode.<br>
8. <b>coreml</b>: CoreML. <code>Torch_DIR</code> is required.
<pre><code>-DTorch_DIR=${Torch_DIR}</code></pre>
9. <b>TVM</b>: TVM. <code>TVM_DIR</code> is required. <pre><code>-DTVM_DIR=${TVM_DIR}</code></pre>
</td>
</tr>
<tr>
<td>MMDEPLOY_CODEBASES</td>
<td>{"mmpretrain", "mmdet", "mmseg", "mmagic", "mmocr", "all"}</td>
<td>all</td>
<td>Enable codebase's postprocess modules. You can provide a semicolon separated list of codebase names to enable them, e.g., <code>-DMMDEPLOY_CODEBASES="mmpretrain;mmdet"</code>. Or you can pass <code>all</code> to enable them all, i.e., <code>-DMMDEPLOY_CODEBASES=all</code></td>
</tr>
</tbody>
</table>
docs/en/01-how-to-build/cross_build_ncnn_aarch64.md 0 → 100644
View file @ 4353fa59
# Ubuntu Cross Build aarch64
mmdeploy chose ncnn as the inference backend for aarch64 embedded linux devices. There are two parts:
Host
- model conversion
- cross build SDK and demo for embedded devices
Device
- Run converted model
## 1. Model Convert on Host
Refer to the doc to install [mmdeploy](../01-how-to-build/) and [mmpretrain](https://github.com/open-mmlab/mmpretrain), and convert resnet18 for model package
```bash
export MODEL_CONFIG=/path/to/mmpretrain/configs/resnet/resnet18_8xb32_in1k.py
export MODEL_PATH=https://download.openmmlab.com/mmclassification/v0/resnet/resnet18_8xb32_in1k_20210831-fbbb1da6.pth
# Convert resnet18
cd /path/to/mmdeploy
python tools/deploy.py \
configs/mmpretrain/classification_ncnn_static.py \
$MODEL_CONFIG \
$MODEL_PATH \
tests/data/tiger.jpeg \
--work-dir resnet18 \
--device cpu \
--dump-info
```
## 2. Cross Build on Host
It is recommended to compile directly with the script
```bash
sh -x tools/scripts/ubuntu_cross_build_aarch64.sh
```
The following is the manual process corresponding to the script:
a) Install aarch64 build tools
```bash
sudo apt install -y gcc-aarch64-linux-gnu g++-aarch64-linux-gnu
```
b) Cross build opencv and install to /tmp/ocv-aarch64
```bash
git clone https://github.com/opencv/opencv --depth=1 --branch=4.x --recursive
cd opencv/platforms/linux/
mkdir build && cd build
cmake ../../.. \
-DCMAKE_INSTALL_PREFIX=/tmp/ocv-aarch64 \
-DCMAKE_TOOLCHAIN_FILE=../aarch64-gnu.toolchain.cmake
make -j && make install
ls -alh /tmp/ocv-aarch64
..
```
c) Cross build ncnn and install to /tmp/ncnn-aarch64
```bash
git clone https://github.com/tencent/ncnn --branch 20221128 --depth=1
mkdir build && cd build
cmake .. \
-DCMAKE_TOOLCHAIN_FILE=../toolchains/aarch64-linux-gnu.toolchain.cmake \
-DCMAKE_INSTALL_PREFIX=/tmp/ncnn-aarch64
make -j && make install
ls -alh /tmp/ncnn-aarch64
..
```
d) Cross build mmdeploy
```bash
git submodule init
git submodule update
mkdir build && cd build
cmake .. \
-DCMAKE_TOOLCHAIN_FILE=../cmake/toolchains/aarch64-linux-gnu.cmake \
-DMMDEPLOY_TARGET_DEVICES="cpu" \
-DMMDEPLOY_TARGET_BACKENDS="ncnn" \
-Dncnn_DIR=/tmp/ncnn-aarch64/lib/cmake/ncnn \
-DOpenCV_DIR=/tmp/ocv-aarch64/lib/cmake/opencv4
make install
ls -lah install/bin/*
..
