Fix readthedocs (#2134)

* [Fix]: limit urllib3 for readthedocs (#2070)

* fix readthedocs for zh_cn

* fix

.circleci/scripts/linux/build.sh

@@ -6,7 +6,7 @@ cd mmdeploy
 MMDEPLOY_DIR=$(pwd)
 mkdir -p build && cd build
 cmake .. -DMMDEPLOY_BUILD_SDK=ON -DMMDEPLOY_BUILD_TEST=ON -DMMDEPLOY_BUILD_SDK_PYTHON_API=ON \
-         -DMMDEPLOY_BUILD_EXAMPLES=ON -DMMDEPLOY_BUILD_SDK_CXX_API=ON -DMMDEPLOY_BUILD_SDK_CSHARP_API=ON \
+         -DMMDEPLOY_BUILD_EXAMPLES=ON -DMMDEPLOY_BUILD_SDK_CSHARP_API=ON \
          -DMMDEPLOY_TARGET_DEVICES="$1" -DMMDEPLOY_TARGET_BACKENDS="$2" "${ARGS[@]:2}"
 
 make -j$(nproc) && make install

.circleci/test.yml

@@ -74,7 +74,7 @@ commands:
       - run:
           name: Install mmcv-full
           command: |
-            python -m pip install opencv-python==4.5.4.60
+            python -m pip install opencv-python==4.5.4.60 opencv-contrib-python==4.5.4.60 opencv-python-headless==4.5.4.60
             python -m pip install mmcv-full==<< parameters.version >> -f https://download.openmmlab.com/mmcv/dist/cpu/torch<< parameters.torch >>/index.html
   install_mmcv_cuda:
     parameters:
@@ -91,7 +91,7 @@ commands:
       - run:
           name: Install mmcv-full
           command: |
-            python -m pip install opencv-python==4.5.4.60
+            python -m pip install opencv-python==4.5.4.60 opencv-contrib-python==4.5.4.60 opencv-python-headless==4.5.4.60
             python -m pip install mmcv-full==<< parameters.version >> -f https://download.openmmlab.com/mmcv/dist/<< parameters.cuda >>/torch<< parameters.torch >>/index.html
   install_mmdeploy:
     description: "Install MMDeploy"
@@ -217,7 +217,6 @@ jobs:
              -DMMDEPLOY_BUILD_TEST=ON `
              -DMMDEPLOY_BUILD_SDK_PYTHON_API=ON `
              -DMMDEPLOY_BUILD_EXAMPLES=ON `
-             -DMMDEPLOY_BUILD_SDK_CXX_API=ON `
              -DMMDEPLOY_BUILD_SDK_CSHARP_API=ON `
              -DMMDEPLOY_TARGET_BACKENDS="ort" `
              -DOpenCV_DIR="$env:OPENCV_PACKAGE_DIR"

.github/release.yml

@@ -0,0 +1,32 @@
+changelog:
+  categories:
+    - title: 🚀 Features
+      labels:
+        - feature
+        - enhancement
+    - title: 💥 Improvements
+      labels:
+        - improvement
+    - title: 🐞 Bug fixes
+      labels:
+        - bug
+        - Bug:P0
+        - Bug:P1
+        - Bug:P2
+        - Bug:P3
+    - title: 📚 Documentations
+      labels:
+        - documentation
+    - title: 🌐 Other
+      labels:
+        - '*'
+      exclude:
+        labels:
+          - feature
+          - enhancement
+          - bug
+          - documentation
+          - Bug:P0
+          - Bug:P1
+          - Bug:P2
+          - Bug:P3

.github/scripts/test_java_demo.py

@@ -47,6 +47,13 @@ PARAMS = [
         'configs': [
             'https://media.githubusercontent.com/media/hanrui1sensetime/mmdeploy-javaapi-testdata/master/litehrnet.tar'  # noqa: E501
         ]
+    },
+    {
+        'task':
+        'RotatedDetection',
+        'configs': [
+            'https://media.githubusercontent.com/media/hanrui1sensetime/mmdeploy-javaapi-testdata/master/gliding-vertex.tar'  # noqa: E501
+        ]
     }
 ]
 

.github/workflows/backend-ascend.yml

@@ -21,13 +21,13 @@ permissions:
 
 jobs:
   build_sdk_demo:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-20.04
     strategy:
       matrix:
         python-version: [3.7]
     steps:
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
       - name: Checkout repository
@@ -40,9 +40,7 @@ jobs:
         run: |
           sudo apt update
           sudo apt install -y ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libxrender-dev libc++1-9 libc++abi1-9
-          sudo add-apt-repository ppa:ignaciovizzo/opencv3-nonfree
           sudo apt install libopencv-dev
-          pkg-config --libs opencv
       - name: Install Ascend Toolkit
         run: |
           mkdir -p $GITHUB_WORKSPACE/Ascend
@@ -53,5 +51,5 @@ jobs:
           mkdir -p build && pushd build
           source $GITHUB_WORKSPACE/Ascend/ascend-toolkit/set_env.sh
           export LD_LIBRARY_PATH=$GITHUB_WORKSPACE/Ascend/ascend-toolkit/latest/runtime/lib64/stub:$LD_LIBRARY_PATH
-          cmake .. -DCMAKE_CXX_COMPILER=g++-7    -DMMDEPLOY_SHARED_LIBS=ON   -DMMDEPLOY_BUILD_SDK=ON       -DMMDEPLOY_BUILD_SDK_PYTHON_API=OFF  -DMMDEPLOY_TARGET_DEVICES=cpu   -DMMDEPLOY_BUILD_EXAMPLES=ON    -DMMDEPLOY_TARGET_BACKENDS=acl  -DMMDEPLOY_CODEBASES=all
+          cmake .. -DMMDEPLOY_BUILD_SDK=ON -DMMDEPLOY_BUILD_EXAMPLES=ON -DMMDEPLOY_TARGET_BACKENDS=acl
           make install -j4

.github/workflows/backend-coreml.yml

@@ -39,22 +39,21 @@ jobs:
           wget https://github.com/irexyc/mmdeploy-ci-resource/releases/download/libtorch/libtorch-osx-arm64-1.8.0.tar.gz
           mkdir $GITHUB_WORKSPACE/libtorch-install
           tar xf libtorch-osx-arm64-1.8.0.tar.gz -C $GITHUB_WORKSPACE/libtorch-install
-      - name: build
+      - name: build-static-lib
         run: |
           mkdir build && cd build
           cmake .. -DCMAKE_OSX_ARCHITECTURES="arm64" \
             -DCMAKE_SYSTEM_PROCESSOR="arm64" \
             -DMMDEPLOY_BUILD_SDK=ON \
-            -DMMDEPLOY_TARGET_DEVICES="cpu" \
-            -DMMDEPLOY_CODEBASES=all \
             -DOpenCV_DIR=$GITHUB_WORKSPACE/opencv-install/lib/cmake/opencv4 \
             -DTorch_DIR=$GITHUB_WORKSPACE/libtorch-install/share/cmake/Torch \
             -DMMDEPLOY_TARGET_BACKENDS="coreml" \
             -DMMDEPLOY_BUILD_EXAMPLES=ON \
+            -DMMDEPLOY_BUILD_SDK_MONOLITHIC=OFF \
             -DMMDEPLOY_SHARED_LIBS=OFF
           cmake --build . -j 3
           cmake --build . --target install
-      - name: build-shared
+      - name: build-monolithic-lib
         run: |
           mkdir build-shared && cd build-shared
           cmake .. -DCMAKE_OSX_ARCHITECTURES="arm64" \
@@ -65,7 +64,8 @@ jobs:
             -DOpenCV_DIR=$GITHUB_WORKSPACE/opencv-install/lib/cmake/opencv4 \
             -DTorch_DIR=$GITHUB_WORKSPACE/libtorch-install/share/cmake/Torch \
             -DMMDEPLOY_TARGET_BACKENDS="coreml" \
-            -DMMDEPLOY_BUILD_EXAMPLES=ON \
-            -DMMDEPLOY_SHARED_LIBS=ON
+            -DMMDEPLOY_BUILD_SDK_MONOLITHIC=ON \
+            -DMMDEPLOY_SHARED_LIBS=OFF \
+            -DMMDEPLOY_BUILD_EXAMPLES=ON
           cmake --build . -j 3
           cmake --build . --target install

.github/workflows/backend-ncnn.yml

@@ -29,7 +29,7 @@ permissions:
 
 jobs:
   test_onnx2ncnn:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-20.04
     strategy:
       matrix:
         python-version: [3.7]
@@ -39,7 +39,7 @@ jobs:
         with:
           submodules: 'recursive'
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
       - name: Install unittest dependencies
@@ -82,12 +82,12 @@ jobs:
         with:
           submodules: 'recursive'
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
       - name: Install mmdeploy
         run: |
-          python3 tools/scripts/build_ubuntu_x64_ncnn.py
           python3 -m pip install torch==1.8.2 torchvision==0.9.2 --extra-index-url https://download.pytorch.org/whl/lts/1.8/cpu
           python3 -m pip install mmcv-full==1.5.1  -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.8.0/index.html
+          python3 tools/scripts/build_ubuntu_x64_ncnn.py 8
           python3 -c 'import mmdeploy.apis.ncnn as ncnn_api; assert ncnn_api.is_available(with_custom_ops=True)'

.github/workflows/backend-ort.yml

@@ -31,14 +31,14 @@ jobs:
         with:
           submodules: 'recursive'
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
       - name: Install mmdeploy
         run: |
-          python3 tools/scripts/build_ubuntu_x64_ort.py
           python3 -m pip install torch==1.8.2 torchvision==0.9.2 --extra-index-url https://download.pytorch.org/whl/lts/1.8/cpu
           python3 -m pip install mmcv-full==1.5.1  -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.8.0/index.html
+          python3 tools/scripts/build_ubuntu_x64_ort.py 8
           python3 -c 'import mmdeploy.apis.onnxruntime as ort_api; assert ort_api.is_available(with_custom_ops=True)'
       - name: test mmcls full pipeline
         run: |

.github/workflows/backend-pplnn.yml

@@ -21,22 +21,15 @@ permissions:
 
 jobs:
   script_install:
-    runs-on: ubuntu-18.04
-    strategy:
-      matrix:
-        python-version: [3.7]
+    runs-on: ubuntu-20.04
     steps:
       - name: Checkout repository
         uses: actions/checkout@v3
         with:
           submodules: 'recursive'
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
-        with:
-          python-version: ${{ matrix.python-version }}
       - name: Install mmdeploy
         run: |
-          python3 tools/scripts/build_ubuntu_x64_pplnn.py
           python3 -m pip install torch==1.8.2 torchvision==0.9.2 --extra-index-url https://download.pytorch.org/whl/lts/1.8/cpu
           python3 -m pip install mmcv-full==1.5.1  -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.8.0/index.html
+          python3 tools/scripts/build_ubuntu_x64_pplnn.py 8
           python3 -c 'import mmdeploy.apis.pplnn as pplnn_api; assert pplnn_api.is_available()'

.github/workflows/backend-rknn.yml

@@ -22,7 +22,7 @@ permissions:
 
 jobs:
   build_rknpu2:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-20.04
     steps:
       - name: Checkout repository
         uses: actions/checkout@v3
@@ -34,7 +34,7 @@ jobs:
         run: |
           sh -x tools/scripts/ubuntu_cross_build_rknn.sh rk3588
   build_rknpu:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-20.04
     steps:
       - name: Checkout repository
         uses: actions/checkout@v3

.github/workflows/backend-snpe.yml

@@ -21,7 +21,7 @@ permissions:
 
 jobs:
   build_sdk_demo:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-20.04
     steps:
       - name: Checkout repository
         uses: actions/checkout@v3
@@ -34,9 +34,7 @@ jobs:
           sudo apt install wget libprotobuf-dev protobuf-compiler
           sudo apt update
           sudo apt install -y ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libxrender-dev libc++1-9 libc++abi1-9
-          sudo add-apt-repository ppa:ignaciovizzo/opencv3-nonfree
           sudo apt install libopencv-dev
-          pkg-config --libs opencv
       - name: Install snpe
         run: |
           wget https://media.githubusercontent.com/media/tpoisonooo/mmdeploy_snpe_testdata/main/snpe-1.59.tar.gz
@@ -50,7 +48,7 @@ jobs:
           export SNPE_ROOT=/home/runner/work/mmdeploy/mmdeploy/snpe-1.59.0.3230
           export LD_LIBRARY_PATH=${SNPE_ROOT}/lib/x86_64-linux-clang:${LD_LIBRARY_PATH}
           export MMDEPLOY_SNPE_X86_CI=1
-          cmake .. -DCMAKE_CXX_COMPILER=g++-7    -DMMDEPLOY_SHARED_LIBS=ON   -DMMDEPLOY_BUILD_SDK=ON       -DMMDEPLOY_BUILD_SDK_PYTHON_API=OFF  -DMMDEPLOY_TARGET_DEVICES=cpu       -DMMDEPLOY_TARGET_BACKENDS=snpe  -DMMDEPLOY_CODEBASES=all
+          cmake .. -DMMDEPLOY_BUILD_SDK=ON -DMMDEPLOY_TARGET_BACKENDS=snpe
           make -j2
           make install
           pushd install/example

.github/workflows/backend-torchscript.yml

@@ -21,7 +21,7 @@ permissions:
 
 jobs:
   script_install:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-20.04
     strategy:
       matrix:
         python-version: [3.7]
@@ -31,9 +31,9 @@ jobs:
         with:
           submodules: 'recursive'
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
       - name: Install mmdeploy
         run: |
-          python3 tools/scripts/build_ubuntu_x64_torchscript.py
+          python3 tools/scripts/build_ubuntu_x64_torchscript.py 8

.github/workflows/backend-tvm.yml

@@ -31,14 +31,14 @@ jobs:
         with:
           submodules: 'recursive'
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
       - name: Install mmdeploy
         run: |
-          python3 tools/scripts/build_ubuntu_x64_tvm.py
-          source ~/mmdeploy.env
           python3 -m pip install torch==1.8.2 torchvision==0.9.2 --extra-index-url https://download.pytorch.org/whl/lts/1.8/cpu
           python3 -m pip install mmcv-full==1.5.1  -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.8.0/index.html
           python3 -m pip install decorator psutil scipy attrs tornado pytest
+          python3 tools/scripts/build_ubuntu_x64_tvm.py 8
+          source ~/mmdeploy.env
           python3 -c 'import mmdeploy.apis.tvm as tvm_api; assert tvm_api.is_available()'

.github/workflows/build.yml

@@ -25,10 +25,9 @@ permissions:
 
 jobs:
   build_cpu_model_convert:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-20.04
     strategy:
       matrix:
-        python-version: [3.7]
         torch: [1.8.0, 1.9.0]
         mmcv: [1.4.2]
         include:
@@ -39,23 +38,23 @@ jobs:
             torch_version: torch1.9
             torchvision: 0.10.0
     steps:
-      - uses: actions/checkout@v2
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
-        with:
-          python-version: ${{ matrix.python-version }}
+      - uses: actions/checkout@v3
       - name: Install PyTorch
-        run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
+        run: |
+          python -m pip install --upgrade pip
+          python -V
+          python -m pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
       - name: Install MMCV
         run: |
-          pip install mmcv-full==${{matrix.mmcv}} -f https://download.openmmlab.com/mmcv/dist/cpu/${{matrix.torch_version}}/index.html
+          python -m pip install mmcv-full==${{matrix.mmcv}} -f https://download.openmmlab.com/mmcv/dist/cpu/${{matrix.torch_version}}/index.html
           python -c 'import mmcv; print(mmcv.__version__)'
       - name: Install unittest dependencies
         run: |
-          pip install -r requirements.txt
-          pip install -U numpy
+          python -m pip install -U numpy
+          python -m pip install rapidfuzz==2.15.1
+          python -m pip install -r requirements.txt
       - name: Build and install
-        run: rm -rf .eggs && pip install -e .
+        run: rm -rf .eggs && python -m pip install -e .
       - name: Run python unittests and generate coverage report
         run: |
           coverage run --branch --source mmdeploy -m pytest -rsE tests
@@ -63,7 +62,7 @@ jobs:
           coverage report -m
 
   build_cpu_sdk:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-20.04
     steps:
       - name: Checkout repository
         uses: actions/checkout@v3
@@ -73,16 +72,18 @@ jobs:
         run: sudo apt update
       - name: gcc-multilib
         run: |
-          sudo apt install gcc-multilib g++-multilib wget libprotobuf-dev protobuf-compiler
           sudo apt update
-          sudo apt install -y ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libxrender-dev libc++1-9 libc++abi1-9
-          sudo add-apt-repository ppa:ignaciovizzo/opencv3-nonfree
-          sudo apt install libopencv-dev lcov wget
-          pkg-config --libs opencv
+          sudo apt install libopencv-dev lcov wget -y
       - name: Build and run SDK unit test without backend
         run: |
           mkdir -p build && pushd build
-          cmake .. -DCMAKE_CXX_COMPILER=g++-7  -DMMDEPLOY_CODEBASES=all    -DMMDEPLOY_BUILD_SDK=ON     -DMMDEPLOY_BUILD_SDK_PYTHON_API=OFF     -DMMDEPLOY_TARGET_DEVICES=cpu   -DMMDEPLOY_COVERAGE=ON  -DMMDEPLOY_BUILD_TEST=ON
+          cmake .. \
+            -DMMDEPLOY_CODEBASES=all \
+            -DMMDEPLOY_BUILD_SDK=ON \
+            -DMMDEPLOY_BUILD_SDK_PYTHON_API=OFF \
+            -DMMDEPLOY_TARGET_DEVICES=cpu \
+            -DMMDEPLOY_COVERAGE=ON \
+            -DMMDEPLOY_BUILD_TEST=ON
           make -j2
           mkdir -p mmdeploy_test_resources/transform
           cp ../tests/data/tiger.jpeg mmdeploy_test_resources/transform/
@@ -101,7 +102,7 @@ jobs:
       - name: update
         run: sudo apt update
       - name: Set up Python
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
           python-version: 3.8
       - name: gcc-multilib
@@ -109,14 +110,14 @@ jobs:
           sh -x tools/scripts/ubuntu_cross_build_aarch64.sh
 
   build_cuda102:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-20.04
     container:
       image: pytorch/pytorch:1.9.0-cuda10.2-cudnn7-devel
     env:
       FORCE_CUDA: 1
     strategy:
       matrix:
-        python-version: [3.7]
+        python-version: [3.8]
         torch: [1.9.0+cu102]
         mmcv: [1.4.2]
         include:
@@ -124,26 +125,20 @@ jobs:
             torch_version: torch1.9
             torchvision: 0.10.0+cu102
     steps:
-      - uses: actions/checkout@v2
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
-        with:
-          python-version: ${{ matrix.python-version }}
+      - uses: actions/checkout@v3
       - name: Install system dependencies
         run: |
           apt-key adv --keyserver keyserver.ubuntu.com --recv-keys A4B469963BF863CC
-          apt-get update && apt-get install -y ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libxrender-dev python${{matrix.python-version}}-dev
-          apt-get clean
-          rm -rf /var/lib/apt/lists/*
+          apt-get update && apt-get install -y git
       - name: Install PyTorch
         run: python -m pip install torch==${{matrix.torch}} torchvision==${{matrix.torchvision}} -f https://download.pytorch.org/whl/torch_stable.html
       - name: Install dependencies
         run: |
           python -V
+          python -m pip install -U pip
           python -m pip install mmcv-full==${{matrix.mmcv}} -f https://download.openmmlab.com/mmcv/dist/cu102/${{matrix.torch_version}}/index.html
-          CFLAGS=`python -c 'import sysconfig;print("-I"+sysconfig.get_paths()["include"])'` python -m pip install -r requirements.txt
-          pip install -U pycuda
-          python -m pip install -U numpy
+          python -m pip install -r requirements.txt
+          python -m pip install rapidfuzz==2.15.1
       - name: Build and install
         run: |
           rm -rf .eggs && python -m pip install -e .
@@ -155,41 +150,31 @@ jobs:
           coverage report -m
 
   build_cuda111:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-20.04
     container:
       image: pytorch/pytorch:1.8.0-cuda11.1-cudnn8-devel
-
     strategy:
       matrix:
-        python-version: [3.7]
+        python-version: [3.8]
         torch: [1.8.0+cu111]
         mmcv: [1.4.2]
         include:
           - torch: 1.8.0+cu111
             torch_version: torch1.8
             torchvision: 0.9.0+cu111
-
     steps:
-      - uses: actions/checkout@v2
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
-        with:
-          python-version: ${{ matrix.python-version }}
+      - uses: actions/checkout@v3
       - name: Install system dependencies
         run: |
           apt-key adv --keyserver keyserver.ubuntu.com --recv-keys A4B469963BF863CC
-          apt-get update && apt-get install -y ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libxrender-dev python${{matrix.python-version}}-dev
-          apt-get clean
-          rm -rf /var/lib/apt/lists/*
-      - name: Install PyTorch
-        run: python -m pip install torch==${{matrix.torch}} torchvision==${{matrix.torchvision}} -f https://download.pytorch.org/whl/torch_stable.html
+          apt-get update && apt-get install -y git
       - name: Install dependencies
         run: |
           python -V
+          python -m pip install -U pip
           python -m pip install mmcv-full==${{matrix.mmcv}} -f https://download.openmmlab.com/mmcv/dist/cu111/${{matrix.torch_version}}/index.html
-          CFLAGS=`python -c 'import sysconfig;print("-I"+sysconfig.get_paths()["include"])'` python -m pip install -r requirements.txt
-          pip install -U pycuda
-          python -m pip install -U numpy
+          python -m pip install -r requirements.txt
+          python -m pip install rapidfuzz==2.15.1
       - name: Build and install
         run: |
           rm -rf .eggs && python -m pip install -e .

