mirror of https://github.com/open-mmlab/mmocr.git
[CI] Add tests for pytorch 2.0 (#1836)
* [CI] Add tests for pytorch 2.0 * fix * fix * fix * fix * test * update * update1.x
Tong Gao
GitHub
parent
e0a78c021b
commit
97efb04c50
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@ -80,7 +80,7 @@ jobs:
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type: string
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cuda:
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type: enum
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enum: ["10.1", "10.2", "11.1"]
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enum: ["10.1", "10.2", "11.1", "11.7"]
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cudnn:
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type: integer
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default: 7
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@ -150,8 +150,8 @@ workflows:
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- lint
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- build_cpu:
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name: maximum_version_cpu
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torch: 1.13.0
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torchvision: 0.14.0
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torch: 2.0.0
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torchvision: 0.15.1
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python: 3.9.0
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requires:
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- minimum_version_cpu
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@ -167,6 +167,15 @@ workflows:
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cuda: "10.2"
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requires:
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- hold
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- build_cuda:
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name: mainstream_version_gpu
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torch: 2.0.0
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# Use double quotation mark to explicitly specify its type
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# as string instead of number
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cuda: "11.7"
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cudnn: 8
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requires:
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- hold
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merge_stage_test:
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when:
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not:
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@ -19,7 +19,7 @@ concurrency:
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jobs:
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build_cpu_py:
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runs-on: ubuntu-18.04
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runs-on: ubuntu-22.04
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strategy:
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matrix:
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python-version: [3.8, 3.9]
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@ -28,15 +28,15 @@ jobs:
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- torch: 1.8.1
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torchvision: 0.9.1
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steps:
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- uses: actions/checkout@v2
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- uses: actions/checkout@v3
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v2
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uses: actions/setup-python@v4
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with:
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python-version: ${{ matrix.python-version }}
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- name: Upgrade pip
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run: pip install pip --upgrade
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- name: Install PyTorch
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run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
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run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html
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- name: Install MMEngine
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run: pip install git+https://github.com/open-mmlab/mmengine.git@main
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- name: Install MMCV
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@ -56,7 +56,7 @@ jobs:
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coverage report -m
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build_cpu_pt:
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runs-on: ubuntu-18.04
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runs-on: ubuntu-22.04
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strategy:
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matrix:
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python-version: [3.7]
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@ -78,16 +78,19 @@ jobs:
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torchvision: 0.13.1
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- torch: 1.13.0
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torchvision: 0.14.0
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- torch: 2.0.0
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torchvision: 0.15.1
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python-version: 3.8
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steps:
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- uses: actions/checkout@v2
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- uses: actions/checkout@v3
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v2
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uses: actions/setup-python@v4
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with:
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python-version: ${{ matrix.python-version }}
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- name: Upgrade pip
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run: pip install pip --upgrade
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- name: Install PyTorch
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run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
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run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html
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- name: Install MMEngine
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run: pip install git+https://github.com/open-mmlab/mmengine.git@main
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- name: Install MMCV
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@ -116,86 +119,20 @@ jobs:
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name: codecov-umbrella
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fail_ci_if_error: false
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build_cu102:
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runs-on: ubuntu-18.04
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container:
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image: pytorch/pytorch:1.8.1-cuda10.2-cudnn7-devel
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strategy:
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matrix:
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python-version: [3.7]
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include:
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- torch: 1.8.1
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cuda: 10.2
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steps:
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- uses: actions/checkout@v2
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v2
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with:
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python-version: ${{ matrix.python-version }}
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- name: Upgrade pip
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run: pip install pip --upgrade
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- name: Fetch GPG keys
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run: |
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apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
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apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
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- name: Install Python-dev
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run: apt-get update && apt-get install -y python${{matrix.python-version}}-dev
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if: ${{matrix.python-version != 3.9}}
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- name: Install system dependencies
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run: |
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apt-get update && apt-get install -y ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6
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- name: Install mmocr dependencies
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run: |
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pip install git+https://github.com/open-mmlab/mmengine.git@main
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pip install -U openmim
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mim install 'mmcv >= 2.0.0rc1'
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pip install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
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pip install -r requirements/tests.txt
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- name: Build and install
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run: |
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python setup.py check -m -s
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TORCH_CUDA_ARCH_LIST=7.0 pip install -e .