```
## 3. Execute on Device
Make sure that `--dump-info` is used during model conversion, so that the `resnet18` directory contains the files required by the SDK such as `pipeline.json`.
Copy the model folder(resnet18), executable(image_classification) file, test image(tests/data/tiger.jpeg) and prebuilt OpenCV(/tmp/ocv-aarch64) to the device.
```bash
./image_classification cpu ./resnet18 tiger.jpeg
..
label: 292, score: 0.9261
label: 282, score: 0.0726
label: 290, score: 0.0008
label: 281, score: 0.0002
label: 340, score: 0.0001
```
docs/en/01-how-to-build/jetsons.md 0 → 100644
View file @ 4353fa59
# Build for Jetson
In this chapter, we introduce how to install MMDeploy on NVIDIA Jetson platforms, which we have verified on the following modules:
- Jetson Nano
- Jetson TX2
- Jetson AGX Xavier
Hardware recommendation:
- [Seeed reComputer built with Jetson Nano module](https://www.seeedstudio.com/Jetson-10-1-A0-p-5336.html)
- [Seeed reComputer built with Jetson Xavier NX module](https://www.seeedstudio.com/Jetson-20-1-H1-p-5328.html)
## Prerequisites
- To equip a Jetson device, JetPack SDK is a must.
- The Model Converter of MMDeploy requires an environment with PyTorch for converting PyTorch models to ONNX models.
- Regarding the toolchain, CMake and GCC has to be upgraded to no less than 3.14 and 7.0 respectively.
### JetPack SDK
JetPack SDK provides a full development environment for hardware-accelerated AI-at-the-edge development.
All Jetson modules and developer kits are supported by JetPack SDK.
There are two major installation methods including,
1. SD Card Image Method
2. NVIDIA SDK Manager Method
You can find a very detailed installation guide from NVIDIA [official website](https://developer.nvidia.com/jetpack-sdk-461).
```{note}
Please select the option to install "Jetson SDK Components" when using NVIDIA SDK Manager as this includes CUDA and TensorRT which are needed for this guide.
```
Here we have chosen [JetPack 4.6.1](https://developer.nvidia.com/jetpack-sdk-461) as our best practice on setting up Jetson platforms. MMDeploy has been tested on JetPack 4.6 (rev.3) and above and TensorRT 8.0.1.6 and above. Earlier JetPack versions has incompatibilities with TensorRT 7.x
### Conda
Install [Archiconda](https://github.com/Archiconda/build-tools/releases) instead of Anaconda because the latter does not provide the wheel built for Jetson.
```shell
wget https://github.com/Archiconda/build-tools/releases/download/0.2.3/Archiconda3-0.2.3-Linux-aarch64.sh
bash Archiconda3-0.2.3-Linux-aarch64.sh -b
echo -e '\n# set environment variable for conda' >> ~/.bashrc
echo ". ~/archiconda3/etc/profile.d/conda.sh" >> ~/.bashrc
echo 'export PATH=$PATH:~/archiconda3/bin' >> ~/.bashrc
echo -e '\n# set environment variable for pip' >> ~/.bashrc
echo 'export OPENBLAS_CORETYPE=ARMV8' >> ~/.bashrc
source ~/.bashrc
conda --version
```
After the installation, create a conda environment and activate it.
```shell
# get the version of python3 installed by default
export PYTHON_VERSION=`python3 --version | cut -d' ' -f 2 | cut -d'.' -f1,2`
conda create -y -n mmdeploy python=${PYTHON_VERSION}
conda activate mmdeploy
```
```{note}
JetPack SDK 4+ provides Python 3.6. We strongly recommend using the default Python. Trying to upgrade it will probably ruin the JetPack environment.
If a higher-version of Python is necessary, you can install JetPack 5+, in which the Python version is 3.8.
```
### PyTorch
Download the PyTorch wheel for Jetson from [here](https://forums.developer.nvidia.com/t/pytorch-for-jetson-version-1-11-now-available/72048) and save it to the `/home/username` directory. Build torchvision from source as there is no prebuilt torchvision for Jetson platforms.