.github/workflows/java_api.yml

@@ -19,14 +19,14 @@ permissions:
 
 jobs:
   test_java_api:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-20.04
     steps:
       - name: Checkout repository
         uses: actions/checkout@v3
         with:
           submodules: 'recursive'
       - name: Set up Python 3.7
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
           python-version: 3.7
       - name: Install unittest dependencies

.github/workflows/lint.yml

@@ -7,11 +7,11 @@ permissions:
 
 jobs:
   lint:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-20.04
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
       - name: Set up Python 3.7
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
           python-version: 3.7
       - name: Install pre-commit hook

.github/workflows/linux-riscv64-gcc.yml

@@ -48,12 +48,9 @@ jobs:
           cmake .. \
             -DCMAKE_TOOLCHAIN_FILE=../cmake/toolchains/riscv64-linux-gnu.cmake \
             -DMMDEPLOY_BUILD_SDK=ON \
-            -DMMDEPLOY_SHARED_LIBS=ON \
             -DMMDEPLOY_BUILD_EXAMPLES=ON \
-            -DMMDEPLOY_TARGET_DEVICES="cpu" \
             -DMMDEPLOY_TARGET_BACKENDS="ncnn" \
             -Dncnn_DIR=$GITHUB_WORKSPACE/ncnn-install/lib/cmake/ncnn/ \
-            -DMMDEPLOY_CODEBASES=all \
             -DOpenCV_DIR=$GITHUB_WORKSPACE/opencv-install/lib/cmake/opencv4
           make -j$(nproc)
           make install

.github/workflows/prebuild.yml

@@ -0,0 +1,277 @@
+name: prebuild
+
+on:
+  push:
+    branches:
+      - main
+      - dev-1.x
+      - master
+    paths:
+      - "mmdeploy/version.py"
+
+permissions: write-all
+
+jobs:
+  linux_build:
+    runs-on: [self-hosted, linux-3090]
+    container:
+      image: openmmlab/mmdeploy:manylinux2014_x86_64-cuda11.3
+      options: "--gpus=all --ipc=host"
+      volumes:
+        - /data2/actions-runner/prebuild:/__w/mmdeploy/prebuild
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+        with:
+          submodules: recursive
+      - name: Get mmdeploy version
+        run: |
+          export MMDEPLOY_VERSION=$(python3 -c "import sys; sys.path.append('mmdeploy');from version import __version__;print(__version__)")
+          echo $MMDEPLOY_VERSION
+          echo "MMDEPLOY_VERSION=$MMDEPLOY_VERSION"  >> $GITHUB_ENV
+          echo "OUTPUT_DIR=$MMDEPLOY_VERSION-$GITHUB_RUN_ID" >> $GITHUB_ENV
+      - name: Build MMDeploy
+        run: |
+          source activate mmdeploy-3.6
+          pip install pyyaml packaging setuptools wheel
+          mkdir pack; cd pack
+          python ../tools/package_tools/generate_build_config.py --backend 'trt;ort' \
+            --system linux --output config.yml --build-mmdeploy
+          python ../tools/package_tools/mmdeploy_builder.py --config config.yml
+      - name: Build sdk cpu backend
+        run: |
+          source activate mmdeploy-3.6
+          cd pack
+          python ../tools/package_tools/generate_build_config.py --backend 'ort' \
+            --system linux --output config.yml --device cpu --build-sdk --build-sdk-monolithic \
+            --build-sdk-python --sdk-dynamic-net
+          python ../tools/package_tools/mmdeploy_builder.py --config config.yml
+      - name: Build sdk cuda backend
+        run: |
+          source activate mmdeploy-3.6
+          cd pack
+          python ../tools/package_tools/generate_build_config.py --backend 'ort;trt' \
+            --system linux --output config.yml --device cuda --build-sdk --build-sdk-monolithic \
+            --build-sdk-python --sdk-dynamic-net --onnxruntime-dir=$ONNXRUNTIME_GPU_DIR
+          python ../tools/package_tools/mmdeploy_builder.py --config config.yml
+      - name: Move artifact
+        run: |
+          mkdir -p /__w/mmdeploy/prebuild/$OUTPUT_DIR
+          cp -r pack/* /__w/mmdeploy/prebuild/$OUTPUT_DIR
+
+  linux_build_cxx11abi:
+    runs-on: [self-hosted, linux-3090]
+    container:
+      image: openmmlab/mmdeploy:build-ubuntu16.04-cuda11.3
+      options: "--gpus=all --ipc=host"
+      volumes:
+        - /data2/actions-runner/prebuild:/__w/mmdeploy/prebuild
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+        with:
+          submodules: recursive
+      - name: Get mmdeploy version
+        run: |
+          export MMDEPLOY_VERSION=$(python3 -c "import sys; sys.path.append('mmdeploy');from version import __version__;print(__version__)")
+          echo $MMDEPLOY_VERSION
+          echo "MMDEPLOY_VERSION=$MMDEPLOY_VERSION"  >> $GITHUB_ENV
+          echo "OUTPUT_DIR=$MMDEPLOY_VERSION-$GITHUB_RUN_ID" >> $GITHUB_ENV
+      - name: Build sdk cpu backend
+        run: |
+          mkdir pack; cd pack
+          python ../tools/package_tools/generate_build_config.py --backend 'ort' \
+            --system linux --output config.yml --device cpu --build-sdk --build-sdk-monolithic \
+            --sdk-dynamic-net --cxx11abi
+          python ../tools/package_tools/mmdeploy_builder.py --config config.yml
+      - name: Build sdk cuda backend
+        run: |
+          cd pack
+          python ../tools/package_tools/generate_build_config.py --backend 'ort;trt' \
+            --system linux --output config.yml --device cuda --build-sdk --build-sdk-monolithic \
+            --sdk-dynamic-net --cxx11abi --onnxruntime-dir=$ONNXRUNTIME_GPU_DIR --cudnn-dir /usr
+          python ../tools/package_tools/mmdeploy_builder.py --config config.yml
+      - name: Move artifact
+        run: |
+          mkdir -p /__w/mmdeploy/prebuild/$OUTPUT_DIR
+          cp -r pack/* /__w/mmdeploy/prebuild/$OUTPUT_DIR
+
+  linux_test:
+    runs-on: [self-hosted, linux-3090]
+    needs:
+      - linux_build
+      - linux_build_cxx11abi
+    container:
+      image: openmmlab/mmdeploy:ubuntu20.04-cuda11.3
+      options: "--gpus=all --ipc=host"
+      volumes:
+        - /data2/actions-runner/prebuild:/__w/mmdeploy/prebuild
+        - /data2/actions-runner/testmodel:/__w/mmdeploy/testmodel
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+      - name: Get mmdeploy version
+        run: |
+          export MMDEPLOY_VERSION=$(python3 -c "import sys; sys.path.append('mmdeploy');from version import __version__;print(__version__)")
+          echo $MMDEPLOY_VERSION
+          echo "MMDEPLOY_VERSION=$MMDEPLOY_VERSION"  >> $GITHUB_ENV
+          echo "OUTPUT_DIR=$MMDEPLOY_VERSION-$GITHUB_RUN_ID" >> $GITHUB_ENV
+      - name: Test python
+        run: |
+          cd /__w/mmdeploy/prebuild/$OUTPUT_DIR
+          bash $GITHUB_WORKSPACE/tools/package_tools/test/test_sdk_python.sh
+      - name: Test c/cpp
+        run: |
+          cd /__w/mmdeploy/prebuild/$OUTPUT_DIR
+          bash $GITHUB_WORKSPACE/tools/package_tools/test/test_sdk.sh
+
+  linux_upload:
+    runs-on: [self-hosted, linux-3090]
+    if: startsWith(github.ref, 'refs/tags/')
+    environment: 'prod'
+    needs: linux_test
+    env:
+      PREBUILD_DIR: /data2/actions-runner/prebuild
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+      - name: Get mmdeploy version
+        run: |
+          export MMDEPLOY_VERSION=$(python3 -c "import sys; sys.path.append('mmdeploy');from version import __version__;print(__version__)")
+          echo $MMDEPLOY_VERSION
+          echo "MMDEPLOY_VERSION=$MMDEPLOY_VERSION"  >> $GITHUB_ENV
+          echo "OUTPUT_DIR=$MMDEPLOY_VERSION-$GITHUB_RUN_ID" >> $GITHUB_ENV
+      - name: Upload mmdeploy
+        run: |
+          cd $PREBUILD_DIR/$OUTPUT_DIR/mmdeploy
+          pip install twine
+          # twine upload * --repository testpypi -u __token__ -p ${{ secrets.test_pypi_password }}
+          twine upload * -u __token__ -p ${{ secrets.pypi_password }}
+      - name: Upload mmdeploy_runtime
+        run: |
+          cd $PREBUILD_DIR/$OUTPUT_DIR/mmdeploy_runtime
+          # twine upload * --repository testpypi -u __token__ -p ${{ secrets.test_pypi_password }}
+          twine upload * -u __token__ -p ${{ secrets.pypi_password }}
+      - name: Zip mmdeploy sdk
+        run: |
+          cd $PREBUILD_DIR/$OUTPUT_DIR/sdk
+          for folder in *
+          do
+            tar czf $folder.tar.gz $folder
+          done
+      - name: Upload mmdeploy sdk
+        uses: softprops/action-gh-release@v1
+        with:
+          files: |
+              $PREBUILD_DIR/$OUTPUT_DIR/sdk/*.tar.gz
+
+
+  windows_build:
+    runs-on: [self-hosted, win10-3080]
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+        with:
+          submodules: recursive
+      - name: Get mmdeploy version
+        run: |
+          conda activate mmdeploy-3.8
+          $env:MMDEPLOY_VERSION=(python -c "import sys; sys.path.append('mmdeploy');from version import __version__;print(__version__)")
+          echo $env:MMDEPLOY_VERSION
+          echo "MMDEPLOY_VERSION=$env:MMDEPLOY_VERSION"  >> $env:GITHUB_ENV
+          echo "OUTPUT_DIR=$env:MMDEPLOY_VERSION-$env:GITHUB_RUN_ID" >> $env:GITHUB_ENV
+      - name: Build MMDeploy
+        run: |
+          . D:\DEPS\cienv\prebuild_gpu_env.ps1
+          conda activate mmdeploy-3.6
+          mkdir pack; cd pack
+          python ../tools/package_tools/generate_build_config.py --backend 'trt;ort' `
+            --system windows --output config.yml --build-mmdeploy
+          python ../tools/package_tools/mmdeploy_builder.py --config config.yml
+      - name: Build sdk cpu backend
+        run: |
+          . D:\DEPS\cienv\prebuild_cpu_env.ps1
+          conda activate mmdeploy-3.6
+          cd pack
+          python ../tools/package_tools/generate_build_config.py --backend 'ort' `
+            --system windows --output config.yml --device cpu --build-sdk --build-sdk-monolithic `
+            --build-sdk-python --sdk-dynamic-net
+          python ../tools/package_tools/mmdeploy_builder.py --config config.yml
+      - name: Build sdk cuda backend
+        run: |
+          . D:\DEPS\cienv\prebuild_gpu_env.ps1
+          conda activate mmdeploy-3.6
+          cd pack
+          python ../tools/package_tools/generate_build_config.py --backend 'ort;trt' `
+            --system windows --output config.yml --device cuda --build-sdk --build-sdk-monolithic `
+            --build-sdk-python --sdk-dynamic-net
+          python ../tools/package_tools/mmdeploy_builder.py --config config.yml
+      - name: Move artifact
+        run: |
+          New-Item "D:/DEPS/ciartifact/$env:OUTPUT_DIR" -ItemType Directory -Force
+          Move-Item pack/* "D:/DEPS/ciartifact/$env:OUTPUT_DIR"
+
+  windows_test:
+    runs-on: [self-hosted, win10-3080]
+    needs: windows_build
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+      - name: Get mmdeploy version
+        run: |
+          conda activate mmdeploy-3.8
+          $env:MMDEPLOY_VERSION=(python -c "import sys; sys.path.append('mmdeploy');from version import __version__;print(__version__)")
+          echo $env:MMDEPLOY_VERSION
+          echo "MMDEPLOY_VERSION=$env:MMDEPLOY_VERSION"  >> $env:GITHUB_ENV
+          echo "OUTPUT_DIR=$env:MMDEPLOY_VERSION-$env:GITHUB_RUN_ID" >> $env:GITHUB_ENV
+      - name: Test python
+        run: |
+          cd "D:/DEPS/ciartifact/$env:OUTPUT_DIR"
+          . D:\DEPS\cienv\prebuild_cpu_env.ps1
+          conda activate ci-test
+          & "$env:GITHUB_WORKSPACE/tools/package_tools/test/test_sdk_python.ps1"
+      - name: Test c/cpp
+        run: |
+          cd "D:/DEPS/ciartifact/$env:OUTPUT_DIR"
+          . D:\DEPS\cienv\prebuild_cpu_env.ps1
+          & "$env:GITHUB_WORKSPACE/tools/package_tools/test/test_sdk.ps1"
+
+  windows_upload:
+    runs-on: [self-hosted, win10-3080]
+    if: startsWith(github.ref, 'refs/tags/')
+    environment: 'prod'
+    needs: windows_test
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+      - name: Get mmdeploy version
+        run: |
+          conda activate mmdeploy-3.8
+          $env:MMDEPLOY_VERSION=(python -c "import sys; sys.path.append('mmdeploy');from version import __version__;print(__version__)")
+          echo $env:MMDEPLOY_VERSION
+          echo "MMDEPLOY_VERSION=$env:MMDEPLOY_VERSION"  >> $env:GITHUB_ENV
+          echo "OUTPUT_DIR=$env:MMDEPLOY_VERSION-$env:GITHUB_RUN_ID" >> $env:GITHUB_ENV
+      - name: Upload mmdeploy
+        run: |
+          cd "D:/DEPS/ciartifact/$env:OUTPUT_DIR/mmdeploy"
+          conda activate mmdeploy-3.8
+          # twine upload * --repository testpypi -u __token__ -p ${{ secrets.test_pypi_password }}
+          twine upload * -u __token__ -p ${{ secrets.pypi_password }}
+      - name: Upload mmdeploy_runtime
+        run: |
+          cd "D:/DEPS/ciartifact/$env:OUTPUT_DIR/mmdeploy_runtime"
+          conda activate mmdeploy-3.8
+          # twine upload * --repository testpypi -u __token__ -p ${{ secrets.test_pypi_password }}
+          twine upload * -u __token__ -p ${{ secrets.pypi_password }}
+      - name: Zip mmdeploy sdk
+        run: |
+          cd "D:/DEPS/ciartifact/$env:OUTPUT_DIR/sdk"
+          $folders = $(ls).Name
+          foreach ($folder in $folders) {
+            Compress-Archive -Path $folder -DestinationPath "$folder.zip"
+          }
+      - name: Upload mmdeploy sdk
+        uses: softprops/action-gh-release@v1
+        with:
+          files: |
+              D:/DEPS/ciartifact/$env:OUTPUT_DIR/sdk/*.zip

.github/workflows/quantize.yml

@@ -21,7 +21,7 @@ permissions:
 
 jobs:
   test_ncnn_PTQ:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-20.04
     container:
       image: pytorch/pytorch:1.8.0-cuda11.1-cudnn8-devel
 
@@ -36,45 +36,31 @@ jobs:
             torchvision: 0.9.0+cu111
 
     steps:
-      - uses: actions/checkout@v2
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
-        with:
-          python-version: ${{ matrix.python-version }}
+      - uses: actions/checkout@v3
       - name: Install system dependencies
         run: |
           apt-key adv --keyserver keyserver.ubuntu.com --recv-keys A4B469963BF863CC
-          apt-get update && apt-get install -y wget ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libxrender-dev python${{matrix.python-version}}-dev
-          apt-get clean
-          rm -rf /var/lib/apt/lists/*
-      - name: Install PyTorch
-        run: python -m pip install torch==${{matrix.torch}} torchvision==${{matrix.torchvision}} -f https://download.pytorch.org/whl/torch_stable.html
+          apt-get update && apt-get install -y git wget
       - name: Install dependencies
         run: |
           python -V
+          python -m pip install -U pip
           python -m pip install mmcv-full==${{matrix.mmcv}} -f https://download.openmmlab.com/mmcv/dist/cu111/${{matrix.torch_version}}/index.html
-          CFLAGS=`python -c 'import sysconfig;print("-I"+sysconfig.get_paths()["include"])'` python -m pip install -r requirements.txt
-          python -m pip install -U numpy
-
+          python -m pip install -r requirements.txt
+          python -m pip install rapidfuzz==2.15.1
       - name: Install mmcls
         run: |
           cd ~
-          git clone https://github.com/open-mmlab/mmclassification.git
+          git clone -b v0.23.0 --depth 1 https://github.com/open-mmlab/mmclassification.git
           cd mmclassification
-          git checkout v0.23.0
           python3 -m pip install -e .
-          cd -
       - name: Install ppq
         run: |
-          cd ~
-          python -m pip install protobuf==3.20.0
-          git clone https://github.com/openppl-public/ppq
+          git clone -b v0.6.6 --depth 1 https://github.com/openppl-public/ppq
           cd ppq
-          git checkout edbecf44c7b203515640e4f4119c000a1b66b33a
           python3 -m pip install -r requirements.txt
           python3 setup.py install
-          cd -
       - name: Run tests
         run: |
-          echo $(pwd)
+          export PYTHONPATH=${PWD}/ppq:${PYTHONPATH}
           python3 .github/scripts/quantize_to_ncnn.py

.github/workflows/rust_api.yml

@@ -19,7 +19,7 @@ permissions:
 
 jobs:
   test_rust_api:
-    runs-on: ubuntu-18.04
+    runs-on: ubuntu-20.04
     steps:
       - name: Checkout repository
         uses: actions/checkout@v3
@@ -27,7 +27,7 @@ jobs:
           submodules: 'recursive'
 
       - name: Set up Python 3.7
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
           python-version: 3.7
       - name: Install latest nightly Rust

.github/workflows/stale.yml

@@ -10,9 +10,12 @@ permissions:
 
 jobs:
   stale:
+    permissions:
+      issues: write
+      pull-requests: write
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/stale@v6
+      - uses: actions/stale@v7
         with:
           stale-issue-message: 'This issue is marked as stale because it has been marked as invalid or awaiting response for 7 days without any further response. It will be closed in 5 days if the stale label is not removed or if there is no further response.'
           stale-pr-message: 'This PR is marked as stale because there has been no activity in the past 45 days. It will be closed in 10 days if the stale label is not removed or if there is no further updates.'
@@ -26,3 +29,4 @@ jobs:
           days-before-pr-close: 10
           # automatically remove the stale label when the issues or the pull reqquests are updated or commented
           remove-stale-when-updated: true
+          operations-per-run: 50