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build_cu116:
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runs-on: ubuntu-18.04
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container:
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image: pytorch/pytorch:1.13.0-cuda11.6-cudnn8-devel
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strategy:
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matrix:
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python-version: [3.7]
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steps:
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- uses: actions/checkout@v2
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v2
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with:
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python-version: ${{ matrix.python-version }}
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- name: Upgrade pip
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run: pip install pip --upgrade
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- name: Fetch GPG keys
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run: |
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apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
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apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
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- name: Install system dependencies
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run: apt-get update && apt-get install -y git ffmpeg libturbojpeg
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- name: Install mmocr dependencies
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run: |
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pip install git+https://github.com/open-mmlab/mmengine.git@main
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pip install -U openmim
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mim install 'mmcv >= 2.0.0rc1'
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pip install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
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pip install -r requirements/tests.txt
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- name: Build and install
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run: |
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python setup.py check -m -s
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TORCH_CUDA_ARCH_LIST=7.0 pip install -e .
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build_windows:
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runs-on: ${{ matrix.os }}
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runs-on: windows-2022
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strategy:
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matrix:
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os: [windows-2022]
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python: [3.7]
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platform: [cpu, cu111]
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torch: [1.8.1]
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torchvision: [0.9.1]
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include:
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- python-version: 3.8
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platform: cu117
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torch: 2.0.0
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torchvision: 0.15.1
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steps:
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- uses: actions/checkout@v2
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- name: Set up Python ${{ matrix.python }}
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@ -207,7 +144,7 @@ jobs:
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- name: Install lmdb
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run: pip install lmdb
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- name: Install PyTorch
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run: pip install torch==1.8.1+${{matrix.platform}} torchvision==0.9.1+${{matrix.platform}} -f https://download.pytorch.org/whl/lts/1.8/torch_lts.html
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run: pip install torch==${{matrix.torch}}+${{matrix.platform}} torchvision==${{matrix.torchvision}}+${{matrix.platform}} -f https://download.pytorch.org/whl/${{matrix.platform}}/torch_stable.html
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- name: Install mmocr dependencies
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run: |
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pip install git+https://github.com/open-mmlab/mmengine.git@main
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@ -17,7 +17,7 @@ concurrency:
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jobs:
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build_cpu:
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runs-on: ubuntu-18.04
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runs-on: ubuntu-22.04
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strategy:
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matrix:
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python-version: [3.7]
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@ -25,15 +25,15 @@ jobs:
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- torch: 1.8.1
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torchvision: 0.9.1
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steps:
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- uses: actions/checkout@v2
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- uses: actions/checkout@v3
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v2
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uses: actions/setup-python@v4
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with:
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python-version: ${{ matrix.python-version }}
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- name: Upgrade pip
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run: pip install pip --upgrade
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- name: Install PyTorch
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run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
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run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html
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- name: Install MMEngine
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run: pip install git+https://github.com/open-mmlab/mmengine.git@main
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- name: Install MMCV
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@ -61,55 +61,24 @@ jobs:
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name: codecov-umbrella
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fail_ci_if_error: false
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build_cu102:
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runs-on: ubuntu-18.04
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container:
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image: pytorch/pytorch:1.8.1-cuda10.2-cudnn7-devel
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strategy:
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matrix:
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python-version: [3.8]
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steps:
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- uses: actions/checkout@v2
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v2
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with:
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python-version: ${{ matrix.python-version }}
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- name: Upgrade pip
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run: pip install pip --upgrade
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- name: Fetch GPG keys
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run: |
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apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
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apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
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- name: Install Python-dev
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run: apt-get update && apt-get install -y python${{matrix.python-version}}-dev
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if: ${{matrix.python-version != 3.9}}
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- name: Install system dependencies
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run: |
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apt-get update
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apt-get install -y ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libxrender-dev
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- name: Install mmocr dependencies
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run: |
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pip install git+https://github.com/open-mmlab/mmengine.git@main
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pip install -U openmim
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mim install 'mmcv >= 2.0.0rc1'
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pip install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
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pip install -r requirements/tests.txt
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- name: Build and install
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run: |
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python setup.py check -m -s
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TORCH_CUDA_ARCH_LIST=7.0 pip install -e .