Take `torch 1.10.0` and `torchvision 0.11.1` for example. You can install them as below:
```shell
# pytorch
wget https://nvidia.box.com/shared/static/fjtbno0vpo676a25cgvuqc1wty0fkkg6.whl -O torch-1.10.0-cp36-cp36m-linux_aarch64.whl
pip3 install torch-1.10.0-cp36-cp36m-linux_aarch64.whl
# torchvision
sudo apt-get install libjpeg-dev zlib1g-dev libpython3-dev libavcodec-dev libavformat-dev libswscale-dev libopenblas-base libopenmpi-dev libopenblas-dev -y
git clone --branch v0.11.1 https://github.com/pytorch/vision torchvision
cd torchvision
export BUILD_VERSION=0.11.1
pip install -e .
```
```{note}
It takes about 30 minutes to install torchvision on a Jetson Nano. So, please be patient until the installation is complete.
```
If you install other versions of PyTorch and torchvision, make sure the versions are compatible. Refer to the compatibility chart listed [here](https://pypi.org/project/torchvision/).
### CMake
We use the latest cmake v3.23.1 released in April 2022.
```shell
# purge existing
sudo apt-get purge cmake -y
# install prebuilt binary
export CMAKE_VER=3.23.1
export ARCH=aarch64
wget https://github.com/Kitware/CMake/releases/download/v${CMAKE_VER}/cmake-${CMAKE_VER}-linux-${ARCH}.sh
chmod +x cmake-${CMAKE_VER}-linux-${ARCH}.sh
sudo ./cmake-${CMAKE_VER}-linux-${ARCH}.sh --prefix=/usr --skip-license
cmake --version
```
## Install Dependencies
The Model Converter of MMDeploy on Jetson platforms depends on [MMCV](https://github.com/open-mmlab/mmcv) and the inference engine [TensorRT](https://developer.nvidia.com/tensorrt).
While MMDeploy C/C++ Inference SDK relies on [spdlog](https://github.com/gabime/spdlog), OpenCV and [ppl.cv](https://github.com/openppl-public/ppl.cv) and so on, as well as TensorRT.
Thus, in the following sections, we will describe how to prepare TensorRT.
And then, we will present the way to install dependencies of Model Converter and C/C++ Inference SDK respectively.
### Prepare TensorRT
TensorRT is already packed into JetPack SDK. But In order to import it successfully in conda environment, we need to copy the tensorrt package to the conda environment created before.
```shell
cp -r /usr/lib/python${PYTHON_VERSION}/dist-packages/tensorrt* ~/archiconda3/envs/mmdeploy/lib/python${PYTHON_VERSION}/site-packages/
conda deactivate
conda activate mmdeploy
python -c "import tensorrt; print(tensorrt.__version__)" # Will print the version of TensorRT
# set environment variable for building mmdeploy later on
export TENSORRT_DIR=/usr/include/aarch64-linux-gnu
# append cuda path and libraries to PATH and LD_LIBRARY_PATH, which is also used for building mmdeploy later on.
# this is not needed if you use NVIDIA SDK Manager with "Jetson SDK Components" for installing JetPack.
# this is only needed if you install JetPack using SD Card Image Method.
export PATH=$PATH:/usr/local/cuda/bin
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64
```
You can also make the above environment variables permanent by adding them to `~/.bashrc`.
```shell
echo -e '\n# set environment variable for TensorRT' >> ~/.bashrc
echo 'export TENSORRT_DIR=/usr/include/aarch64-linux-gnu' >> ~/.bashrc
# this is not needed if you use NVIDIA SDK Manager with "Jetson SDK Components" for installing JetPack.
# this is only needed if you install JetPack using SD Card Image Method.
echo -e '\n# set environment variable for CUDA' >> ~/.bashrc
echo 'export PATH=$PATH:/usr/local/cuda/bin' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64' >> ~/.bashrc
source ~/.bashrc
conda activate mmdeploy
```
### Install Dependencies for Model Converter
#### Install MMCV
[MMCV](https://github.com/open-mmlab/mmcv) has not provided prebuilt package for Jetson platforms, so we have to build it from source.