.gitignore

@@ -164,3 +164,6 @@ service/snpe/grpc_cpp_plugin
 csrc/mmdeploy/preprocess/elena/json
 csrc/mmdeploy/preprocess/elena/cpu_kernel/*
 csrc/mmdeploy/preprocess/elena/cuda_kernel/*
+
+# c#
+demo/csharp/*/Properties

.pre-commit-config.yaml

@@ -3,9 +3,11 @@ repos:
     rev: 4.0.1
     hooks:
       - id: flake8
-        args: ["--exclude=*/client/inference_pb2.py,*/client/inference_pb2_grpc.py"]
+        args: ["--exclude=*/client/inference_pb2.py, \
+                */client/inference_pb2_grpc.py, \
+                tools/package_tools/packaging/setup.py"]
   - repo: https://github.com/PyCQA/isort
-    rev: 5.10.1
+    rev: 5.11.5
     hooks:
       - id: isort
   - repo: https://github.com/pre-commit/mirrors-yapf

CMakeLists.txt

@@ -5,7 +5,7 @@ endif ()
 message(STATUS "CMAKE_INSTALL_PREFIX: ${CMAKE_INSTALL_PREFIX}")
 
 cmake_minimum_required(VERSION 3.14)
-project(MMDeploy VERSION 0.12.0)
+project(MMDeploy VERSION 0.14.0)
 
 set(CMAKE_CXX_STANDARD 17)
 
@@ -24,10 +24,10 @@ 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_CXX_API "build SDK C++ 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)
@@ -40,6 +40,10 @@ 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 (NOT CMAKE_BUILD_TYPE)
     set(CMAKE_BUILD_TYPE Release CACHE STRING "choose 'Release' as default build type" FORCE)
 endif ()
@@ -73,8 +77,6 @@ endif ()
 
 if (MSVC)
     add_compile_options($<$<COMPILE_LANGUAGE:CXX>:/diagnostics:classic>)
-    add_compile_options($<$<COMPILE_LANGUAGE:CXX>:/Zc:preprocessor>) # /experimental:preprocessor on VS2017
-    add_compile_options($<$<COMPILE_LANGUAGE:CXX>:/Zc:__cplusplus>)
     add_compile_options($<$<COMPILE_LANGUAGE:CXX>:/wd4251>)
 endif ()
 
@@ -97,10 +99,12 @@ include(cmake/MMDeploy.cmake)
 add_subdirectory(csrc/mmdeploy)
 
 if (MMDEPLOY_BUILD_SDK)
-    install(TARGETS MMDeployStaticModules
-            MMDeployDynamicModules
-            MMDeployLibs
-            EXPORT MMDeployTargets)
+    if (NOT MMDEPLOY_BUILD_SDK_MONOLITHIC)
+        install(TARGETS MMDeployStaticModules
+                MMDeployDynamicModules
+                MMDeployLibs
+                EXPORT MMDeployTargets)
+    endif ()
 
     if (MMDEPLOY_BUILD_TEST)
         add_subdirectory(tests/test_csrc)

MANIFEST.in

@@ -2,7 +2,9 @@ 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

README.md

@@ -28,6 +28,16 @@
 
 English | [简体中文](README_zh-CN.md)
 
+## 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  |
+
 ## Introduction
 
 MMDeploy is an open-source deep learning model deployment toolset. It is a part of the [OpenMMLab](https://openmmlab.com/) project.

README_zh-CN.md

@@ -28,6 +28,16 @@
 
 [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   | mmcls 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       |
+
 ## 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。

cmake/MMDeploy.cmake

@@ -1,6 +1,6 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 
-function (mmdeploy_export NAME)
+function (mmdeploy_export_impl NAME)
     set(_LIB_DIR lib)
     if (MSVC)
         set(_LIB_DIR bin)
@@ -12,6 +12,24 @@ function (mmdeploy_export NAME)
             RUNTIME DESTINATION bin)
 endfunction ()
 
+macro(mmdeploy_add_net NAME)
+    if (MMDEPLOY_DYNAMIC_BACKEND)
+        mmdeploy_add_library(${NAME} SHARED ${ARGN})
+        # DYNAMIC_BACKEND implies BUILD_SDK_MONOLITHIC
+        mmdeploy_export_impl(${NAME})
+        target_link_libraries(${PROJECT_NAME} PRIVATE mmdeploy)
+        set(BACKEND_LIB_NAMES ${BACKEND_LIB_NAMES} ${PROJECT_NAME} PARENT_SCOPE)
+    else ()
+        mmdeploy_add_module(${NAME} ${ARGN})
+    endif ()
+endmacro()
+
+function (mmdeploy_export NAME)
+    if (NOT MMDEPLOY_BUILD_SDK_MONOLITHIC)
+        mmdeploy_export_impl(${NAME})
+    endif ()
+endfunction ()
+
 
 function (mmdeploy_add_library NAME)
     # EXCLUDE: exclude from registering & exporting

cmake/MMDeployConfig.cmake.in

@@ -10,13 +10,12 @@ set(MMDEPLOY_TARGET_DEVICES @MMDEPLOY_TARGET_DEVICES@)
 set(MMDEPLOY_TARGET_BACKENDS @MMDEPLOY_TARGET_BACKENDS@)
 set(MMDEPLOY_BUILD_TYPE @CMAKE_BUILD_TYPE@)
 set(MMDEPLOY_BUILD_SHARED @MMDEPLOY_SHARED_LIBS@)
-set(MMDEPLOY_BUILD_SDK_CXX_API @MMDEPLOY_BUILD_SDK_CXX_API@)
 set(MMDEPLOY_BUILD_SDK_MONOLITHIC @MMDEPLOY_BUILD_SDK_MONOLITHIC@)
 set(MMDEPLOY_VERSION_MAJOR @MMDEPLOY_VERSION_MAJOR@)
 set(MMDEPLOY_VERSION_MINOR @MMDEPLOY_VERSION_MINOR@)
 set(MMDEPLOY_VERSION_PATCH @MMDEPLOY_VERSION_PATCH@)
 
-if (NOT MMDEPLOY_BUILD_SHARED)
+if (NOT MMDEPLOY_BUILD_SHARED AND NOT MMDEPLOY_BUILD_SDK_MONOLITHIC)
     if ("cuda" IN_LIST MMDEPLOY_TARGET_DEVICES)
         find_package(CUDA REQUIRED)
         if(MSVC)

cmake/cuda.cmake

@@ -11,6 +11,37 @@ if (MSVC OR (NOT DEFINED CMAKE_CUDA_RUNTIME_LIBRARY))
     set(CUDA_USE_STATIC_CUDA_RUNTIME OFF)
 endif ()
 
+if (MSVC)
+    # no plugin in BuildCustomizations and no specify cuda toolset
+    if (NOT CMAKE_VS_PLATFORM_TOOLSET_CUDA)
+        message(FATAL_ERROR "Please install CUDA MSBuildExtensions")
+    endif ()
+
+    if (CMAKE_VS_PLATFORM_TOOLSET_CUDA_CUSTOM_DIR)
+        # find_package(CUDA) required ENV{CUDA_PATH}
+        set(ENV{CUDA_PATH} ${CMAKE_VS_PLATFORM_TOOLSET_CUDA_CUSTOM_DIR})
+    else ()
+        # we use CUDA_PATH and ignore nvcc.exe
+        # cmake will import highest cuda props version, which may not equal to CUDA_PATH
+        if (NOT (DEFINED ENV{CUDA_PATH}))
+            message(FATAL_ERROR "Please set CUDA_PATH environment variable")
+        endif ()
+
+        string(REGEX REPLACE ".*v([0-9]+)\\..*" "\\1" _MAJOR $ENV{CUDA_PATH})
+        string(REGEX REPLACE ".*v[0-9]+\\.([0-9]+).*" "\\1" _MINOR $ENV{CUDA_PATH})
+        if (NOT (${CMAKE_VS_PLATFORM_TOOLSET_CUDA} STREQUAL "${_MAJOR}.${_MINOR}"))
+            message(FATAL_ERROR "Auto detected cuda version ${CMAKE_VS_PLATFORM_TOOLSET_CUDA}"
+                " is mismatch with ENV{CUDA_PATH} $ENV{CUDA_PATH}. Please modify CUDA_PATH"
+                " to match ${CMAKE_VS_PLATFORM_TOOLSET_CUDA} or specify cuda toolset by"
+                " cmake -T cuda=/path/to/cuda ..")
+        endif ()
+
+        if (NOT (DEFINED ENV{CUDA_PATH_V${_MAJOR}_${_MINOR}}))
+            message(FATAL_ERROR "Please set CUDA_PATH_V${_MAJOR}_${_MINOR} environment variable")
+        endif ()
+    endif ()
+endif ()
+
 # nvcc compiler settings
 find_package(CUDA REQUIRED)
 

cmake/loader.cpp.in

@@ -1,15 +1,53 @@
 // Copyright (c) OpenMMLab. All rights reserved.
 
-#include <Windows.h>
-
+#include <string>
 #include <cstdio>
 
+#ifdef _WIN32
+#include <Windows.h>
+#else
+#include <dlfcn.h>
+#endif
+
+#ifdef _WIN32
+#define LIBPREFIX ""
+#define LIBSUFFIX ".dll"
+#elif defined(__APPLE__)
+#define LIBPREFIX "lib"
+#define LIBSUFFIX ".dylib"
+#else
+#define LIBPREFIX "lib"
+#define LIBSUFFIX ".so"
+#endif
+
 namespace mmdeploy {
 namespace {
 
+#ifdef _WIN32
+inline static const std::wstring GetDllPath() {
+    HMODULE hm = NULL;
+    GetModuleHandleExW(GET_MODULE_HANDLE_EX_FLAG_FROM_ADDRESS | GET_MODULE_HANDLE_EX_FLAG_UNCHANGED_REFCOUNT,
+      (LPWSTR)&GetDllPath, &hm);
+    std::wstring ret;
+    ret.resize(MAX_PATH);
+    GetModuleFileNameW(hm, &ret[0], ret.size());
+    ret = ret.substr(0, ret.find_last_of(L"/\\"));
+    return ret;
+}
+#endif
+
 void* mmdeploy_load_library(const char* name) {
   fprintf(stderr, "loading %s ...\n", name);
-  auto handle = LoadLibraryA(name);
+
+#ifdef _WIN32
+  auto handle = LoadLibraryExA(name, NULL, LOAD_LIBRARY_SEARCH_USER_DIRS);
+  if (handle == NULL) {
+    handle = LoadLibraryExA(name, NULL, LOAD_WITH_ALTERED_SEARCH_PATH);
+  }
+#else
+  auto handle = dlopen(name, RTLD_NOW | RTLD_GLOBAL);
+#endif
+
   if (!handle) {
     fprintf(stderr, "failed to load library %s\n", name);
     return nullptr;
@@ -22,11 +60,15 @@ void* mmdeploy_load_library(const char* name) {
 class Loader {
  public:
   Loader() {
+#ifdef _WIN32
+    AddDllDirectory(GetDllPath().c_str());
+#endif
     const char* modules[] = {
         @_MMDEPLOY_DYNAMIC_MODULES@
     };
     for (const auto name : modules) {
-      mmdeploy_load_library(name);
+      std::string libname = std::string{} + LIBPREFIX + name + LIBSUFFIX;
+      mmdeploy_load_library(libname.c_str());
     }
   }
 };

cmake/tensorrt.cmake

@@ -29,6 +29,7 @@ else ()
     message(FATAL_ERROR "Cannot find TensorRT libs")
 endif ()
 
+include(FindPackageHandleStandardArgs)
 find_package_handle_standard_args(TENSORRT DEFAULT_MSG TENSORRT_INCLUDE_DIR
         TENSORRT_LIBRARY)
 if (NOT TENSORRT_FOUND)

configs/mmcls/classification_coreml_static-384x384.py

@@ -0,0 +1,11 @@
+_base_ = ['./classification_coreml_dynamic-224x224-224x224.py']
+
+ir_config = dict(input_shape=(384, 384))
+backend_config = dict(model_inputs=[
+    dict(
+        input_shapes=dict(
+            input=dict(
+                min_shape=[1, 3, 384, 384],
+                max_shape=[1, 3, 384, 384],
+                default_shape=[1, 3, 384, 384])))
+])

configs/mmdet/detection/detection_coreml_static-608x608.py

@@ -0,0 +1,11 @@
+_base_ = ['../_base_/base_torchscript.py', '../../_base_/backends/coreml.py']
+
+ir_config = dict(input_shape=(608, 608))
+backend_config = dict(model_inputs=[
+    dict(
+        input_shapes=dict(
+            input=dict(
+                min_shape=[1, 3, 608, 608],
+                max_shape=[1, 3, 608, 608],
+                default_shape=[1, 3, 608, 608])))
+])

configs/mmedit/inpainting/inpainting_dynamic.py

@@ -0,0 +1,20 @@
+_base_ = ['./inpainting_static.py']
+
+onnx_config = dict(
+    dynamic_axes=dict(
+        masked_img={
+            0: 'batch',
+            2: 'height',
+            3: 'width'
+        },
+        mask={
+            0: 'batch',
+            2: 'height',
+            3: 'width'
+        },
+        output={
+            0: 'batch',
+            2: 'height',
+            3: 'width'
+        }),
+    input_shape=None)

configs/mmedit/inpainting/inpainting_onnxruntime_dynamic.py

@@ -0,0 +1 @@
+_base_ = ['./inpainting_dynamic.py', '../../_base_/backends/onnxruntime.py']

configs/mmedit/inpainting/inpainting_onnxruntime_static.py

@@ -0,0 +1,3 @@
+_base_ = ['./inpainting_static.py', '../../_base_/backends/onnxruntime.py']
+
+onnx_config = dict(input_shape=[256, 256])

configs/mmedit/inpainting/inpainting_static.py

@@ -0,0 +1,5 @@
+_base_ = ['../../_base_/onnx_config.py']
+
+codebase_config = dict(type='mmedit', task='Inpainting')
+onnx_config = dict(
+    input_names=['masked_img', 'mask'], output_names=['fake_img'])

configs/mmedit/inpainting/inpainting_tensorrt-fp16_static-256x256.py

@@ -0,0 +1,17 @@
+_base_ = ['./inpainting_static.py', '../../_base_/backends/tensorrt-fp16.py']
+
+onnx_config = dict(input_shape=[256, 256])
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                masked_img=dict(
+                    min_shape=[1, 3, 256, 256],
+                    opt_shape=[1, 3, 256, 256],
+                    max_shape=[1, 3, 256, 256]),
+                mask=dict(
+                    min_shape=[1, 1, 256, 256],
+                    opt_shape=[1, 1, 256, 256],
+                    max_shape=[1, 1, 256, 256])))
+    ])

configs/mmedit/inpainting/inpainting_tensorrt-int8_static-256x256.py

@@ -0,0 +1,17 @@
+_base_ = ['./inpainting_static.py', '../../_base_/backends/tensorrt-int8.py']
+
+onnx_config = dict(input_shape=[256, 256])
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                masked_img=dict(
+                    min_shape=[1, 3, 256, 256],
+                    opt_shape=[1, 3, 256, 256],
+                    max_shape=[1, 3, 256, 256]),
+                mask=dict(
+                    min_shape=[1, 1, 256, 256],
+                    opt_shape=[1, 1, 256, 256],
+                    max_shape=[1, 1, 256, 256])))
+    ])

configs/mmedit/inpainting/inpainting_tensorrt_static-256x256.py

@@ -0,0 +1,17 @@
+_base_ = ['./inpainting_static.py', '../../_base_/backends/tensorrt.py']
+
+onnx_config = dict(input_shape=[256, 256])
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                masked_img=dict(
+                    min_shape=[1, 3, 256, 256],
+                    opt_shape=[1, 3, 256, 256],
+                    max_shape=[1, 3, 256, 256]),
+                mask=dict(
+                    min_shape=[1, 1, 256, 256],
+                    opt_shape=[1, 1, 256, 256],
+                    max_shape=[1, 1, 256, 256])))
+    ])

configs/mmocr/text-recognition/text-recognition_coreml_dynamic-32x32-32x640.py

@@ -0,0 +1,13 @@
+_base_ = [
+    '../../_base_/torchscript_config.py', '../../_base_/backends/coreml.py'
+]
+
+codebase_config = dict(type='mmocr', task='TextRecognition')
+backend_config = dict(model_inputs=[
+    dict(
+        input_shapes=dict(
+            input=dict(
+                min_shape=[1, 3, 32, 32],
+                max_shape=[1, 3, 32, 640],
+                default_shape=[1, 3, 32, 64])))
+])

csrc/mmdeploy/apis/CMakeLists.txt

@@ -1,10 +1,5 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 
-# Python API depends on C++ API
-if (MMDEPLOY_BUILD_SDK_PYTHON_API)
-    set(MMDEPLOY_BUILD_SDK_CXX_API ON)
-endif ()
-
 add_subdirectory(c)
 add_subdirectory(cxx)
 add_subdirectory(java)

csrc/mmdeploy/apis/c/CMakeLists.txt

@@ -12,6 +12,9 @@ macro(add_object name)
         target_compile_options(${name} PRIVATE $<$<COMPILE_LANGUAGE:CXX>:-fvisibility=hidden>)
     endif ()
     target_link_libraries(${name} PRIVATE mmdeploy::core)
+    target_include_directories(${name} PUBLIC
+            $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}>
+            $<INSTALL_INTERFACE:include>)
     set(CAPI_OBJS ${CAPI_OBJS} ${name})
     mmdeploy_export(${name})
 endmacro()
@@ -31,6 +34,7 @@ foreach (TASK ${COMMON_LIST})
     mmdeploy_add_library(${TARGET_NAME})
     target_link_libraries(${TARGET_NAME} PRIVATE ${OBJECT_NAME})
     target_include_directories(${TARGET_NAME} PUBLIC
+            $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}>
             $<INSTALL_INTERFACE:include>)
     install(FILES ${CMAKE_CURRENT_SOURCE_DIR}/mmdeploy/${TASK}.h
             DESTINATION include/mmdeploy)
@@ -76,5 +80,14 @@ if (MMDEPLOY_BUILD_SDK_CSHARP_API OR MMDEPLOY_BUILD_SDK_MONOLITHIC)
     set_target_properties(mmdeploy PROPERTIES
             VERSION ${MMDEPLOY_VERSION}
             SOVERSION ${MMDEPLOY_VERSION_MAJOR})
-    mmdeploy_export(mmdeploy)
+    if (APPLE)
+            set_target_properties(mmdeploy PROPERTIES
+                    INSTALL_RPATH "@loader_path"
+                    BUILD_RPATH "@loader_path")
+    else ()
+            set_target_properties(mmdeploy PROPERTIES
+                    INSTALL_RPATH "\$ORIGIN"
+                    BUILD_RPATH "\$ORIGIN")
+    endif ()
+    mmdeploy_export_impl(mmdeploy)
 endif ()

csrc/mmdeploy/apis/c/mmdeploy/classifier.cpp

@@ -1,52 +1,21 @@
 // Copyright (c) OpenMMLab. All rights reserved.
 