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build_windows:
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runs-on: ${{ matrix.os }}
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runs-on: windows-2022
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strategy:
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matrix:
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os: [windows-2022]
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python: [3.7]
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platform: [cpu, cu111]
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torch: [1.8.1]
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torchvision: [0.9.1]
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include:
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- python-version: 3.8
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platform: cu117
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torch: 2.0.0
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torchvision: 0.15.1
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steps:
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- uses: actions/checkout@v2
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- uses: actions/checkout@v3
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- name: Set up Python ${{ matrix.python }}
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uses: actions/setup-python@v2
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uses: actions/setup-python@v4
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with:
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python-version: ${{ matrix.python }}
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- name: Upgrade pip
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|
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@ -117,7 +86,7 @@ jobs:
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- name: Install lmdb
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run: pip install lmdb
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- name: Install PyTorch
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run: pip install torch==1.8.1+${{matrix.platform}} torchvision==0.9.1+${{matrix.platform}} -f https://download.pytorch.org/whl/lts/1.8/torch_lts.html
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run: pip install torch==${{matrix.torch}}+${{matrix.platform}} torchvision==${{matrix.torchvision}}+${{matrix.platform}} -f https://download.pytorch.org/whl/${{matrix.platform}}/torch_stable.html
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- name: Install mmocr dependencies
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run: |
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pip install git+https://github.com/open-mmlab/mmengine.git@main
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@ -78,8 +78,6 @@
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"source": [
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"!git clone https://github.com/open-mmlab/mmocr.git\n",
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"%cd mmocr\n",
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"!git checkout 1.x\n",
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"!pip install -r requirements.txt\n",
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"!pip install -v -e .\n",
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"# \"-v\" increases pip's verbosity.\n",
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"# \"-e\" means installing the project in editable mode,\n",
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@ -357,13 +355,13 @@
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "CW2AYtBUA2yb"
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},
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"source": [
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"In order to train SAR to its best state on toy dataset, we need to modify some hyperparameters in the config to accomodate some of the settings of colab.\n",
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"For more explanation about the config and its fields, please refer to [documentation](https://mmocr.readthedocs.io/en/dev-1.x/user_guides/config.html)."
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],
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"metadata": {
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"id": "CW2AYtBUA2yb"
|
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}
|
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]
|
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},
|
||||
{
|
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"cell_type": "code",
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|
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@ -480,17 +478,22 @@
|
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},
|
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{
|
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"cell_type": "markdown",
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"metadata": {
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"id": "xxehFhP7N_xf"
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},
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"source": [
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"### Toy Dataset\n",
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"\n",
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"With the checkpoint we obtained from the last section, we can evaluate it on the toy dataset again. Some more explanataions about the evaulation metrics are available [here](https://mmocr.readthedocs.io/en/dev-1.x/basic_concepts/evaluation.html). "
|
||||
],
|
||||
"metadata": {
|
||||
"id": "xxehFhP7N_xf"
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "PHneq5LxRT6z"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from mmengine.runner import Runner\n",
|
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"import time\n",
|
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|
|
@ -504,47 +507,42 @@
|
|||
"\n",
|
||||
"runner = Runner.from_cfg(cfg)\n",
|
||||
"runner.test()"
|
||||
],
|
||||
"metadata": {
|
||||
"id": "PHneq5LxRT6z"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"source": [
|
||||
"It's also possible to evaluate with a stronger and more generalized pretrained weight, which were trained on larger datasets and achieved quite competitve acadmical performance, though it may not defeat the previous checkpoint overfitted to the toy dataset. ([readme](https://mmocr.readthedocs.io/en/dev-1.x/textrecog_models.html#sar))\n"
|
||||
],
|
||||
"metadata": {
|
||||
"id": "TXmgGRcjOba2"
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"It's also possible to evaluate with a stronger and more generalized pretrained weight, which were trained on larger datasets and achieved quite competitve acadmical performance, though it may not defeat the previous checkpoint overfitted to the toy dataset. ([readme](https://mmocr.readthedocs.io/en/dev-1.x/textrecog_models.html#sar))\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "Uj8qFQjYRCxK"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# The location of pretrained weight\n",
|
||||
"cfg['load_from'] = 'https://download.openmmlab.com/mmocr/textrecog/sar/sar_resnet31_parallel-decoder_5e_st-sub_mj-sub_sa_real/sar_resnet31_parallel-decoder_5e_st-sub_mj-sub_sa_real_20220915_171910-04eb4e75.pth'\n",
|
||||
"cfg.visualizer.name = f'{time.localtime()}'\n",
|
||||
"runner = Runner.from_cfg(cfg)\n",
|
||||
"runner.test()"
|
||||
],
|
||||
"metadata": {
|
||||
"id": "Uj8qFQjYRCxK"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "WctaeVsYR4W_"
|
||||
},
|
||||
"source": [
|
||||
"### SVTP Dataset\n",
|
||||
"\n",
|
||||
"SVTP dataset is one of the six commonly used academic test sets that systematically reflects a text recognizer's performance. Now we will evaluate SAR on this dataset, and we are going to use [Dataset Preparer](https://mmocr.readthedocs.io/en/dev-1.x/user_guides/data_prepare/dataset_preparer.html) to get it prepared first."