```shell
sudo apt-get install -y libssl-dev
git clone --branch 2.x https://github.com/open-mmlab/mmcv.git
cd mmcv
MMCV_WITH_OPS=1 pip install -e .
```
```{note}
It takes about 1 hour 40 minutes to install MMCV on a Jetson Nano. So, please be patient until the installation is complete.
```
#### Install ONNX
Don't install the latest ONNX. The recommended ONNX version is 1.10.0.
```shell
# Execute one of the following commands
pip install onnx==1.10.0
conda install -c conda-forge onnx
```
If the installation failed and showed the following error:
```
CMake Error at CMakeLists.txt:299 (message):
Protobuf compiler not found
```
Please install dependencies:
```shell
sudo apt-get install protobuf-compiler libprotoc-dev
```
#### Install ONNX Runtime [Optional]
Go to [Jetson_Zoo#ONNX_Runtime](https://elinux.org/Jetson_Zoo#ONNX_Runtime) to find **right version** of onnx runtime. Then download and install package.
For example:
```
# Download pip wheel from location mentioned above
$ wget https://nvidia.box.com/shared/static/jy7nqva7l88mq9i8bw3g3sklzf4kccn2.whl -O onnxruntime_gpu-1.10.0-cp36-cp36m-linux_aarch64.whl
# Install pip wheel
$ pip3 install onnxruntime_gpu-1.10.0-cp36-cp36m-linux_aarch64.whl
```
#### Install h5py and pycuda
Model Converter employs HDF5 to save the calibration data for TensorRT INT8 quantization and needs `pycuda` to copy device memory.
```shell
sudo apt-get install -y pkg-config libhdf5-100 libhdf5-dev
pip install versioned-hdf5 pycuda
```
```{note}
It takes about 6 minutes to install versioned-hdf5 on a Jetson Nano. So, please be patient until the installation is complete.
```
### Install Dependencies for C/C++ Inference SDK
#### Install spdlog
[spdlog](https://github.com/gabime/spdlog) is a very fast, header-only/compiled, C++ logging library
```shell
sudo apt-get install -y libspdlog-dev
```
#### Install ppl.cv
[ppl.cv](https://github.com/openppl-public/ppl.cv) is a high-performance image processing library of [openPPL](https://openppl.ai/home)
```shell
git clone https://github.com/openppl-public/ppl.cv.git
cd ppl.cv
export PPLCV_DIR=$(pwd)
echo -e '\n# set environment variable for ppl.cv' >> ~/.bashrc
echo "export PPLCV_DIR=$(pwd)" >> ~/.bashrc
./build.sh cuda
```
```{note}
It takes about 15 minutes to install ppl.cv on a Jetson Nano. So, please be patient until the installation is complete.
```
## Install MMDeploy
```shell
git clone -b main --recursive https://github.com/open-mmlab/mmdeploy.git
cd mmdeploy
export MMDEPLOY_DIR=$(pwd)
```
### Install Model Converter
Since some operators adopted by OpenMMLab codebases are not supported by TensorRT, we build the custom TensorRT plugins to make it up, such as `roi_align`, `scatternd`, etc.
You can find a full list of custom plugins from [here](../06-custom-ops/tensorrt.md).
```shell
# build TensorRT custom operators
mkdir -p build && cd build
cmake .. -DMMDEPLOY_TARGET_BACKENDS="trt"
make -j$(nproc) && make install
# install model converter
cd ${MMDEPLOY_DIR}
pip install -v -e .
# "-v" means verbose, or more output
# "-e" means installing a project in editable mode,
# thus any local modifications made to the code will take effect without re-installation.
```
```{note}
It takes about 5 minutes to install model converter on a Jetson Nano. So, please be patient until the installation is complete.