-#include "classifier.h"
+#include "mmdeploy/classifier.h"
 
 #include <numeric>
 
-#include "common_internal.h"
-#include "handle.h"
 #include "mmdeploy/archive/value_archive.h"
 #include "mmdeploy/codebase/mmcls/mmcls.h"
+#include "mmdeploy/common_internal.h"
 #include "mmdeploy/core/device.h"
 #include "mmdeploy/core/graph.h"
 #include "mmdeploy/core/utils/formatter.h"
-#include "pipeline.h"
+#include "mmdeploy/handle.h"
+#include "mmdeploy/pipeline.h"
 
 using namespace mmdeploy;
 using namespace std;
 
-namespace {
-
-Value config_template(const Model& model) {
-  // clang-format off
-  static Value v{
-    {
-      "pipeline", {
-        {"input", {"img"}},
-        {"output", {"cls"}},
-        {
-          "tasks", {
-            {
-              {"name", "classifier"},
-              {"type", "Inference"},
-              {"params", {{"model", "TBD"}}},
-              {"input", {"img"}},
-              {"output", {"cls"}}
-            }
-          }
-        }
-      }
-    }
-  };
-  // clang-format on
-  auto config = v;
-  config["pipeline"]["tasks"][0]["params"]["model"] = model;
-  return config;
-}
-
-}  // namespace
-
 int mmdeploy_classifier_create(mmdeploy_model_t model, const char* device_name, int device_id,
                                mmdeploy_classifier_t* classifier) {
   mmdeploy_context_t context{};
@@ -73,8 +42,7 @@ int mmdeploy_classifier_create_by_path(const char* model_path, const char* devic
 
 int mmdeploy_classifier_create_v2(mmdeploy_model_t model, mmdeploy_context_t context,
                                   mmdeploy_classifier_t* classifier) {
-  auto config = config_template(*Cast(model));
-  return mmdeploy_pipeline_create_v3(Cast(&config), context, (mmdeploy_pipeline_t*)classifier);
+  return mmdeploy_pipeline_create_from_model(model, context, (mmdeploy_pipeline_t*)classifier);
 }
 
 int mmdeploy_classifier_create_input(const mmdeploy_mat_t* mats, int mat_count,

csrc/mmdeploy/apis/c/mmdeploy/classifier.h

@@ -8,9 +8,9 @@
 #ifndef MMDEPLOY_CLASSIFIER_H
 #define MMDEPLOY_CLASSIFIER_H
 
-#include "common.h"
-#include "executor.h"
-#include "model.h"
+#include "mmdeploy/common.h"
+#include "mmdeploy/executor.h"
+#include "mmdeploy/model.h"
 
 #ifdef __cplusplus
 extern "C" {

csrc/mmdeploy/apis/c/mmdeploy/common.cpp

@@ -1,9 +1,9 @@
-#include "common.h"
+#include "mmdeploy/common.h"
 
-#include "common_internal.h"
-#include "executor_internal.h"
+#include "mmdeploy/common_internal.h"
 #include "mmdeploy/core/mat.h"
 #include "mmdeploy/core/profiler.h"
+#include "mmdeploy/executor_internal.h"
 
 mmdeploy_value_t mmdeploy_value_copy(mmdeploy_value_t value) {
   if (!value) {

csrc/mmdeploy/apis/c/mmdeploy/common_internal.h

@@ -3,12 +3,12 @@
 #ifndef MMDEPLOY_CSRC_APIS_C_COMMON_INTERNAL_H_
 #define MMDEPLOY_CSRC_APIS_C_COMMON_INTERNAL_H_
 
-#include "common.h"
-#include "handle.h"
+#include "mmdeploy/common.h"
 #include "mmdeploy/core/mat.h"
 #include "mmdeploy/core/value.h"
-#include "model.h"
-#include "pipeline.h"
+#include "mmdeploy/handle.h"
+#include "mmdeploy/model.h"
+#include "mmdeploy/pipeline.h"
 
 using namespace mmdeploy;
 

csrc/mmdeploy/apis/c/mmdeploy/detector.cpp

@@ -1,6 +1,6 @@
 // Copyright (c) OpenMMLab. All rights reserved.
 
-#include "detector.h"
+#include "mmdeploy/detector.h"
 
 #include <deque>
 #include <numeric>
@@ -19,27 +19,11 @@
 using namespace std;
 using namespace mmdeploy;
 
-namespace {
-
-Value config_template(Model model) {
-  // clang-format off
-  return {
-    {"name", "detector"},
-    {"type", "Inference"},
-    {"params", {{"model", std::move(model)}}},
-    {"input", {"image"}},
-    {"output", {"dets"}}
-  };
-  // clang-format on
-}
-
 using ResultType = mmdeploy::Structure<mmdeploy_detection_t,                       //
                                        std::vector<int>,                           //
                                        std::deque<mmdeploy_instance_mask_t>,       //
                                        std::vector<mmdeploy::framework::Buffer>>;  //
 
-}  // namespace
-
 int mmdeploy_detector_create(mmdeploy_model_t model, const char* device_name, int device_id,
                              mmdeploy_detector_t* detector) {
   mmdeploy_context_t context{};
@@ -54,8 +38,7 @@ int mmdeploy_detector_create(mmdeploy_model_t model, const char* device_name, in
 
 int mmdeploy_detector_create_v2(mmdeploy_model_t model, mmdeploy_context_t context,
                                 mmdeploy_detector_t* detector) {
-  auto config = config_template(*Cast(model));
-  return mmdeploy_pipeline_create_v3(Cast(&config), context, (mmdeploy_pipeline_t*)detector);
+  return mmdeploy_pipeline_create_from_model(model, context, (mmdeploy_pipeline_t*)detector);
 }
 
 int mmdeploy_detector_create_by_path(const char* model_path, const char* device_name, int device_id,

csrc/mmdeploy/apis/c/mmdeploy/detector.h

@@ -8,9 +8,9 @@
 #ifndef MMDEPLOY_DETECTOR_H
 #define MMDEPLOY_DETECTOR_H
 
-#include "common.h"
-#include "executor.h"
-#include "model.h"
+#include "mmdeploy/common.h"
+#include "mmdeploy/executor.h"
+#include "mmdeploy/model.h"
 
 #ifdef __cplusplus
 extern "C" {

csrc/mmdeploy/apis/c/mmdeploy/executor.cpp

@@ -1,11 +1,11 @@
 // Copyright (c) OpenMMLab. All rights reserved.
 
-#include "executor.h"
+#include "mmdeploy/executor.h"
 
-#include "common.h"
-#include "common_internal.h"
-#include "executor_internal.h"
+#include "mmdeploy/common.h"
+#include "mmdeploy/common_internal.h"
 #include "mmdeploy/execution/when_all_value.h"
+#include "mmdeploy/executor_internal.h"
 
 using namespace mmdeploy;
 

csrc/mmdeploy/apis/c/mmdeploy/executor.h

@@ -3,7 +3,7 @@
 #ifndef MMDEPLOY_CSRC_APIS_C_EXECUTOR_H_
 #define MMDEPLOY_CSRC_APIS_C_EXECUTOR_H_
 
-#include "common.h"
+#include "mmdeploy/common.h"
 
 #if __cplusplus
 extern "C" {

csrc/mmdeploy/apis/c/mmdeploy/executor_internal.h

@@ -3,8 +3,8 @@
 #ifndef MMDEPLOY_CSRC_APIS_C_EXECUTOR_INTERNAL_H_
 #define MMDEPLOY_CSRC_APIS_C_EXECUTOR_INTERNAL_H_
 
-#include "executor.h"
 #include "mmdeploy/execution/schedulers/registry.h"
+#include "mmdeploy/executor.h"
 
 using namespace mmdeploy;
 

csrc/mmdeploy/apis/c/mmdeploy/model.cpp

@@ -1,11 +1,11 @@
 // Copyright (c) OpenMMLab. All rights reserved.
 
 // clang-format off
-#include "model.h"
+#include "mmdeploy/model.h"
 
 #include <memory>
 
-#include "common_internal.h"
+#include "mmdeploy/common_internal.h"
 #include "mmdeploy/core/logger.h"
 #include "mmdeploy/core/model.h"
 // clang-format on

csrc/mmdeploy/apis/c/mmdeploy/model.h

@@ -8,7 +8,7 @@
 #ifndef MMDEPLOY_SRC_APIS_C_MODEL_H_
 #define MMDEPLOY_SRC_APIS_C_MODEL_H_
 
-#include "common.h"
+#include "mmdeploy/common.h"
 
 #ifdef __cplusplus
 extern "C" {

csrc/mmdeploy/apis/c/mmdeploy/pipeline.cpp

@@ -1,10 +1,10 @@
 // Copyright (c) OpenMMLab. All rights reserved.
 
-#include "pipeline.h"
+#include "mmdeploy/pipeline.h"
 
-#include "common_internal.h"
-#include "executor_internal.h"
-#include "handle.h"
+#include "mmdeploy/common_internal.h"
+#include "mmdeploy/executor_internal.h"
+#include "mmdeploy/handle.h"
 
 int mmdeploy_pipeline_create_v3(mmdeploy_value_t config, mmdeploy_context_t context,
                                 mmdeploy_pipeline_t* pipeline) {
@@ -27,6 +27,15 @@ int mmdeploy_pipeline_create_v3(mmdeploy_value_t config, mmdeploy_context_t cont
   return MMDEPLOY_E_FAIL;
 }
 
+int mmdeploy_pipeline_create_from_model(mmdeploy_model_t model, mmdeploy_context_t context,
+                                        mmdeploy_pipeline_t* pipeline) {
+  auto config = Cast(model)->ReadConfig("pipeline.json");
+  auto _context = *Cast(context);
+  _context["model"] = *Cast(model);
+  return mmdeploy_pipeline_create_v3(Cast(&config.value()), (mmdeploy_context_t)&_context,
+                                     pipeline);
+}
+
 int mmdeploy_pipeline_apply_async(mmdeploy_pipeline_t pipeline, mmdeploy_sender_t input,
                                   mmdeploy_sender_t* output) {
   if (!pipeline || !input || !output) {

csrc/mmdeploy/apis/c/mmdeploy/pipeline.h

@@ -3,8 +3,9 @@
 #ifndef MMDEPLOY_CSRC_APIS_C_PIPELINE_H_
 #define MMDEPLOY_CSRC_APIS_C_PIPELINE_H_
 
-#include "common.h"
-#include "executor.h"
+#include "mmdeploy/common.h"
+#include "mmdeploy/executor.h"
+#include "mmdeploy/model.h"
 
 #ifdef __cplusplus
 extern "C" {
@@ -24,6 +25,16 @@ typedef struct mmdeploy_pipeline* mmdeploy_pipeline_t;
  */
 MMDEPLOY_API int mmdeploy_pipeline_create_v3(mmdeploy_value_t config, mmdeploy_context_t context,
                                              mmdeploy_pipeline_t* pipeline);
+/**
+ * Create pipeline from internal pipeline config of the model
+ * @param model
+ * @param context
+ * @param pipeline
+ * @return
+ */
+MMDEPLOY_API int mmdeploy_pipeline_create_from_model(mmdeploy_model_t model,
+                                                     mmdeploy_context_t context,
+                                                     mmdeploy_pipeline_t* pipeline);
 
 /**
  * @brief Apply pipeline

csrc/mmdeploy/apis/c/mmdeploy/pose_detector.cpp

@@ -1,37 +1,21 @@
 // Copyright (c) OpenMMLab. All rights reserved.
 
-#include "pose_detector.h"
+#include "mmdeploy/pose_detector.h"
 
 #include <numeric>
 
-#include "common_internal.h"
-#include "handle.h"
 #include "mmdeploy/codebase/mmpose/mmpose.h"
+#include "mmdeploy/common_internal.h"
 #include "mmdeploy/core/device.h"
 #include "mmdeploy/core/graph.h"
 #include "mmdeploy/core/mat.h"
 #include "mmdeploy/core/utils/formatter.h"
-#include "pipeline.h"
+#include "mmdeploy/handle.h"
+#include "mmdeploy/pipeline.h"
 
 using namespace std;
 using namespace mmdeploy;
 
-namespace {
-
-Value config_template(const Model& model) {
-  // clang-format off
-  return {
-    {"name", "pose-detector"},
-    {"type", "Inference"},
-    {"params", {{"model", model}, {"batch_size", 1}}},
-    {"input", {"image"}},
-    {"output", {"dets"}}
-  };
-  // clang-format on
-}
-
-}  // namespace
-
 int mmdeploy_pose_detector_create(mmdeploy_model_t model, const char* device_name, int device_id,
                                   mmdeploy_pose_detector_t* detector) {
   mmdeploy_context_t context{};
@@ -95,8 +79,7 @@ void mmdeploy_pose_detector_destroy(mmdeploy_pose_detector_t detector) {
 
 int mmdeploy_pose_detector_create_v2(mmdeploy_model_t model, mmdeploy_context_t context,
                                      mmdeploy_pose_detector_t* detector) {
-  auto config = config_template(*Cast(model));
-  return mmdeploy_pipeline_create_v3(Cast(&config), context, (mmdeploy_pipeline_t*)detector);
+  return mmdeploy_pipeline_create_from_model(model, context, (mmdeploy_pipeline_t*)detector);
 }
 
 int mmdeploy_pose_detector_create_input(const mmdeploy_mat_t* mats, int mat_count,
@@ -117,7 +100,7 @@ int mmdeploy_pose_detector_create_input(const mmdeploy_mat_t* mats, int mat_coun
       } else {
         b = {0, 0, img.width(), img.height(), 1.0};
       }
-      input_images.push_back({{"ori_img", img}, {"bbox", std::move(b)}, {"rotation", 0.f}});
+      input_images.push_back({{"ori_img", img}, {"bbox", std::move(b)}});
     };
 
     for (int i = 0; i < mat_count; ++i) {

csrc/mmdeploy/apis/c/mmdeploy/pose_detector.h

@@ -8,9 +8,9 @@
 #ifndef MMDEPLOY_SRC_APIS_C_POSE_DETECTOR_H_
 #define MMDEPLOY_SRC_APIS_C_POSE_DETECTOR_H_
 
-#include "common.h"
-#include "executor.h"
-#include "model.h"
+#include "mmdeploy/common.h"
+#include "mmdeploy/executor.h"
+#include "mmdeploy/model.h"
 
 #ifdef __cplusplus
 extern "C" {

csrc/mmdeploy/apis/c/mmdeploy/pose_tracker.cpp

@@ -0,0 +1,225 @@
+// Copyright (c) OpenMMLab. All rights reserved.
+
+#include "mmdeploy/pose_tracker.h"
+
+#include "mmdeploy/archive/json_archive.h"
+#include "mmdeploy/archive/value_archive.h"
+#include "mmdeploy/codebase/mmpose/pose_tracker/common.h"
+#include "mmdeploy/common_internal.h"
+#include "mmdeploy/core/mpl/structure.h"
+#include "mmdeploy/pipeline.h"
+
+namespace mmdeploy {
+
+using namespace framework;
+
+}  // namespace mmdeploy
+
+using namespace mmdeploy;
+
+namespace {
+
+Value config_template() {
+  static const auto json = R"(
+{
+  "type": "Pipeline",
+  "input": ["img", "force_det", "state"],
+  "output": "targets",
+  "tasks": [
+    {
+      "type": "Task",
+      "name": "prepare",
+      "module": "pose_tracker::Prepare",
+      "input": ["img", "force_det", "state"],
+      "output": "use_det"
+    },
+    {
+      "type": "Task",
+      "module": "Transform",
+      "name": "preload",
+      "input": "img",
+      "output": "data",
+      "transforms": [ { "type": "LoadImageFromFile" } ]
+    },
+    {
+      "type": "Cond",
+      "name": "cond",
+      "input": ["use_det", "data"],
+      "output": "dets",
+      "body": {
+        "name": "detection",
+        "type": "Inference",
+        "params": { "model": "detection" }
+      }
+    },
+    {
+      "type": "Task",
+      "name": "process_bboxes",
+      "module": "pose_tracker::ProcessBboxes",
+      "input": ["dets", "data", "state"],
+      "output": ["rois", "track_ids"]
+    },
+    {
+      "input": "*rois",
+      "output": "*keypoints",
+      "name": "pose",
+      "type": "Inference",
+      "params": { "model": "pose" }
+    },
+    {
+      "type": "Task",
+      "name": "track_step",
+      "module": "pose_tracker::TrackStep",
+      "scheduler": "pool",
+      "input": ["keypoints", "track_ids", "state"],
+      "output": "targets"
+    }
+  ]
+}
+)"_json;
+  static const auto config = from_json<Value>(json);
+  return config;
+}
+
+}  // namespace
+
+int mmdeploy_pose_tracker_default_params(mmdeploy_pose_tracker_param_t* params) {
+  mmpose::_pose_tracker::SetDefaultParams(*params);
+  return 0;
+}
+
+int mmdeploy_pose_tracker_create(mmdeploy_model_t det_model, mmdeploy_model_t pose_model,
+                                 mmdeploy_context_t context, mmdeploy_pose_tracker_t* pipeline) {
+  mmdeploy_context_add(context, MMDEPLOY_TYPE_MODEL, "detection", det_model);
+  mmdeploy_context_add(context, MMDEPLOY_TYPE_MODEL, "pose", pose_model);
+  auto config = config_template();
+  return mmdeploy_pipeline_create_v3(Cast(&config), context, (mmdeploy_pipeline_t*)pipeline);
+}
+
+void mmdeploy_pose_tracker_destroy(mmdeploy_pose_tracker_t pipeline) {
+  mmdeploy_pipeline_destroy((mmdeploy_pipeline_t)pipeline);
+}
+
+int mmdeploy_pose_tracker_create_state(mmdeploy_pose_tracker_t pipeline,
+                                       const mmdeploy_pose_tracker_param_t* params,
+                                       mmdeploy_pose_tracker_state_t* state) {
+  try {
+    auto create_fn = gRegistry<Module>().Create("pose_tracker::Create", Value()).value();
+    *state = reinterpret_cast<mmdeploy_pose_tracker_state_t>(new Value(
+        create_fn->Process({const_cast<mmdeploy_pose_tracker_param_t*>(params)}).value()[0]));
+    return MMDEPLOY_SUCCESS;
+  } catch (const std::exception& e) {
+    MMDEPLOY_ERROR("unhandled exception: {}", e.what());
+  } catch (...) {
+    MMDEPLOY_ERROR("unknown exception caught");
+  }
+  return MMDEPLOY_E_FAIL;
+}
+
+void mmdeploy_pose_tracker_destroy_state(mmdeploy_pose_tracker_state_t state) {
+  delete reinterpret_cast<Value*>(state);
+}
+
+int mmdeploy_pose_tracker_create_input(mmdeploy_pose_tracker_state_t* states,
+                                       const mmdeploy_mat_t* frames, const int32_t* use_detect,
+                                       int batch_size, mmdeploy_value_t* value) {
+  try {
+    Value::Array images;
+    Value::Array use_dets;
+    Value::Array trackers;
+    for (int i = 0; i < batch_size; ++i) {
+      images.push_back({{"ori_img", Cast(frames[i])}});
+      use_dets.emplace_back(use_detect ? use_detect[i] : -1);
+      trackers.push_back(*reinterpret_cast<Value*>(states[i]));
+    }
+    *value = Take(Value{std::move(images), std::move(use_dets), std::move(trackers)});
+    return MMDEPLOY_SUCCESS;
+  } catch (const std::exception& e) {
+    MMDEPLOY_ERROR("unhandled exception: {}", e.what());
+  } catch (...) {
+    MMDEPLOY_ERROR("unknown exception caught");
+  }
+  return MMDEPLOY_E_FAIL;
+}
+
+using ResultType = mmdeploy::Structure<mmdeploy_pose_tracker_target_t, std::vector<int32_t>,
+                                       std::vector<mmpose::_pose_tracker::TrackerResult>>;
+
+int mmdeploy_pose_tracker_get_result(mmdeploy_value_t output,
+                                     mmdeploy_pose_tracker_target_t** results,
+                                     int32_t** result_count) {
+  if (!output || !results) {
+    return MMDEPLOY_E_INVALID_ARG;
+  }
+  try {
+    // convert result from Values
+    std::vector<mmpose::_pose_tracker::TrackerResult> res;
+    from_value(Cast(output)->front(), res);
+
+    size_t total = 0;
+    for (const auto& r : res) {
+      total += r.bboxes.size();
+    }
+
+    // preserve space for the output structure
+    ResultType result_type({total, 1, 1});
+    auto [result_data, result_cnt, result_holder] = result_type.pointers();
+
+    auto result_ptr = result_data;
+
+    result_holder->swap(res);
+
+    // build output structure
+    for (auto& r : *result_holder) {
+      for (int j = 0; j < r.bboxes.size(); ++j) {
+        auto& p = *result_ptr++;
+        p.keypoint_count = static_cast<int32_t>(r.keypoints[j].size());
+        p.keypoints = r.keypoints[j].data();
+        p.scores = r.scores[j].data();
+        p.bbox = r.bboxes[j];
+        p.target_id = r.track_ids[j];
+      }
+      result_cnt->push_back(r.bboxes.size());
+      // debug info
+      //  p.reserved0 = new std::vector(r.pose_input_bboxes);
+      //  p.reserved1 = new std::vector(r.pose_output_bboxes);
+    }
+
+    *results = result_data;
+    *result_count = result_cnt->data();
+    result_type.release();
+
+    return MMDEPLOY_SUCCESS;
+
+  } catch (const std::exception& e) {
+    MMDEPLOY_ERROR("unhandled exception: {}", e.what());
+  } catch (...) {
+    MMDEPLOY_ERROR("unknown exception caught");
+  }
+  return MMDEPLOY_E_FAIL;
+}
+
+int mmdeploy_pose_tracker_apply(mmdeploy_pose_tracker_t pipeline,
+                                mmdeploy_pose_tracker_state_t* states, const mmdeploy_mat_t* frames,
+                                const int32_t* use_detect, int32_t count,
+                                mmdeploy_pose_tracker_target_t** results, int32_t** result_count) {
+  wrapped<mmdeploy_value_t> input;
+  if (auto ec =
+          mmdeploy_pose_tracker_create_input(states, frames, use_detect, count, input.ptr())) {
+    return ec;
+  }
+  wrapped<mmdeploy_value_t> output;
+  if (auto ec = mmdeploy_pipeline_apply((mmdeploy_pipeline_t)pipeline, input, output.ptr())) {
+    return ec;
+  }
+  if (auto ec = mmdeploy_pose_tracker_get_result(output, results, result_count)) {
+    return ec;
+  }
+  return MMDEPLOY_SUCCESS;
+}
+
+void mmdeploy_pose_tracker_release_result(mmdeploy_pose_tracker_target_t* results,
+                                          const int32_t* result_count, int count) {
+  auto total = std::accumulate(result_count, result_count + count, 0);
+  ResultType deleter({static_cast<size_t>(total), 1, 1}, results);
+}

csrc/mmdeploy/apis/c/mmdeploy/pose_tracker.h

@@ -0,0 +1,158 @@
+// Copyright (c) OpenMMLab. All rights reserved.
+
+/**
+ * @file pose_tracker.h
+ * @brief Pose tracker C API
+ */
+
+#ifndef MMDEPLOY_POSE_TRACKER_H
+#define MMDEPLOY_POSE_TRACKER_H
+
+#include "mmdeploy/common.h"
+#include "mmdeploy/detector.h"
+#include "mmdeploy/model.h"
+#include "mmdeploy/pose_detector.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+typedef struct mmdeploy_pose_tracker* mmdeploy_pose_tracker_t;
+typedef struct mmdeploy_pose_tracker_state* mmdeploy_pose_tracker_state_t;
+
+typedef struct mmdeploy_pose_tracker_param_t {
+  // detection interval, default = 1
+  int32_t det_interval;
+  // detection label use for pose estimation, default = 0
+  int32_t det_label;
+  // detection score threshold, default = 0.5
+  float det_thr;
+  // detection minimum bbox size (compute as sqrt(area)), default = -1
+  float det_min_bbox_size;
+  // nms iou threshold for merging detected bboxes and bboxes from tracked targets, default = 0.7
+  float det_nms_thr;
+
+  // max number of bboxes used for pose estimation per frame, default = -1
+  int32_t pose_max_num_bboxes;
+  // threshold for visible key-points, default = 0.5
+  float pose_kpt_thr;
+  // min number of key-points for valid poses (-1 indicates ceil(n_kpts/2)), default = -1
+  int32_t pose_min_keypoints;
+  // scale for expanding key-points to bbox, default = 1.25
+  float pose_bbox_scale;
+  // min pose bbox size, tracks with bbox size smaller than the threshold will be dropped,
+  // default = -1
+  float pose_min_bbox_size;
+  // nms oks/iou threshold for suppressing overlapped poses, useful when multiple pose estimations
+  // collapse to the same target, default = 0.5
+  float pose_nms_thr;
+  // keypoint sigmas for computing OKS, will use IOU if not set, default = nullptr
+  float* keypoint_sigmas;
+  // size of keypoint sigma array, must be consistent with the number of key-points, default = 0
+  int32_t keypoint_sigmas_size;
+
+  // iou threshold for associating missing tracks, default = 0.4
+  float track_iou_thr;
+  // max number of missing frames before a missing tracks is removed, default = 10
+  int32_t track_max_missing;
+  // track history size, default = 1
+  int32_t track_history_size;
+
+  // weight of position for setting covariance matrices of kalman filters, default = 0.05
+  float std_weight_position;
+  // weight of velocity for setting covariance matrices of kalman filters, default = 0.00625
+  float std_weight_velocity;
+
+  // params for the one-euro filter for smoothing the outputs - (beta, fc_min, fc_derivative)
+  // default = (0.007, 1, 1)
+  float smooth_params[3];
+} mmdeploy_pose_tracker_param_t;
+
+typedef struct mmdeploy_pose_tracker_target_t {
+  mmdeploy_point_t* keypoints;  // key-points of the target
+  int32_t keypoint_count;       // size of `keypoints` array
+  float* scores;                // scores of each key-point
+  mmdeploy_rect_t bbox;         // estimated bbox from key-points
+  uint32_t target_id;           // target id from internal tracker
+} mmdeploy_pose_tracker_target_t;
+
+/**
+ * @brief Fill params with default parameters
+ * @param[in,out] params
+ * @return status of the operation
+ */
+MMDEPLOY_API int mmdeploy_pose_tracker_default_params(mmdeploy_pose_tracker_param_t* params);
+
+/**
+ * @brief Create pose tracker pipeline
+ * @param[in] det_model detection model object, created by \ref mmdeploy_model_create
+ * @param[in] pose_model pose model object
+ * @param[in] context context object describing execution environment (device, profiler, etc...),
+ * created by \ref mmdeploy_context_create
+ * @param[out] pipeline handle of the created pipeline
+ * @return status of the operation
+ */
+MMDEPLOY_API int mmdeploy_pose_tracker_create(mmdeploy_model_t det_model,
+                                              mmdeploy_model_t pose_model,
+                                              mmdeploy_context_t context,
+                                              mmdeploy_pose_tracker_t* pipeline);
+
+/**
+ * @brief Destroy pose tracker pipeline
+ * @param[in] pipeline
+ */
+MMDEPLOY_API void mmdeploy_pose_tracker_destroy(mmdeploy_pose_tracker_t pipeline);
+
+/**
+ * @brief Create a tracker state handle corresponds to a video stream
+ * @param[in] pipeline handle of a pose tracker pipeline
+ * @param[in] params params for creating the tracker state
+ * @param[out] state handle of the created tracker state
+ * @return status of the operation
+ */
+MMDEPLOY_API int mmdeploy_pose_tracker_create_state(mmdeploy_pose_tracker_t pipeline,
+                                                    const mmdeploy_pose_tracker_param_t* params,
+                                                    mmdeploy_pose_tracker_state_t* state);
+
+/**
+ * @brief Destroy tracker state
+ * @param[in] state handle of the tracker state
+ */
+MMDEPLOY_API void mmdeploy_pose_tracker_destroy_state(mmdeploy_pose_tracker_state_t state);
+
+/**
+ * @brief Apply pose tracker pipeline, notice that this function supports batch operation by feeding
+ * arrays of size \p count to \p states, \p frames and \p use_detect
+ * @param[in] pipeline handle of a pose tracker pipeline
+ * @param[in] states tracker states handles, array of size \p count
+ * @param[in] frames input frames of size \p count
+ * @param[in] use_detect control the use of detector, array of size \p count
+ *   -1: use params.det_interval, 0: don't use detector, 1: force use detector
+ * @param[in] count batch size
+ * @param[out] results a linear buffer contains the tracked targets of input frames. Should be
+ * released by \ref mmdeploy_pose_tracker_release_result
+ * @param[out] result_count a linear buffer of size \p count contains the number of tracked
+ * targets of the frames. Should be released by \ref mmdeploy_pose_tracker_release_result
+ * @return status of the operation
+ */
+MMDEPLOY_API int mmdeploy_pose_tracker_apply(mmdeploy_pose_tracker_t pipeline,
+                                             mmdeploy_pose_tracker_state_t* states,
+                                             const mmdeploy_mat_t* frames,
+                                             const int32_t* use_detect, int32_t count,
+                                             mmdeploy_pose_tracker_target_t** results,
+                                             int32_t** result_count);
+
+/**
+ * @brief Release result objects
+ * @param[in] results
+ * @param[in] result_count
+ * @param[in] count
+ */
+MMDEPLOY_API void mmdeploy_pose_tracker_release_result(mmdeploy_pose_tracker_target_t* results,
+                                                       const int32_t* result_count, int count);
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif  // MMDEPLOY_POSE_TRACKER_H

csrc/mmdeploy/apis/c/mmdeploy/restorer.cpp

@@ -1,37 +1,21 @@
 // Copyright (c) OpenMMLab. All rights reserved.
 
-#include "restorer.h"
+#include "mmdeploy/restorer.h"
 
-#include "common_internal.h"
-#include "executor_internal.h"
-#include "handle.h"
 #include "mmdeploy/codebase/mmedit/mmedit.h"
+#include "mmdeploy/common_internal.h"
 #include "mmdeploy/core/device.h"
 #include "mmdeploy/core/graph.h"
 #include "mmdeploy/core/mpl/structure.h"
 #include "mmdeploy/core/utils/formatter.h"
-#include "pipeline.h"
+#include "mmdeploy/executor_internal.h"
+#include "mmdeploy/handle.h"
+#include "mmdeploy/pipeline.h"
 
 using namespace mmdeploy;
 
-namespace {
-
-Value config_template(const Model& model) {
-  // clang-format off
-  return {
-    {"name", "restorer"},
-    {"type", "Inference"},
-    {"params", {{"model", model}}},
-    {"input", {"img"}},
-    {"output", {"out"}}
-  };
-  // clang-format on
-}
-
 using ResultType = mmdeploy::Structure<mmdeploy_mat_t, mmdeploy::framework::Buffer>;
 
-}  // namespace
-
 int mmdeploy_restorer_create(mmdeploy_model_t model, const char* device_name, int device_id,
                              mmdeploy_restorer_t* restorer) {
   mmdeploy_context_t context{};
@@ -81,8 +65,7 @@ void mmdeploy_restorer_destroy(mmdeploy_restorer_t restorer) {
 
 int mmdeploy_restorer_create_v2(mmdeploy_model_t model, mmdeploy_context_t context,
                                 mmdeploy_restorer_t* restorer) {
-  auto config = config_template(*Cast(model));
-  return mmdeploy_pipeline_create_v3(Cast(&config), context, (mmdeploy_pipeline_t*)restorer);
+  return mmdeploy_pipeline_create_from_model(model, context, (mmdeploy_pipeline_t*)restorer);
 }
 
 int mmdeploy_restorer_create_input(const mmdeploy_mat_t* mats, int mat_count,

csrc/mmdeploy/apis/c/mmdeploy/restorer.h

@@ -8,9 +8,9 @@
 #ifndef MMDEPLOY_SRC_APIS_C_RESTORER_H_
 #define MMDEPLOY_SRC_APIS_C_RESTORER_H_
 
-#include "common.h"
-#include "executor.h"
-#include "model.h"
+#include "mmdeploy/common.h"
+#include "mmdeploy/executor.h"
+#include "mmdeploy/model.h"
 
 #ifdef __cplusplus
 extern "C" {

csrc/mmdeploy/apis/c/mmdeploy/rotated_detector.cpp

@@ -1,36 +1,20 @@
 // Copyright (c) OpenMMLab. All rights reserved.
 
-#include "rotated_detector.h"
+#include "mmdeploy/rotated_detector.h"
 
 #include <numeric>
 
-#include "common_internal.h"
-#include "handle.h"
 #include "mmdeploy/codebase/mmrotate/mmrotate.h"
+#include "mmdeploy/common_internal.h"
 #include "mmdeploy/core/graph.h"
 #include "mmdeploy/core/mat.h"
 #include "mmdeploy/core/utils/formatter.h"
-#include "pipeline.h"
+#include "mmdeploy/handle.h"
+#include "mmdeploy/pipeline.h"
 
 using namespace std;
 using namespace mmdeploy;
 
-namespace {
-
-Value config_template(const Model& model) {
-  // clang-format off
-  return  {
-    {"name", "mmrotate"},
-    {"type", "Inference"},
-    {"params", {{"model", model}}},
-    {"input", {"image"}},
-    {"output", {"det"}}
-  };
-  // clang-format on
-}
-
-}  // namespace
-
 int mmdeploy_rotated_detector_create(mmdeploy_model_t model, const char* device_name, int device_id,
                                      mmdeploy_rotated_detector_t* detector) {
   mmdeploy_context_t context{};
@@ -84,8 +68,7 @@ void mmdeploy_rotated_detector_destroy(mmdeploy_rotated_detector_t detector) {
 
 int mmdeploy_rotated_detector_create_v2(mmdeploy_model_t model, mmdeploy_context_t context,
                                         mmdeploy_rotated_detector_t* detector) {
-  auto config = config_template(*Cast(model));
-  return mmdeploy_pipeline_create_v3(Cast(&config), context, (mmdeploy_pipeline_t*)detector);
+  return mmdeploy_pipeline_create_from_model(model, context, (mmdeploy_pipeline_t*)detector);
 }
 
 int mmdeploy_rotated_detector_create_input(const mmdeploy_mat_t* mats, int mat_count,

csrc/mmdeploy/apis/c/mmdeploy/rotated_detector.h

@@ -8,9 +8,9 @@
 #ifndef MMDEPLOY_SRC_APIS_C_ROTATED_DETECTOR_H_
 #define MMDEPLOY_SRC_APIS_C_ROTATED_DETECTOR_H_
 
-#include "common.h"
-#include "executor.h"
-#include "model.h"
+#include "mmdeploy/common.h"
+#include "mmdeploy/executor.h"
+#include "mmdeploy/model.h"
 
 #ifdef __cplusplus
 extern "C" {

csrc/mmdeploy/apis/c/mmdeploy/segmentor.cpp

@@ -1,39 +1,23 @@
 // Copyright (c) OpenMMLab. All rights reserved.
 
-#include "segmentor.h"
+#include "mmdeploy/segmentor.h"
 
-#include "common_internal.h"
-#include "handle.h"
 #include "mmdeploy/codebase/mmseg/mmseg.h"
+#include "mmdeploy/common_internal.h"
 #include "mmdeploy/core/device.h"
 #include "mmdeploy/core/graph.h"
 #include "mmdeploy/core/mat.h"
 #include "mmdeploy/core/mpl/structure.h"
 #include "mmdeploy/core/tensor.h"
 #include "mmdeploy/core/utils/formatter.h"
-#include "pipeline.h"
+#include "mmdeploy/handle.h"
+#include "mmdeploy/pipeline.h"
 
 using namespace std;
 using namespace mmdeploy;
 
-namespace {
-
-Value config_template(const Model& model) {
-  // clang-format off
-  return {
-    {"name", "segmentor"},
-    {"type", "Inference"},
-    {"params", {{"model", model}}},
-    {"input", {"img"}},
-    {"output", {"mask"}}
-  };
-  // clang-format on
-}
-
 using ResultType = mmdeploy::Structure<mmdeploy_segmentation_t, mmdeploy::framework::Buffer>;
 
-}  // namespace
-
 int mmdeploy_segmentor_create(mmdeploy_model_t model, const char* device_name, int device_id,
                               mmdeploy_segmentor_t* segmentor) {
   mmdeploy_context_t context{};
@@ -83,8 +67,7 @@ void mmdeploy_segmentor_destroy(mmdeploy_segmentor_t segmentor) {
 
 int mmdeploy_segmentor_create_v2(mmdeploy_model_t model, mmdeploy_context_t context,
                                  mmdeploy_segmentor_t* segmentor) {
-  auto config = config_template(*Cast(model));
-  return mmdeploy_pipeline_create_v3(Cast(&config), context, (mmdeploy_pipeline_t*)segmentor);
+  return mmdeploy_pipeline_create_from_model(model, context, (mmdeploy_pipeline_t*)segmentor);
 }
 
 int mmdeploy_segmentor_create_input(const mmdeploy_mat_t* mats, int mat_count,
@@ -119,10 +102,17 @@ int mmdeploy_segmentor_get_result(mmdeploy_value_t output, mmdeploy_segmentation
       results_ptr->height = segmentor_output.height;
       results_ptr->width = segmentor_output.width;
       results_ptr->classes = segmentor_output.classes;
-      auto mask_size = results_ptr->height * results_ptr->width;
       auto& mask = segmentor_output.mask;
-      results_ptr->mask = mask.data<int>();
-      buffers[i] = mask.buffer();
+      auto& score = segmentor_output.score;
+      results_ptr->mask = nullptr;
+      results_ptr->score = nullptr;
+      if (mask.shape().size()) {
+        results_ptr->mask = mask.data<int>();
+        buffers[i] = mask.buffer();
+      } else {
+        results_ptr->score = score.data<float>();
+        buffers[i] = score.buffer();
+      }
     }
 
     *results = results_data;

csrc/mmdeploy/apis/c/mmdeploy/segmentor.h

@@ -8,20 +8,23 @@
 #ifndef MMDEPLOY_SEGMENTOR_H
 #define MMDEPLOY_SEGMENTOR_H
 
-#include "common.h"
-#include "executor.h"
-#include "model.h"
+#include "mmdeploy/common.h"
+#include "mmdeploy/executor.h"
+#include "mmdeploy/model.h"
 
 #ifdef __cplusplus
 extern "C" {
 #endif
 
 typedef struct mmdeploy_segmentation_t {
-  int height;   ///< height of \p mask that equals to the input image's height
-  int width;    ///< width of \p mask that equals to the input image's width
-  int classes;  ///< the number of labels in \p mask
-  int* mask;    ///< segmentation mask of the input image, in which mask[i * width + j] indicates
-                ///< the label id of pixel at (i, j)
+  int height;    ///< height of \p mask that equals to the input image's height
+  int width;     ///< width of \p mask that equals to the input image's width
+  int classes;   ///< the number of labels in \p mask
+  int* mask;     ///< segmentation mask of the input image, in which mask[i * width + j] indicates
+                 ///< the label id of pixel at (i, j), this field might be null
+  float* score;  ///< segmentation score map of the input image in CHW format, in which
+                 ///< score[height * width * k + i * width + j] indicates the score
+                 ///< of class k at pixel (i, j), this field might be null
 } mmdeploy_segmentation_t;
 
 typedef struct mmdeploy_segmentor* mmdeploy_segmentor_t;

csrc/mmdeploy/apis/c/mmdeploy/text_detector.cpp

@@ -1,37 +1,21 @@
 // Copyright (c) OpenMMLab. All rights reserved.
 
-#include "text_detector.h"
+#include "mmdeploy/text_detector.h"
 
 #include <numeric>
 
-#include "common_internal.h"
-#include "executor_internal.h"
 #include "mmdeploy/codebase/mmocr/mmocr.h"
+#include "mmdeploy/common_internal.h"
 #include "mmdeploy/core/model.h"
 #include "mmdeploy/core/status_code.h"
 #include "mmdeploy/core/utils/formatter.h"
-#include "model.h"
-#include "pipeline.h"
+#include "mmdeploy/executor_internal.h"
+#include "mmdeploy/model.h"
+#include "mmdeploy/pipeline.h"
 
 using namespace std;
 using namespace mmdeploy;
 
-namespace {
-
-Value config_template(const Model& model) {
-  // clang-format off
-  return {
-    {"name", "detector"},
-    {"type", "Inference"},
-    {"params", {{"model", model}}},
-    {"input", {"img"}},
-    {"output", {"dets"}}
-  };
-  // clang-format on
-}
-
-}  // namespace
-
 int mmdeploy_text_detector_create(mmdeploy_model_t model, const char* device_name, int device_id,
                                   mmdeploy_text_detector_t* detector) {
   mmdeploy_context_t context{};
@@ -46,8 +30,7 @@ int mmdeploy_text_detector_create(mmdeploy_model_t model, const char* device_nam
 
 int mmdeploy_text_detector_create_v2(mmdeploy_model_t model, mmdeploy_context_t context,
                                      mmdeploy_text_detector_t* detector) {
-  auto config = config_template(*Cast(model));
-  return mmdeploy_pipeline_create_v3(Cast(&config), context, (mmdeploy_pipeline_t*)detector);
+  return mmdeploy_pipeline_create_from_model(model, context, (mmdeploy_pipeline_t*)detector);
 }
 
 int mmdeploy_text_detector_create_by_path(const char* model_path, const char* device_name,

csrc/mmdeploy/apis/c/mmdeploy/text_detector.h

@@ -8,9 +8,9 @@
 #ifndef MMDEPLOY_TEXT_DETECTOR_H
 #define MMDEPLOY_TEXT_DETECTOR_H
 
-#include "common.h"
-#include "executor.h"
-#include "model.h"
+#include "mmdeploy/common.h"
+#include "mmdeploy/executor.h"
+#include "mmdeploy/model.h"
 
 #ifdef __cplusplus
 extern "C" {

csrc/mmdeploy/apis/c/mmdeploy/text_recognizer.cpp

@@ -1,21 +1,21 @@
 // Copyright (c) OpenMMLab. All rights reserved.
 
-#include "text_recognizer.h"
+#include "mmdeploy/text_recognizer.h"
 
 #include <numeric>
 
-#include "common_internal.h"
-#include "executor_internal.h"
 #include "mmdeploy/archive/value_archive.h"
 #include "mmdeploy/codebase/mmocr/mmocr.h"
+#include "mmdeploy/common_internal.h"
 #include "mmdeploy/core/device.h"
 #include "mmdeploy/core/mat.h"
 #include "mmdeploy/core/model.h"
 #include "mmdeploy/core/status_code.h"
 #include "mmdeploy/core/utils/formatter.h"
 #include "mmdeploy/core/value.h"
-#include "model.h"
-#include "pipeline.h"
+#include "mmdeploy/executor_internal.h"
+#include "mmdeploy/model.h"
+#include "mmdeploy/pipeline.h"
 
 using namespace mmdeploy;
 
@@ -38,7 +38,7 @@ Value config_template(const Model& model) {
           {"type", "Inference"},
           {"input", "patches"},
           {"output", "texts"},
-          {"params", {{"model", std::move(model)}}},
+          {"params", {{"model", model}}},
         }
       }
     },

csrc/mmdeploy/apis/c/mmdeploy/text_recognizer.h

@@ -8,9 +8,9 @@
 #ifndef MMDEPLOY_SRC_APIS_C_TEXT_RECOGNIZER_H_
 #define MMDEPLOY_SRC_APIS_C_TEXT_RECOGNIZER_H_
 
-#include "common.h"
-#include "executor.h"
-#include "text_detector.h"
+#include "mmdeploy/common.h"
+#include "mmdeploy/executor.h"
+#include "mmdeploy/text_detector.h"
 
 #ifdef __cplusplus
 extern "C" {

csrc/mmdeploy/apis/c/mmdeploy/video_recognizer.cpp

@@ -1,49 +1,25 @@
 // Copyright (c) OpenMMLab. All rights reserved.
 
-#include "video_recognizer.h"
+#include "mmdeploy/video_recognizer.h"
 
 #include <numeric>
 #include <vector>
 
-#include "common_internal.h"
-#include "executor_internal.h"
 #include "mmdeploy/archive/value_archive.h"
 #include "mmdeploy/codebase/mmaction/mmaction.h"
+#include "mmdeploy/common_internal.h"
 #include "mmdeploy/core/device.h"
 #include "mmdeploy/core/mat.h"
 #include "mmdeploy/core/model.h"
 #include "mmdeploy/core/status_code.h"
 #include "mmdeploy/core/utils/formatter.h"
 #include "mmdeploy/core/value.h"
-#include "model.h"
-#include "pipeline.h"
+#include "mmdeploy/executor_internal.h"
+#include "mmdeploy/model.h"
+#include "mmdeploy/pipeline.h"
 
 using namespace mmdeploy;
 
-namespace {
-Value config_template(const Model& model) {
-  // clang-format off
-  return {
-    {"type", "Pipeline"},
-    {"input", {"video"}},
-    {
-      "tasks", {
-        {
-          {"name", "Video Recognizer"},
-          {"type", "Inference"},
-          {"input", "video"},
-          {"output", "label"},
-          {"params", {{"model", std::move(model)}}},
-        }
-      }
-    },
-    {"output", "label"},
-  };
-  // clang-format on
-}
-
-}  // namespace
-
 int mmdeploy_video_recognizer_create(mmdeploy_model_t model, const char* device_name, int device_id,
                                      mmdeploy_video_recognizer_t* recognizer) {
   mmdeploy_context_t context{};
@@ -101,8 +77,7 @@ void mmdeploy_video_recognizer_destroy(mmdeploy_video_recognizer_t recognizer) {
 
 int mmdeploy_video_recognizer_create_v2(mmdeploy_model_t model, mmdeploy_context_t context,
                                         mmdeploy_video_recognizer_t* recognizer) {
-  auto config = config_template(*Cast(model));
-  return mmdeploy_pipeline_create_v3(Cast(&config), context, (mmdeploy_pipeline_t*)recognizer);
+  return mmdeploy_pipeline_create_from_model(model, context, (mmdeploy_pipeline_t*)recognizer);
 }
 
 int mmdeploy_video_recognizer_create_input(const mmdeploy_mat_t* images,

csrc/mmdeploy/apis/c/mmdeploy/video_recognizer.h

@@ -8,9 +8,9 @@
 #ifndef MMDEPLOY_VIDEO_RECOGNIZER_H
 #define MMDEPLOY_VIDEO_RECOGNIZER_H
 
-#include "common.h"
-#include "executor.h"
-#include "model.h"
+#include "mmdeploy/common.h"
+#include "mmdeploy/executor.h"
+#include "mmdeploy/model.h"
 
 #ifdef __cplusplus
 extern "C" {

csrc/mmdeploy/apis/csharp/MMDeploy.sln

@@ -3,7 +3,7 @@ Microsoft Visual Studio Solution File, Format Version 12.00
 # Visual Studio Version 16
 VisualStudioVersion = 16.0.31729.503
 MinimumVisualStudioVersion = 10.0.40219.1
-Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "MMDeploy", "MMDeploy\MMDeploy.csproj", "{3DC914EB-A8FB-4A89-A7CF-7DF9CC5284A6}"
+Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "MMDeploy", "MMDeploy\MMDeployCSharp.csproj", "{3DC914EB-A8FB-4A89-A7CF-7DF9CC5284A6}"
 EndProject
 
 Global

csrc/mmdeploy/apis/csharp/MMDeploy/APIs/Context.cs

@@ -0,0 +1,69 @@
+namespace MMDeploy
+{
+    /// <summary>
+    /// Context.
+    /// </summary>
+    public class Context : DisposableObject
+    {
+        /// <summary>
+        /// Initializes a new instance of the <see cref="Context"/> class.
+        /// </summary>
+        public Context()
+        {
+            ThrowException(NativeMethods.mmdeploy_context_create(out _handle));
+        }
+
+        /// <summary>
+        /// Initializes a new instance of the <see cref="Context"/> class with device.
+        /// </summary>
+        /// <param name="device">device.</param>
+        public Context(Device device) : this()
+        {
+            Add(device);
+        }
+
+        /// <summary>
+        /// Add model to the context.
+        /// </summary>
+        /// <param name="name">name.</param>
+        /// <param name="model">model.</param>
+        public void Add(string name, Model model)
+        {
+            ThrowException(NativeMethods.mmdeploy_context_add(this, (int)ContextType.MODEL, name, model));
+        }
+
+        /// <summary>
+        /// Add scheduler to the context.
+        /// </summary>
+        /// <param name="name">name.</param>
+        /// <param name="scheduler">scheduler.</param>
+        public void Add(string name, Scheduler scheduler)
+        {
+            ThrowException(NativeMethods.mmdeploy_context_add(this, (int)ContextType.SCHEDULER, name, scheduler));
+        }
+
+        /// <summary>
+        /// Add device to the context.
+        /// </summary>
+        /// <param name="device">device.</param>
+        public void Add(Device device)
+        {
+            ThrowException(NativeMethods.mmdeploy_context_add(this, (int)ContextType.DEVICE, "", device));
+        }
+
+        /// <summary>
+        /// Add profiler to the context.
+        /// </summary>
+        /// <param name="profiler">profiler.</param>
+        public void Add(Profiler profiler)
+        {
+            ThrowException(NativeMethods.mmdeploy_context_add(this, (int)ContextType.PROFILER, "", profiler));
+        }
+
+        /// <inheritdoc/>
+        protected override void ReleaseHandle()
+        {
+            NativeMethods.mmdeploy_model_destroy(_handle);
+        }
+    }
+}

csrc/mmdeploy/apis/csharp/MMDeploy/APIs/Device.cs

@@ -0,0 +1,39 @@
+namespace MMDeploy
+{
+    /// <summary>
+    /// Device.
+    /// </summary>
+    public class Device : DisposableObject
+    {
+        private readonly string _name;
+        private readonly int _index;
+
+        /// <summary>
+        /// Initializes a new instance of the <see cref="Device"/> class.
+        /// </summary>
+        /// <param name="name">device name.</param>
+        /// <param name="index">device index.</param>
+        public Device(string name, int index = 0)
+        {
+            this._name = name;
+            this._index = index;
+            ThrowException(NativeMethods.mmdeploy_device_create(name, index, out _handle));
+        }
+
+        /// <summary>
+        /// Gets device name.
+        /// </summary>
+        public string Name { get => _name; }
+
+        /// <summary>
+        /// Gets device index.
+        /// </summary>
+        public int Index { get => _index; }
+
+        /// <inheritdoc/>
+        protected override void ReleaseHandle()
+        {
+            NativeMethods.mmdeploy_device_destroy(_handle);
+        }
+    }
+}

csrc/mmdeploy/apis/csharp/MMDeploy/APIs/DisposableObject.cs

@@ -92,5 +92,11 @@ namespace MMDeploy
                 throw new Exception(result.ToString());
             }
         }
+
+        /// <summary>
+        /// Gets internal handle.
+        /// </summary>
+        /// <param name="obj">instance.</param>
+        public static implicit operator IntPtr(DisposableObject obj) => obj._handle;
     }
 }

csrc/mmdeploy/apis/csharp/MMDeploy/APIs/Model.cs

@@ -0,0 +1,23 @@
+namespace MMDeploy
+{
+    /// <summary>
+    /// model.
+    /// </summary>
+    public class Model : DisposableObject
+    {
+        /// <summary>
+        /// Initializes a new instance of the <see cref="Model"/> class.
+        /// </summary>
+        /// <param name="modelPath">model path.</param>
+        public Model(string modelPath)
+        {
+            ThrowException(NativeMethods.mmdeploy_model_create_by_path(modelPath, out _handle));
+        }
+
+        /// <inheritdoc/>
+        protected override void ReleaseHandle()
+        {
+            NativeMethods.mmdeploy_model_destroy(_handle);
+        }
+    }
+}

csrc/mmdeploy/apis/csharp/MMDeploy/APIs/PoseTracker.cs

@@ -0,0 +1,350 @@
+using System;
+using System.Collections.Generic;
+using System.Runtime.InteropServices;
+
+namespace MMDeploy
+{
+#pragma warning disable 0649
+    internal unsafe struct CPoseTrack
+    {
+        public Pointf* Keypoints;
+        public int KeypointCount;
+        public float* Scores;
+        public Rect Bbox;
+        public int TargetId;
+    }
+#pragma warning restore 0649
+
+    /// <summary>
+    /// Single tracking result of a bbox.
+    /// A picture may contains multiple reuslts.
+    /// </summary>
+    public struct PoseTrack
+    {
+        /// <summary>
+        /// Keypoints.
+        /// </summary>
+        public List<Pointf> Keypoints;
+
+        /// <summary>
+        /// Scores.
+        /// </summary>
+        public List<float> Scores;
+
+        /// <summary>
+        /// Bbox.
+        /// </summary>
+        public Rect Bbox;
+
+        /// <summary>
+        /// TargetId.
+        /// </summary>
+        public int TargetId;
+
+        /// <summary>
+        /// Init data.
+        /// </summary>
+        private void Init()
+        {
+            if (Keypoints == null || Scores == null)
+            {
+                Keypoints = new List<Pointf>();
+                Scores = new List<float>();
+            }
+        }
+
+        internal unsafe void Add(CPoseTrack* result)
+        {
+            Init();
+            for (int i = 0; i < result->KeypointCount; i++)
+            {
+                Keypoints.Add(new Pointf(result->Keypoints[i].X, result->Keypoints[i].Y));
+                Scores.Add(result->Scores[i]);
+            }
+
+            Bbox = result->Bbox;
+            TargetId = result->TargetId;
+        }
+    }
+
+    /// <summary>
+    /// Output of PoseTracker.
+    /// </summary>
+    public struct PoseTrackerOutput
+    {
+        /// <summary>
+        /// Tracking results for single image.
+        /// </summary>
+        public List<PoseTrack> Results;
+
+        /// <summary>
+        /// Gets number of output.
+        /// </summary>
+        public int Count
+        {
+            get { return (Results == null) ? 0 : Results.Count; }
+        }
+
+        /// <summary>
+        /// Result for box level.
+        /// </summary>
+        /// <param name="boxRes">Box res.</param>
+        public void Add(PoseTrack boxRes)
+        {
+            if (Results == null)
+            {
+                Results = new List<PoseTrack>();
+            }
+
+            Results.Add(boxRes);
+        }
+    }
+
+    /// <summary>
+    /// PoseTracker.
+    /// </summary>
+    public class PoseTracker : DisposableObject
+    {
+        /// <summary>
+        /// Params.
+        /// </summary>
+        public struct Params
+        {
+            /// <summary>
+            /// init with default value.
+            /// </summary>
+            public void Init()
+            {
+                IntPtr ptr = Marshal.AllocHGlobal(Marshal.SizeOf(typeof(Params)));
+                NativeMethods.mmdeploy_pose_tracker_default_params(ptr);
+                this = Marshal.PtrToStructure<Params>(ptr);
+                Marshal.DestroyStructure<Params>(ptr);
+                Marshal.FreeHGlobal(ptr);
+            }
+
+            /// <summary>
+            /// Sets keypoint sigmas.
+            /// </summary>
+            /// <param name="array">keypoint sigmas.</param>
+            public void SetKeypointSigmas(float[] array)
+            {
+                this.KeypointSigmasSize = array.Length;
+                this.KeypointSigmas = Marshal.AllocHGlobal(sizeof(float) * array.Length);
+                Marshal.Copy(array, 0, this.KeypointSigmas, array.Length);
+            }
+
+            /// <summary>
+            /// Release ptr.
+            /// </summary>
+            public void DeleteKeypointSigmas()
+            {
+                if (this.KeypointSigmas != null)
+                {
+                    Marshal.FreeHGlobal(this.KeypointSigmas);
+                    this.KeypointSigmasSize = 0;
+                }
+            }
+
+            /// <summary>
+            /// detection interval, default = 1.
+            /// </summary>
+            public int DetInterval;
+
+            /// <summary>
+            /// detection label use for pose estimation, default = 0.
+            /// </summary>
+            public int DetLabel;
+
+            /// <summary>
+            /// detection score threshold, default = 0.5.
+            /// </summary>
+            public float DetThr;
+
+            /// <summary>
+            /// detection minimum bbox size (compute as sqrt(area)), default = -1.
+            /// </summary>
+            public float DetMinBboxSize;
+
+            /// <summary>
+            /// nms iou threshold for merging detected bboxes and bboxes from tracked targets, default = 0.7.
+            /// </summary>
+            public float DetNmsThr;
+
+            /// <summary>
+            /// max number of bboxes used for pose estimation per frame, default = -1.
+            /// </summary>
+            public int PoseMaxNumBboxes;
+
+            /// <summary>
+            /// threshold for visible key-points, default = 0.5.
+            /// </summary>
+            public float PoseKptThr;
+
+            /// <summary>
+            /// min number of key-points for valid poses, default = -1.
+            /// </summary>
+            public int PoseMinKeypoints;
+
+            /// <summary>
+            /// scale for expanding key-points to bbox, default = 1.25.
+            /// </summary>
+            public float PoseBboxScale;
+
+            /// <summary>
+            /// min pose bbox size, tracks with bbox size smaller than the threshold will be dropped,default = -1.
+            /// </summary>
+            public float PoseMinBboxSize;
+
+            /// <summary>
+            /// nms oks/iou threshold for suppressing overlapped poses, useful when multiple pose estimations
+            /// collapse to the same target, default = 0.5.
+            /// </summary>
+            public float PoseNmsThr;
+
+            /// <summary>
+            /// keypoint sigmas for computing OKS, will use IOU if not set, default = nullptr.
+            /// </summary>
+            public IntPtr KeypointSigmas;
+
+            /// <summary>
+            /// size of keypoint sigma array, must be consistent with the number of key-points, default = 0.
+            /// </summary>
+            public int KeypointSigmasSize;
+
+            /// <summary>
+            /// iou threshold for associating missing tracks, default = 0.4.
+            /// </summary>
+            public float TrackIouThr;
+
+            /// <summary>
+            /// max number of missing frames before a missing tracks is removed, default = 10.
+            /// </summary>
+            public int TrackMaxMissing;
+
+            /// <summary>
+            /// track history size, default = 1.
+            /// </summary>
+            public int TrackHistorySize;
+
+            /// <summary>
+            /// weight of position for setting covariance matrices of kalman filters, default = 0.05.
+            /// </summary>
+            public float StdWeightPosition;
+
+            /// <summary>
+            /// weight of velocity for setting covariance matrices of kalman filters, default = 0.00625.
+            /// </summary>
+            public float StdWeightVelocity;
+
+            /// <summary>
+            /// params for the one-euro filter for smoothing the outputs - (beta, fc_min, fc_derivative)
+            /// default = (0.007, 1, 1).
+            /// </summary>
+            [MarshalAs(UnmanagedType.ByValArray, SizeConst = 3)]
+            public float[] SmoothParams;
+        }
+
+        /// <summary>
+        /// tracking state.
+        /// </summary>
+        public class State : DisposableObject
+        {
+            /// <summary>
+            /// Initializes a new instance of the <see cref="State"/> class.
+            /// </summary>
+            /// <param name="pipeline">pipeline.</param>
+            /// <param name="param">param.</param>
+            public State(IntPtr pipeline, Params param)
+            {
+                ThrowException(NativeMethods.mmdeploy_pose_tracker_create_state(pipeline, param, out _handle));
+            }
+
+            /// <inheritdoc/>
+            protected override void ReleaseHandle()
+            {
+                NativeMethods.mmdeploy_pose_tracker_destroy_state(_handle);
+            }
+        }
+
+        /// <summary>
+        /// Initializes a new instance of the <see cref="PoseTracker"/> class.
+        /// </summary>
+        /// <param name="detect">detect model.</param>
+        /// <param name="pose">pose model.</param>
+        /// <param name="context">context.</param>
+        public PoseTracker(Model detect, Model pose, Context context)
+        {
+            ThrowException(NativeMethods.mmdeploy_pose_tracker_create(detect, pose, context, out _handle));
+        }
+
+        /// <summary>
+        /// Get track information of image.
+        /// </summary>
+        /// <param name="state">state for video.</param>
+        /// <param name="mat">input mat.</param>
+        /// <param name="detect">control the use of detector.
+        /// -1: use params.DetInterval, 0: don't use detector, 1: force use detector.</param>
+        /// <returns>results of this frame.</returns>
+        public PoseTrackerOutput Apply(State state, Mat mat, int detect = -1)
+        {
+            PoseTrackerOutput output = default;
+
+            IntPtr[] states = new IntPtr[1] { state };
+            Mat[] mats = new Mat[1] { mat };
+            int[] detects = new int[1] { -1 };
+
+            unsafe
+            {
+                CPoseTrack* results = null;
+                int* resultCount = null;
+                fixed (Mat* _mats = mats)
+                fixed (IntPtr* _states = states)
+                fixed (int* _detects = detects)
+                {
+                    ThrowException(NativeMethods.mmdeploy_pose_tracker_apply(_handle, _states, _mats, _detects,
+                        mats.Length, &results, &resultCount));
+
+                    FormatResult(resultCount, results, ref output, out var total);
+                    ReleaseResult(results, resultCount, mats.Length);
+                }
+            }
+
+            return output;
+        }
+
+        private unsafe void FormatResult(int* resultCount, CPoseTrack* results, ref PoseTrackerOutput output, out int total)
+        {
+            total = resultCount[0];
+            for (int i = 0; i < total; i++)
+            {
+                PoseTrack outi = default;
+                outi.Add(results);
+                output.Add(outi);
+                results++;
+            }
+        }
+
+        private unsafe void ReleaseResult(CPoseTrack* results, int* resultCount, int count)
+        {
+            NativeMethods.mmdeploy_pose_tracker_release_result(results, resultCount, count);
+        }
+
+        /// <summary>
+        /// Create internal state.
+        /// </summary>
+        /// <param name="param">instance of Params.</param>
+        /// <returns>instance of State.</returns>
+        public State CreateState(Params param)
+        {
+            State state = new State(_handle, param);
+            return state;
+        }
+
+        /// <inheritdoc/>
+        protected override void ReleaseHandle()
+        {
+            // _state.Dispose();
+            NativeMethods.mmdeploy_pose_tracker_destroy(_handle);
+        }
+    }
+}

csrc/mmdeploy/apis/csharp/MMDeploy/APIs/Profiler.cs

@@ -0,0 +1,23 @@
+namespace MMDeploy
+{
+    /// <summary>
+    /// Profiler.
+    /// </summary>
+    public class Profiler : DisposableObject
+    {
+        /// <summary>
+        /// Initializes a new instance of the <see cref="Profiler"/> class.
+        /// </summary>
+        /// <param name="path">path.</param>
+        public Profiler(string path)
+        {
+            ThrowException(NativeMethods.mmdeploy_profiler_create(path, out _handle));
+        }
+
+        /// <inheritdoc/>
+        protected override void ReleaseHandle()
+        {
+            NativeMethods.mmdeploy_profiler_destroy(_handle);
+        }
+    }
+}

csrc/mmdeploy/apis/csharp/MMDeploy/APIs/RotatedDetector.cs

@@ -0,0 +1,157 @@
+using System;
+using System.Collections.Generic;
+
+namespace MMDeploy
+{
+    /// <summary>
+    /// Single detection result of a picture.
+    /// A picture may contains multiple reuslts.
+    /// </summary>
+    public struct RDetect
+    {
+        /// <summary>
+        /// Label id.
+        /// </summary>
+        public int LabelId;
+
+        /// <summary>
+        /// Score.
+        /// </summary>
+        public float Score;
+
+        /// <summary>
+        /// Center x.
+        /// </summary>
+        public float Cx;
+
+        /// <summary>
+        /// Center y.
+        /// </summary>
+        public float Cy;
+
+        /// <summary>
+        /// Width.
+        /// </summary>
+        public float Width;
+
+        /// <summary>
+        /// Height.
+        /// </summary>
+        public float Height;
+
+        /// <summary>
+        /// Angle.
+        /// </summary>
+        public float Angle;
+
+        internal unsafe RDetect(RDetect* result) : this()
+        {
+            this = *result;
+        }
+    }
+
+    /// <summary>
+    /// Output of RotatedDetector.
+    /// </summary>
+    public struct RotatedDetectorOutput
+    {
+        /// <summary>
+        /// Rotated detection results for single image.
+        /// </summary>
+        public List<RDetect> Results;
+
+        private void Init()
+        {
+            if (Results == null)
+            {
+                Results = new List<RDetect>();
+            }
+        }
+
+        internal unsafe void Add(RDetect* result)
+        {
+            Init();
+            Results.Add(new RDetect(result));
+        }
+
+        /// <summary>
+        /// Gets number of output.
+        /// </summary>
+        public int Count
+        {
+            get { return (Results == null) ? 0 : Results.Count; }
+        }
+    }
+
+    /// <summary>
+    /// RotatedDetector.
+    /// </summary>
+    public class RotatedDetector : DisposableObject
+    {
+        /// <summary>
+        /// Initializes a new instance of the <see cref="RotatedDetector"/> class.
+        /// </summary>
+        /// <param name="modelPath">model path.</param>
+        /// <param name="deviceName">device name.</param>
+        /// <param name="deviceId">device id.</param>
+        public RotatedDetector(string modelPath, string deviceName, int deviceId)
+        {
+            ThrowException(NativeMethods.mmdeploy_rotated_detector_create_by_path(modelPath,
+                deviceName, deviceId, out _handle));
+        }
+
+        /// <summary>
+        /// Get information of each image in a batch.
+        /// </summary>
+        /// <param name="mats">input mats.</param>
+        /// <returns>Results of each input mat.</returns>
+        public List<RotatedDetectorOutput> Apply(Mat[] mats)
+        {
+            List<RotatedDetectorOutput> output = new List<RotatedDetectorOutput>();
+
+            unsafe
+            {
+                RDetect* results = null;
+                int* resultCount = null;
+                fixed (Mat* _mats = mats)
+                {
+                    ThrowException(NativeMethods.mmdeploy_rotated_detector_apply(_handle,
+                        _mats, mats.Length, &results, &resultCount));
+                }
+
+                FormatResult(mats.Length, resultCount, results, ref output, out var total);
+                ReleaseResult(results, resultCount);
+            }
+
+            return output;
+        }
+
+        private unsafe void FormatResult(int matCount, int* resultCount, RDetect* results,
+            ref List<RotatedDetectorOutput> output, out int total)
+        {
+            total = matCount;
+            for (int i = 0; i < matCount; i++)
+            {
+                RotatedDetectorOutput outi = default;
+                for (int j = 0; j < resultCount[i]; j++)
+                {
+                    outi.Add(results);
+                    results++;
+                }
+
+                output.Add(outi);
+            }
+        }
+
+        private unsafe void ReleaseResult(RDetect* results, int* resultCount)
+        {
+            NativeMethods.mmdeploy_rotated_detector_release_result(results, resultCount);
+        }
+
+        /// <inheritdoc/>
+        protected override void ReleaseHandle()
+        {
+            NativeMethods.mmdeploy_rotated_detector_destroy(_handle);
+        }
+    }
+}

csrc/mmdeploy/apis/csharp/MMDeploy/APIs/Scheduler.cs

@@ -0,0 +1,51 @@
+using System;
+
+namespace MMDeploy
+{
+    /// <summary>
+    /// Scheduler.
+    /// </summary>
+    public class Scheduler : DisposableObject
+    {
+        private Scheduler()
+        {
+        }
+
+        /// <summary>
+        /// Create thread pool scheduler.
+        /// </summary>
+        /// <param name="num_threads">thread number.</param>
+        /// <returns>scheduler.</returns>
+        public static Scheduler ThreadPool(int num_threads)
+        {
+            Scheduler result = new Scheduler();
+            unsafe
+            {
+                result._handle = (IntPtr)NativeMethods.mmdeploy_executor_create_thread_pool(num_threads);
+            }
+
+            return result;
+        }
+
+        /// <summary>
+        /// Create single thread scheduler.
+        /// </summary>
+        /// <returns>scheduler.</returns>
+        public static Scheduler Thread()
+        {
+            Scheduler result = new Scheduler();
+            unsafe
+            {
+                result._handle = (IntPtr)NativeMethods.mmdeploy_executor_create_thread();
+            }
+
+            return result;
+        }
+
+        /// <inheritdoc/>
+        protected override void ReleaseHandle()
+        {
+            NativeMethods.mmdeploy_scheduler_destroy(_handle);
+        }
+    }
+}

csrc/mmdeploy/apis/csharp/MMDeploy/APIs/Segmentor.cs

@@ -10,6 +10,7 @@ namespace MMDeploy
         public int Width;
         public int Classes;
         public int* Mask;
+        public float* Score;
     }
 #pragma warning restore 0649
 
@@ -34,10 +35,16 @@ namespace MMDeploy
         public int Classes;
 
         /// <summary>
-        /// Mask data.
+        /// Mask data, mask[i * width + j] indicates the label id of pixel at (i, j).
         /// </summary>
         public int[] Mask;
 
+        /// <summary>
+        /// Score data, score[height * width * k + i * width + j] indicates the score
+        /// of class k at pixel (i, j).
+        /// </summary>
+        public float[] Score;
+
         /// <summary>
         /// Initializes a new instance of the <see cref="SegmentorOutput"/> struct.
         /// </summary>
@@ -45,13 +52,31 @@ namespace MMDeploy
         /// <param name="width">width.</param>
         /// <param name="classes">classes.</param>
         /// <param name="mask">mask.</param>
-        public SegmentorOutput(int height, int width, int classes, int[] mask)
+        /// <param name="score">score.</param>
+        public SegmentorOutput(int height, int width, int classes, int[] mask, float[] score)
         {
             Height = height;
             Width = width;
             Classes = classes;
-            Mask = new int[Height * Width];
-            Array.Copy(mask, this.Mask, mask.Length);
+            if (mask.Length > 0)
+            {
+                Mask = new int[Height * Width];
+                Array.Copy(mask, this.Mask, mask.Length);
+            }
+            else
+            {
+                Mask = new int[] { };
+            }
+
+            if (score.Length > 0)
+            {
+                Score = new float[Height * Width * Classes];
+                Array.Copy(score, this.Score, score.Length);
+            }
+            else
+            {
+                Score = new float[] { };
+            }
         }
 
         internal unsafe SegmentorOutput(CSegment* result)
@@ -59,11 +84,34 @@ namespace MMDeploy
             Height = result->Height;
             Width = result->Width;
             Classes = result->Classes;
-            Mask = new int[Height * Width];
-            int nbytes = Height * Width * sizeof(int);
-            fixed (int* data = this.Mask)
+            if (result->Mask != null)
             {
-                Buffer.MemoryCopy(result->Mask, data, nbytes, nbytes);
+                Mask = new int[Height * Width];
+
+                int nbytes = Height * Width * sizeof(int);
+                fixed (int* data = this.Mask)
+                {
+                    Buffer.MemoryCopy(result->Mask, data, nbytes, nbytes);
+                }
+            }
+            else
+            {
+                Mask = new int[] { };
+            }
+
+            if (result->Score != null)
+            {
+                Score = new float[Height * Width * Classes];
+
+                int nbytes = Height * Width * Classes * sizeof(float);
+                fixed (float* data = this.Score)
+                {
+                    Buffer.MemoryCopy(result->Score, data, nbytes, nbytes);
+                }
+            }
+            else
+            {
+                Score = new float[] { };
             }
         }
     }

csrc/mmdeploy/apis/csharp/MMDeploy/APIs/TextDetector.cs

@@ -99,7 +99,7 @@ namespace MMDeploy
     }
 
     /// <summary>
-    /// Output of DetectorOutput.
+    /// Output of TextDetector.
     /// </summary>
     public struct TextDetectorOutput
     {

csrc/mmdeploy/apis/csharp/MMDeploy/APIs/common.cs

@@ -89,4 +89,17 @@ namespace MMDeploy
             Y = y;
         }
     }
+
+    /// <summary>
+    /// Context type.
+    /// </summary>
+    public enum ContextType
+    {
+        DEVICE = 0,
+        STREAM = 1,
+        MODEL = 2,
+        SCHEDULER = 3,
+        MAT = 4,
+        PROFILER = 5,
+    }
 }

csrc/mmdeploy/apis/csharp/MMDeploy/NativeAPIs/NativeMethods_c_api.cs

@@ -9,6 +9,37 @@ namespace MMDeploy
     /// </summary>
     internal static partial class NativeMethods
     {
+        #region common.h
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern int mmdeploy_context_create(out IntPtr handle);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern int mmdeploy_context_create_by_device(string deviceName, int deviceId,
+            out IntPtr handle);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern void mmdeploy_context_destroy(IntPtr handle);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern int mmdeploy_context_add(IntPtr handle, int type, string name,
+            IntPtr obj);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern int mmdeploy_device_create(string device_name, int device_id,
+            out IntPtr device);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern void mmdeploy_device_destroy(IntPtr device);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern int mmdeploy_profiler_create(string path, out IntPtr handle);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern unsafe void mmdeploy_profiler_destroy(IntPtr handle);
+        #endregion
+
+        #region scheduler.h
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern unsafe void* mmdeploy_executor_create_thread();
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern unsafe void* mmdeploy_executor_create_thread_pool(int num_threads);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern void mmdeploy_scheduler_destroy(IntPtr handle);
+        #endregion
+
         #region model.h
         [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
         public static extern int mmdeploy_model_create_by_path(string path, out IntPtr handle);
@@ -38,6 +69,27 @@ namespace MMDeploy
         public static extern void mmdeploy_pose_detector_destroy(IntPtr handle);
         #endregion
 
+        #region pose_tracker.h
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern int mmdeploy_pose_tracker_create(IntPtr det_model, IntPtr pose_model,
+            IntPtr context, out IntPtr handle);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern int mmdeploy_pose_tracker_destroy(IntPtr handle);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern int mmdeploy_pose_tracker_default_params(IntPtr handle);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern int mmdeploy_pose_tracker_create_state(IntPtr pipeline,
+            PoseTracker.Params param, out IntPtr state);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern void mmdeploy_pose_tracker_destroy_state(IntPtr state);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern unsafe int mmdeploy_pose_tracker_apply(IntPtr handle, IntPtr* state,
+            Mat* mats, int* useDet, int count, CPoseTrack** results, int** resultCount);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern unsafe void mmdeploy_pose_tracker_release_result(CPoseTrack* results,
+            int* resultCount, int count);
+        #endregion
+
         #region classifier.h
         [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
         public static extern int mmdeploy_classifier_create(IntPtr model, string deviceName,
@@ -55,6 +107,23 @@ namespace MMDeploy
         public static extern void mmdeploy_classifier_destroy(IntPtr handle);
         #endregion
 
+        #region rotated_detector.h
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern int mmdeploy_rotated_detector_create(IntPtr model,
+            string deviceName, int deviceId, out IntPtr handle);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern int mmdeploy_rotated_detector_create_by_path(string modelPath,
+            string deviceName, int deviceId, out IntPtr handle);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern unsafe int mmdeploy_rotated_detector_apply(IntPtr handle, Mat* mats,
+            int matCount, RDetect** results, int** resultCount);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern unsafe void mmdeploy_rotated_detector_release_result(RDetect* results,
+            int* resultCount);
+        [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
+        public static extern void mmdeploy_rotated_detector_destroy(IntPtr handle);
+        #endregion
+
         #region detector.h
         [Pure, DllImport(DllExtern, CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
         public static extern int mmdeploy_detector_create(IntPtr model, string deviceName,

csrc/mmdeploy/apis/cxx/CMakeLists.txt

@@ -3,27 +3,42 @@
 cmake_minimum_required(VERSION 3.14)
 project(mmdeploy_cxx_api)
 
-if (MMDEPLOY_BUILD_SDK_CXX_API)
-    add_library(${PROJECT_NAME} INTERFACE)
-    target_include_directories(${PROJECT_NAME} INTERFACE
-            $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}>
-            $<INSTALL_INTERFACE:include>)
-    target_compile_features(${PROJECT_NAME} INTERFACE cxx_std_17)
-    target_link_libraries(${PROJECT_NAME} INTERFACE mmdeploy::core)
-    set(_tasks ${MMDEPLOY_TASKS} pipeline)
-    foreach (task ${_tasks})
-        target_link_libraries(mmdeploy_${task} INTERFACE ${PROJECT_NAME})
-        install(FILES ${CMAKE_CURRENT_SOURCE_DIR}/mmdeploy/${task}.hpp
-                DESTINATION include/mmdeploy)
-    endforeach ()
-    if (TARGET mmdeploy)
-        target_link_libraries(mmdeploy INTERFACE ${PROJECT_NAME})
-    endif ()
-    mmdeploy_export(${PROJECT_NAME})
-    install(FILES ${CMAKE_CURRENT_SOURCE_DIR}/mmdeploy/common.hpp
+add_library(${PROJECT_NAME} INTERFACE)
+target_include_directories(${PROJECT_NAME} INTERFACE
+        $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}>
+        $<INSTALL_INTERFACE:include>)
+target_compile_features(${PROJECT_NAME} INTERFACE cxx_std_17)
+set(_tasks ${MMDEPLOY_TASKS} pipeline)
+foreach (task ${_tasks})
+    target_link_libraries(mmdeploy_${task} INTERFACE ${PROJECT_NAME})
+    install(FILES ${CMAKE_CURRENT_SOURCE_DIR}/mmdeploy/${task}.hpp
             DESTINATION include/mmdeploy)
-    install(DIRECTORY ${CMAKE_SOURCE_DIR}/demo/csrc/ DESTINATION example/cpp
-            FILES_MATCHING
-            PATTERN "*.cxx"
+endforeach ()
+if (TARGET mmdeploy)
+    target_include_directories(${PROJECT_NAME} INTERFACE
+            $<BUILD_INTERFACE:${CMAKE_SOURCE_DIR}/csrc>
+            $<BUILD_INTERFACE:${CMAKE_SOURCE_DIR}/third_party/outcome>
+            $<BUILD_INTERFACE:${CMAKE_SOURCE_DIR}/third_party/json>
             )
+    target_include_directories(${PROJECT_NAME} INTERFACE
+            $<INSTALL_INTERFACE:include>
+            $<INSTALL_INTERFACE:include/mmdeploy/third_party/outcome>
+            $<INSTALL_INTERFACE:include/mmdeploy/third_party/json>
+            )
+    if (NOT MMDEPLOY_SPDLOG_EXTERNAL)
+        target_include_directories(${PROJECT_NAME} INTERFACE
+                $<BUILD_INTERFACE:${CMAKE_SOURCE_DIR}/third_party/spdlog/include>
+                $<INSTALL_INTERFACE:include/mmdeploy/third_party>)
+    endif ()
+    target_link_libraries(mmdeploy INTERFACE ${PROJECT_NAME})
+else ()
+    target_link_libraries(${PROJECT_NAME} INTERFACE mmdeploy::core)
 endif ()
+mmdeploy_export_impl(${PROJECT_NAME})
+install(FILES ${CMAKE_CURRENT_SOURCE_DIR}/mmdeploy/common.hpp
+        DESTINATION include/mmdeploy)
+install(DIRECTORY ${CMAKE_SOURCE_DIR}/demo/csrc/ DESTINATION example/cpp
+        FILES_MATCHING
+        PATTERN "*.cxx"
+        PATTERN "*.h"
+        )

csrc/mmdeploy/apis/cxx/mmdeploy/common.hpp

@@ -6,6 +6,7 @@
 #include <memory>
 #include <type_traits>
 #include <utility>
+#include <vector>
 
 #include "mmdeploy/common.h"
 #include "mmdeploy/core/mpl/span.h"
@@ -28,6 +29,30 @@ namespace cxx {
 
 using Rect = mmdeploy_rect_t;
 
+template <typename T>
+class UniqueHandle : public NonCopyable {
+ public:
+  UniqueHandle() = default;
+  explicit UniqueHandle(T handle) : handle_(handle) {}
+
+  // derived class must destroy the object and reset `handle_`
+  ~UniqueHandle() { assert(handle_ == nullptr); }
+
+  UniqueHandle(UniqueHandle&& o) noexcept : handle_(std::exchange(o.handle_, nullptr)) {}
+  UniqueHandle& operator=(UniqueHandle&& o) noexcept {
+    if (this != &o) {
+      handle_ = std::exchange(o.handle_, nullptr);
+    }
+    return *this;
+  }
+
+  explicit operator T() const noexcept { return handle_; }
+  T operator->() const noexcept { return handle_; }
+
+ protected:
+  T handle_{};
+};
+
 class Model {
  public:
   explicit Model(const char* path) {
@@ -39,6 +64,8 @@ class Model {
     model_.reset(model, [](auto p) { mmdeploy_model_destroy(p); });
   }
 
+  explicit Model(const std::string& path) : Model(path.c_str()) {}
+
   Model(const void* buffer, size_t size) {
     mmdeploy_model_t model{};
     auto ec = mmdeploy_model_create(buffer, static_cast<int>(size), &model);
@@ -102,6 +129,8 @@ class Mat {
       mmdeploy_data_type_t type, uint8_t* data, mmdeploy_device_t device = nullptr)
       : desc_{data, height, width, channels, format, type, device} {}
 
+  Mat(const mmdeploy_mat_t& desc) : desc_(desc) {}  // NOLINT
+
   const mmdeploy_mat_t& desc() const noexcept { return desc_; }
 
 #if MMDEPLOY_CXX_USE_OPENCV
@@ -146,6 +175,16 @@ class Mat {
 template <typename T>
 class Result_ {
  public:
+  using value_type = T;
+  using size_type = size_t;
+  using difference_type = ptrdiff_t;
+  using reference = T&;
+  using const_reference = const T&;
+  using pointer = T*;
+  using const_pointer = const T*;
+  using iterator = T*;
+  using const_iterator = T*;
+
   Result_(size_t offset, size_t size, std::shared_ptr<T> data)
       : offset_(offset), size_(size), data_(std::move(data)) {}
 

csrc/mmdeploy/apis/cxx/mmdeploy/pose_tracker.hpp

@@ -0,0 +1,151 @@
+// Copyright (c) OpenMMLab. All rights reserved.
+
+#ifndef MMDEPLOY_POSE_TRACKER_HPP
+#define MMDEPLOY_POSE_TRACKER_HPP
+
+#include "mmdeploy/common.hpp"
+#include "mmdeploy/pose_tracker.h"
+
+namespace mmdeploy {
+
+namespace cxx {
+
+class PoseTracker : public UniqueHandle<mmdeploy_pose_tracker_t> {
+ public:
+  using Result = Result_<mmdeploy_pose_tracker_target_t>;
+  class State;
+  class Params;
+
+ public:
+  /**
+   * @brief Create pose tracker pipeline
+   * @param detect object detection model
+   * @param pose pose estimation model
+   * @param context execution context
+   */
+  PoseTracker(const Model& detect, const Model& pose, const Context& context) {
+    auto ec = mmdeploy_pose_tracker_create(detect, pose, context, &handle_);
+    if (ec != MMDEPLOY_SUCCESS) {
+      throw_exception(static_cast<ErrorCode>(ec));
+    }
+  }
+  ~PoseTracker() {
+    if (handle_) {
+      mmdeploy_pose_tracker_destroy(handle_);
+      handle_ = {};
+    }
+  }
+  PoseTracker(PoseTracker&&) noexcept = default;
+
+  /**
+   * @brief Create a tracker state corresponds to a video stream
+   * @param params params for creating the tracker state
+   * @return created tracker state
+   */
+  State CreateState(const Params& params);
+
+  /**
+   * @brief Apply pose tracker pipeline
+   * @param state tracker state
+   * @param frame input video frame
+   * @param detect control the use of detector
+   *   -1: use params.det_interval, 0: don't use detector, 1: force use detector
+   * @return
+   */
+  Result Apply(State& state, const Mat& frame, int detect = -1);
+
+  /**
+   * @brief batched version of Apply
+   * @param states
+   * @param frames
+   * @param detects
+   * @return
+   */
+  std::vector<Result> Apply(const Span<State>& states, const Span<const Mat>& frames,
+                            const Span<const int>& detects = {});
+
+ public:
+  /**
+   * see \ref mmdeploy/pose_tracker.h for detail
+   */
+  class Params : public UniqueHandle<mmdeploy_pose_tracker_param_t*> {
+   public:
+    explicit Params() {
+      handle_ = new mmdeploy_pose_tracker_param_t{};
+      mmdeploy_pose_tracker_default_params(handle_);
+    }
+    ~Params() {
+      if (handle_) {
+        delete handle_;
+        handle_ = {};
+      }
+    }
+  };
+
+  class State : public UniqueHandle<mmdeploy_pose_tracker_state_t> {
+   public:
+    explicit State(mmdeploy_pose_tracker_t pipeline, const mmdeploy_pose_tracker_param_t* params) {
+      auto ec = mmdeploy_pose_tracker_create_state(pipeline, params, &handle_);
+      if (ec != MMDEPLOY_SUCCESS) {
+        throw_exception(static_cast<ErrorCode>(ec));
+      }
+    }
+    ~State() {
+      if (handle_) {
+        mmdeploy_pose_tracker_destroy_state(handle_);
+        handle_ = {};
+      }
+    }
+    State(State&&) noexcept = default;
+  };
+};
+
+inline PoseTracker::State PoseTracker::CreateState(const PoseTracker::Params& params) {
+  return State(handle_, static_cast<mmdeploy_pose_tracker_param_t*>(params));
+}
+
+inline std::vector<PoseTracker::Result> PoseTracker::Apply(const Span<State>& states,
+                                                           const Span<const Mat>& frames,
+                                                           const Span<const int32_t>& detects) {
+  if (frames.empty()) {
+    return {};
+  }
+  mmdeploy_pose_tracker_target_t* results{};
+  int32_t* result_count{};
+
+  auto ec = mmdeploy_pose_tracker_apply(
+      handle_, reinterpret_cast<mmdeploy_pose_tracker_state_t*>(states.data()),
+      reinterpret(frames.data()), detects.data(), static_cast<int32_t>(frames.size()), &results,
+      &result_count);
+  if (ec != MMDEPLOY_SUCCESS) {
+    throw_exception(static_cast<ErrorCode>(ec));
+  }
+
+  std::shared_ptr<mmdeploy_pose_tracker_target_t> data(
+      results, [result_count, count = frames.size()](auto p) {
+        mmdeploy_pose_tracker_release_result(p, result_count, count);
+      });
+
+  std::vector<Result> rets;
+  rets.reserve(frames.size());
+
+  size_t offset = 0;
+  for (size_t i = 0; i < frames.size(); ++i) {
+    offset += rets.emplace_back(offset, result_count[i], data).size();
+  }
+
+  return rets;
+}
+
+inline PoseTracker::Result PoseTracker::Apply(PoseTracker::State& state, const Mat& frame,
+                                              int32_t detect) {
+  return Apply(Span(&state, 1), Span{frame}, Span{detect})[0];
+}
+
+}  // namespace cxx
+
+using cxx::PoseTracker;
+
+}  // namespace mmdeploy
+
+#endif  // MMDEPLOY_POSE_TRACKER_HPP

csrc/mmdeploy/apis/cxx/mmdeploy/text_recognizer.hpp

@@ -3,6 +3,8 @@
 #ifndef MMDEPLOY_CSRC_MMDEPLOY_APIS_CXX_TEXT_RECOGNIZER_HPP_
 #define MMDEPLOY_CSRC_MMDEPLOY_APIS_CXX_TEXT_RECOGNIZER_HPP_
 
+#include <numeric>
+
 #include "mmdeploy/common.hpp"
 #include "mmdeploy/text_detector.hpp"
 #include "mmdeploy/text_recognizer.h"
@@ -40,9 +42,12 @@ class TextRecognizer : public NonMovable {
     const TextDetection* p_bboxes{};
     const int* p_bbox_count{};
 
+    auto n_total_bboxes = static_cast<int>(images.size());
+
     if (!bboxes.empty()) {
       p_bboxes = bboxes.data();
       p_bbox_count = bbox_count.data();
+      n_total_bboxes = std::accumulate(bbox_count.begin(), bbox_count.end(), 0);
     }
 
     TextRecognition* results{};
@@ -53,7 +58,7 @@ class TextRecognizer : public NonMovable {
       throw_exception(static_cast<ErrorCode>(ec));
     }
 
-    std::shared_ptr<TextRecognition> data(results, [count = images.size()](auto p) {
+    std::shared_ptr<TextRecognition> data(results, [count = n_total_bboxes](auto p) {
       mmdeploy_text_recognizer_release_result(p, count);
     });
 

csrc/mmdeploy/apis/java/CMakeLists.txt

@@ -23,5 +23,6 @@ add_jar(${PROJECT_NAME} SOURCES
         mmdeploy/TextRecognizer.java
         mmdeploy/Restorer.java
         mmdeploy/PoseDetector.java
+        mmdeploy/RotatedDetector.java
         OUTPUT_NAME mmdeploy
         OUTPUT_DIR ${CMAKE_LIBRARY_OUTPUT_DIRECTORY})

csrc/mmdeploy/apis/java/mmdeploy/Classifier.java

@@ -1,5 +1,6 @@
 package mmdeploy;
 
+/** @description: the Java API class of Classifier. */
 public class Classifier {
     static {
         System.loadLibrary("mmdeploy_java");
@@ -7,22 +8,49 @@ public class Classifier {
 
     private final long handle;
 
+    /** @description: Single classification result of a picture. */
     public static class Result {
+
+        /** Class id. */
         public int label_id;
+
+        /** Class score. */
         public float score;
+
+        /** Initializes a new instance of the Result class.
+         * @param label_id: class id.
+         * @param score: class score.
+        */
         public Result(int label_id, float score) {
             this.label_id = label_id;
             this.score = score;
         }
     }
 
-    public Classifier(String modelPath, String deviceName, int deviceId) {
+    /** Initializes a new instance of the Classifier class.
+     * @param modelPath: model path.
+     * @param deviceName: device name.
+     * @param deviceId: device ID.
+     * @exception Exception: create Classifier failed exception.
+    */
+    public Classifier(String modelPath, String deviceName, int deviceId) throws Exception{
         handle = create(modelPath, deviceName, deviceId);
+        if (handle == -1) {
+            throw new Exception("Create Classifier failed!");
+        }
     }
 
-    public Result[][] apply(Mat[] images) {
+    /** Get label information of each image in a batch.
+     * @param images: input mats.
+     * @return: results of each input mat.
+     * @exception Exception: apply Classifier failed exception.
+    */
+    public Result[][] apply(Mat[] images) throws Exception{
         int[] counts = new int[images.length];
         Result[] results = apply(handle, images, counts);
+        if (results == null) {
+            throw new Exception("Apply Classifier failed!");
+        }
         Result[][] rets = new Result[images.length][];
         int offset = 0;
         for (int i = 0; i < images.length; ++i) {
@@ -36,12 +64,22 @@ public class Classifier {
         return rets;
     }
 
-    public Result[] apply(Mat image) {
+    /** Get label information of one image.
+     * @param image: input mat.
+     * @return: result of input mat.
+     * @exception Exception: apply Classifier failed exception.
+    */
+    public Result[] apply(Mat image) throws Exception{
         int[] counts = new int[1];
         Mat[] images = new Mat[]{image};
-        return apply(handle, images, counts);
+        Result[] results = apply(handle, images, counts);
+        if (results == null) {
+            throw new Exception("Apply Classifier failed!");
+        }
+        return results;
     }
 
+    /** Release the instance of Classifier. */
     public void release() {
         destroy(handle);
     }

csrc/mmdeploy/apis/java/mmdeploy/DataType.java

@@ -1,5 +1,6 @@
 package mmdeploy;
 
+/** @description: DataType. */
 public enum DataType {
     FLOAT(0),
     HALF(1),
@@ -7,6 +8,9 @@ public enum DataType {
     INT32(3);
     final int value;
 
+    /** Initializes a new instance of the DataType class.
+     * @param value: the value.
+    */
     DataType(int value) {
         this.value = value;
     }

csrc/mmdeploy/apis/java/mmdeploy/Detector.java

@@ -1,5 +1,6 @@
 package mmdeploy;
 
+/** @description: the Java API class of Detector. */
 public class Detector {
     static {
         System.loadLibrary("mmdeploy_java");
@@ -7,11 +8,27 @@ public class Detector {
 
     private final long handle;
 
+    /** @description: Single detection result of a picture. */
     public static class Result {
+
+        /** Bbox class id. */
         public int label_id;
+
+        /** Bbox score. */
         public float score;
+
+        /** Bbox coordinates. */
         public Rect bbox;
+
+        /** Bbox mask. */
         public InstanceMask mask;
+
+        /** Initializes a new instance of the Result class.
+         * @param label_id: bbox class id.
+         * @param score: bbox score.
+         * @param bbox: bbox coordinates.
+         * @param mask: bbox mask.
+        */
         public Result(int label_id, float score, Rect bbox, InstanceMask mask) {
             this.label_id = label_id;
             this.score = score;
@@ -20,13 +37,30 @@ public class Detector {
         }
     }
 
-    public Detector(String modelPath, String deviceName, int deviceId) {
+    /** Initializes a new instance of the Detector class.
+     * @param modelPath: model path.
+     * @param deviceName: device name.
+     * @param deviceId: device ID.
+     * @exception Exception: create Detector failed exception.
+    */
+    public Detector(String modelPath, String deviceName, int deviceId) throws Exception {
         handle = create(modelPath, deviceName, deviceId);
+        if (handle == -1) {
+            throw new Exception("Create Detector failed!");
+        }
     }
 
-    public Result[][] apply(Mat[] images) {
+    /** Get information of each image in a batch.
+     * @param images: input mats.
+     * @return: results of each input mat.
+     * @exception Exception: apply Detector failed exception.
+    */
+    public Result[][] apply(Mat[] images) throws Exception {
         int[] counts = new int[images.length];
         Result[] results = apply(handle, images, counts);
+        if (results == null) {
+            throw new Exception("Apply Detector failed!");
+        }
         Result[][] rets = new Result[images.length][];
         int offset = 0;
         for (int i = 0; i < images.length; ++i) {
@@ -40,12 +74,22 @@ public class Detector {
         return rets;
     }
 
-    public Result[] apply(Mat image) {
+    /** Get information of one image.
+     * @param image: input mat.
+     * @return: result of input mat.
+     * @exception Exception: apply Detector failed exception.
+    */
+    public Result[] apply(Mat image) throws Exception{
         int[] counts = new int[1];
         Mat[] images = new Mat[]{image};
-        return apply(handle, images, counts);
+        Result[] results = apply(handle, images, counts);
+        if (results == null) {
+            throw new Exception("Apply Detector failed!");
+        }
+        return results;
     }
 
+    /** Release the instance of Detector. */
     public void release() {
         destroy(handle);
     }

csrc/mmdeploy/apis/java/mmdeploy/InstanceMask.java

@@ -1,10 +1,19 @@
 package mmdeploy;
 
+/** @description: InstanceMask. */
 public class InstanceMask {
+
+    /** Mask shape. */
     public int[] shape;
+
+    /** Mask data. */
     public char[] data;
 
-
+    /** Initialize a new instance of the InstanceMask class.
+     * @param height: height.
+     * @param width: width.
+     * @param data: mask data.
+    */
     public InstanceMask(int height, int width, char[] data) {
         shape = new int[]{height, width};
         this.data = data;

csrc/mmdeploy/apis/java/mmdeploy/Mat.java

@@ -1,12 +1,28 @@
 package mmdeploy;
 
+/** @description: Mat. */
 public class Mat {
+
+    /** Shape. */
     public int[] shape;
+
+    /** Pixel format. */
     public int format;
+
+    /** Data type. */
     public int type;
+
+    /** Mat data. */
     public byte[] data;
 
-
+    /** Initialize a new instance of the Mat class.
+     * @param height: height.
+     * @param width: width.
+     * @param channel: channel.
+     * @param format: pixel format.
+     * @param type: data type.
+     * @param data: mat data.
+    */
     public Mat(int height, int width, int channel,
                PixelFormat format, DataType type, byte[] data) {
         shape = new int[]{height, width, channel};

csrc/mmdeploy/apis/java/mmdeploy/PixelFormat.java

@@ -1,5 +1,6 @@
 package mmdeploy;
 
+/** @description: PixelFormat. */
 public enum PixelFormat {
     BGR(0),
     RGB(1),
@@ -9,6 +10,9 @@ public enum PixelFormat {
     BGRA(5);
     final int value;
 
+    /** Initialize a new instance of the PixelFormat class.
+     * @param value: the value.
+    */
     PixelFormat(int value) {
         this.value = value;
     }

csrc/mmdeploy/apis/java/mmdeploy/PointF.java

@@ -1,10 +1,18 @@
 package mmdeploy;
 
+/** @description: the PointF class. */
 public class PointF {
+
+    /** x coordinate. */
     public float x;
+
+    /** y coordinate. */
     public float y;
 
-
+    /** Initialize a new instance of the PointF class.
+     * @param x: x coordinate.
+     * @param y: y coordinate.
+    */
     public PointF(float x, float y) {
         this.x = x;
         this.y = y;

csrc/mmdeploy/apis/java/mmdeploy/PoseDetector.java

@@ -1,5 +1,6 @@
 package mmdeploy;
 
+/** @description: the Java API class of PoseDetector. */
 public class PoseDetector {
     static {
         System.loadLibrary("mmdeploy_java");
@@ -7,21 +8,48 @@ public class PoseDetector {
 
     private final long handle;
 
+    /** @description: Single pose estimation result of a picture. */
     public static class Result {
+
+        /** Points. */
         public PointF[] point;
+
+        /** Scores of points */
         public float[] score;
+
+        /** Initializes a new instance of the Result class.
+         * @param point: points.
+         * @param score: scores of points.
+        */
         public Result(PointF[] point, float [] score) {
             this.point = point;
             this.score = score;
         }
     }
 
-    public PoseDetector(String modelPath, String deviceName, int deviceId) {
+    /** Initializes a new instance of the PoseDetector class.
+     * @param modelPath: model path.
+     * @param deviceName: device name.
+     * @param deviceId: device ID.
+     * @exception Exception: create PoseDetector failed exception.
+    */
+    public PoseDetector(String modelPath, String deviceName, int deviceId) throws Exception{
         handle = create(modelPath, deviceName, deviceId);
+        if (handle == -1) {
+            throw new Exception("Create PoseDetector failed!");
+        }
     }
 
-    public Result[][] apply(Mat[] images) {
+    /** Get information of each image in a batch.
+     * @param images: input mats.
+     * @return: results of each input mat.
+     * @exception Exception: apply PoseDetector failed exception.
+    */
+    public Result[][] apply(Mat[] images) throws Exception{
         Result[] results = apply(handle, images);
+        if (results == null) {
+            throw new Exception("Apply PoseDetector failed!");
+        }
         Result[][] rets = new Result[images.length][];
         int offset = 0;
         for (int i = 0; i < images.length; ++i) {
@@ -33,11 +61,21 @@ public class PoseDetector {
         return rets;
     }
 
-    public Result[] apply(Mat image) {
+    /** Get information of one image.
+     * @param image: input mat.
+     * @return: result of input mat.
+     * @exception Exception: apply PoseDetector failed exception.
+    */
+    public Result[] apply(Mat image) throws Exception{
         Mat[] images = new Mat[]{image};
-        return apply(handle, images);
+        Result[] results = apply(handle, images);
+        if (results == null) {
+            throw new Exception("Apply PoseDetector failed!");
+        }
+        return results;
     }
 
+    /** Release the instance of PoseDetector. */
     public void release() {
         destroy(handle);
     }

csrc/mmdeploy/apis/java/mmdeploy/Rect.java

@@ -1,12 +1,26 @@
 package mmdeploy;
 
+/** @description: the Rect class. */
 public class Rect {
+
+    /** left coordinate. */
     public float left;
+
+    /** top coordinate. */
     public float top;
+
+    /** right coordinate. */
     public float right;
+
+    /** bottom coordinate. */
     public float bottom;
 
-
+    /** Initialize a new instance of the Rect class.
+     * @param left: left coordinate.
+     * @param top: top coordinate.
+     * @param right: right coordinate.
+     * @param bottom: bottom coordinate.
+    */
     public Rect(float left, float top, float right, float bottom) {
         this.left = left;
         this.top = top;