|
||||
],
|
||||
"metadata": {
|
||||
"id": "WctaeVsYR4W_"
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
|
|
|
|||
|
|
@ -1,6 +1,8 @@
|
|||
# Changelog of v1.x
|
||||
|
||||
## v1.0.0rc6 (07/03/2023)
|
||||
## v1.0.0 (04/06/2023)
|
||||
|
||||
## v1.0.0rc6 (03/07/2023)
|
||||
|
||||
### Highlights
|
||||
|
||||
|
|
@ -77,7 +79,7 @@ This version requires MMEngine >= 0.6.0, MMCV >= 2.0.0rc4 and MMDet >= 3.0.0rc5.
|
|||
|
||||
**Full Changelog**: https://github.com/open-mmlab/mmocr/compare/v1.0.0rc5...v1.0.0rc6
|
||||
|
||||
## v1.0.0rc5 (06/01/2023)
|
||||
## v1.0.0rc5 (01/06/2023)
|
||||
|
||||
### Highlights
|
||||
|
||||
|
|
@ -141,7 +143,7 @@ This version requires MMEngine >= 0.6.0, MMCV >= 2.0.0rc4 and MMDet >= 3.0.0rc5.
|
|||
|
||||
**Full Changelog**: https://github.com/open-mmlab/mmocr/compare/v1.0.0rc4...v1.0.0rc5
|
||||
|
||||
## v1.0.0rc4 (06/12/2022)
|
||||
## v1.0.0rc4 (12/06/2022)
|
||||
|
||||
### Highlights
|
||||
|
||||
|
|
@ -213,7 +215,7 @@ This version requires MMEngine >= 0.6.0, MMCV >= 2.0.0rc4 and MMDet >= 3.0.0rc5.
|
|||
|
||||
**Full Changelog**: https://github.com/open-mmlab/mmocr/compare/v1.0.0rc3...v1.0.0rc4
|
||||
|
||||
## v1.0.0rc3 (03/11/2022)
|
||||
## v1.0.0rc3 (11/03/2022)
|
||||
|
||||
### Highlights
|
||||
|
||||
|
|
@ -246,11 +248,11 @@ This version requires MMEngine >= 0.6.0, MMCV >= 2.0.0rc4 and MMDet >= 3.0.0rc5.
|
|||
|
||||
**Full Changelog**: https://github.com/open-mmlab/mmocr/compare/v1.0.0rc2...v1.0.0rc3
|
||||
|
||||
## v1.0.0rc2 (14/10/2022)
|
||||
## v1.0.0rc2 (10/14/2022)
|
||||
|
||||
This release relaxes the version requirement of `MMEngine` to `>=0.1.0, < 1.0.0`.
|
||||
|
||||
## v1.0.0rc1 (9/10/2022)
|
||||
## v1.0.0rc1 (10/09/2022)
|
||||
|
||||
### Highlights
|
||||
|
||||
|
|
@ -303,7 +305,7 @@ We release the weights for all the text recognition models in MMOCR 1.0 architec
|
|||
|
||||
**Full Changelog**: https://github.com/open-mmlab/mmocr/compare/v1.0.0rc0...v1.0.0rc1
|
||||
|
||||
## v1.0.0rc0 (1/9/2022)
|
||||
## v1.0.0rc0 (09/01/2022)
|
||||
|
||||
We are excited to announce the release of MMOCR 1.0.0rc0.
|
||||
MMOCR 1.0.0rc0 is the first version of MMOCR 1.x, a part of the OpenMMLab 2.0 projects.
|
||||
|
|
|
|||
Loading…
Reference in New Issue