```
### Install C/C++ Inference SDK
Build SDK Libraries and its demo as below:
```shell
mkdir -p build && cd build
cmake .. \
-DMMDEPLOY_BUILD_SDK=ON \
-DMMDEPLOY_BUILD_SDK_PYTHON_API=ON \
-DMMDEPLOY_BUILD_EXAMPLES=ON \
-DMMDEPLOY_TARGET_DEVICES="cuda;cpu" \
-DMMDEPLOY_TARGET_BACKENDS="trt" \
-DMMDEPLOY_CODEBASES=all \
-Dpplcv_DIR=${PPLCV_DIR}/cuda-build/install/lib/cmake/ppl
make -j$(nproc) && make install
```
```{note}
It takes about 9 minutes to build SDK libraries on a Jetson Nano. So, please be patient until the installation is complete.
```
### Run a Demo
#### Object Detection demo
Before running this demo, you need to convert model files to be able to use with this SDK.
1. Install [MMDetection](https://github.com/open-mmlab/mmdetection) which is needed for model conversion
MMDetection is an open source object detection toolbox based on PyTorch
```shell
git clone -b 3.x https://github.com/open-mmlab/mmdetection.git
cd mmdetection
pip install -r requirements/build.txt
pip install -v -e . # or "python setup.py develop"
```
2. Follow [this document](../02-how-to-run/convert_model.md) on how to convert model files.
For this example, we have used [retinanet_r18_fpn_1x_coco.py](https://github.com/open-mmlab/mmdetection/blob/3.x/configs/retinanet/retinanet_r18_fpn_1x_coco.py) as the model config, and [this file](https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_r18_fpn_1x_coco/retinanet_r18_fpn_1x_coco_20220407_171055-614fd399.pth) as the corresponding checkpoint file. Also for deploy config, we have used [detection_tensorrt_dynamic-320x320-1344x1344.py](https://github.com/open-mmlab/mmdeploy/tree/main/configs/mmdet/detection/detection_tensorrt_dynamic-320x320-1344x1344.py)
```shell
python ./tools/deploy.py \
configs/mmdet/detection/detection_tensorrt_dynamic-320x320-1344x1344.py \
$PATH_TO_MMDET/configs/retinanet/retinanet_r18_fpn_1x_coco.py \
retinanet_r18_fpn_1x_coco_20220407_171055-614fd399.pth \
$PATH_TO_MMDET/demo/demo.jpg \
--work-dir work_dir \
--show \
--device cuda:0 \
--dump-info
```
3. Finally run inference on an image
<div align=center><img width=650 src="https://files.seeedstudio.com/wiki/open-mmlab/source_image.jpg"/></div>
```shell
./object_detection cuda ${directory/to/the/converted/models} ${path/to/an/image}
```
<div align=center><img width=650 src="https://files.seeedstudio.com/wiki/open-mmlab/output_detection.png"/></div>
The above inference is done on a [Seeed reComputer built with Jetson Nano module](https://www.seeedstudio.com/Jetson-10-1-A0-p-5336.html)
## Troubleshooting
### Installation
- `pip install` throws an error like `Illegal instruction (core dumped)`
Check if you are using any mirror, if you did, try this:
```shell
rm .condarc
conda clean -i
conda create -n xxx python=${PYTHON_VERSION}
```
### Runtime
- `#assertion/root/workspace/mmdeploy/csrc/backend_ops/tensorrt/batched_nms/trt_batched_nms.cpp,98` or `pre_top_k need to be reduced for devices with arch 7.2`
1. Set `MAX N` mode and perform `sudo nvpmodel -m 0 && sudo jetson_clocks`.
2. Reduce the number of `pre_top_k` in deploy config file like [mmdet pre_top_k](https://github.com/open-mmlab/mmdeploy/blob/34879e638cc2db511e798a376b9a4b9932660fe1/configs/mmdet/_base_/base_static.py#L13) does, e.g., `1000`.
3. Convert the model again and try SDK demo again.
### FAQ
- Error `error: cannot import name 'ProcessGroup' from 'torch.distributed'.`
- Please try install pytorch 1.11 version from [pytorch-for-jetson](https://forums.developer.nvidia.com/t/pytorch-for-jetson/72048).
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment