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| # YOLOv5 🚀 by Ultralytics, GPL-3.0 license | ||
| # YOLOv5 Continuous Integration (CI) GitHub Actions tests | ||
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||
| name: CI CPU testing | ||
| name: YOLOv5 CI | ||
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||
| on: # https://help.github.com/en/actions/reference/events-that-trigger-workflows | ||
| on: | ||
| push: | ||
| branches: [ master ] | ||
| pull_request: | ||
| # The branches below must be a subset of the branches above | ||
| branches: [ master ] | ||
| schedule: | ||
| - cron: '0 0 * * *' # Runs at 00:00 UTC every day | ||
| - cron: '0 0 * * *' # runs at 00:00 UTC every day | ||
|
|
||
| jobs: | ||
| cpu-tests: | ||
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||
| Benchmarks: | ||
| runs-on: ${{ matrix.os }} | ||
| strategy: | ||
| fail-fast: false | ||
| matrix: | ||
| os: [ ubuntu-latest, macos-latest, windows-latest ] | ||
| python-version: [ 3.9 ] | ||
| model: [ 'yolov5n' ] # models to test | ||
| os: [ ubuntu-latest ] | ||
| python-version: [ '3.9' ] # requires python<=3.9 | ||
| model: [ yolov5n ] | ||
| steps: | ||
| - uses: actions/checkout@v3 | ||
| - uses: actions/setup-python@v4 | ||
| with: | ||
| python-version: ${{ matrix.python-version }} | ||
| #- name: Cache pip | ||
| # uses: actions/cache@v3 | ||
| # with: | ||
| # path: ~/.cache/pip | ||
| # key: ${{ runner.os }}-Benchmarks-${{ hashFiles('requirements.txt') }} | ||
| # restore-keys: ${{ runner.os }}-Benchmarks- | ||
| - name: Install requirements | ||
| run: | | ||
| python -m pip install --upgrade pip wheel | ||
| pip install -r requirements.txt coremltools openvino-dev tensorflow-cpu --extra-index-url https://download.pytorch.org/whl/cpu | ||
| python --version | ||
| pip --version | ||
| pip list | ||
| - name: Benchmark DetectionModel | ||
| run: | | ||
| python benchmarks.py --data coco128.yaml --weights ${{ matrix.model }}.pt --img 320 --hard-fail 0.29 | ||
| - name: Benchmark SegmentationModel | ||
| run: | | ||
| python benchmarks.py --data coco128-seg.yaml --weights ${{ matrix.model }}-seg.pt --img 320 --hard-fail 0.22 | ||
| - name: Test predictions | ||
| run: | | ||
| python export.py --weights ${{ matrix.model }}-cls.pt --include onnx --img 224 | ||
| python detect.py --weights ${{ matrix.model }}.onnx --img 320 | ||
| python segment/predict.py --weights ${{ matrix.model }}-seg.onnx --img 320 | ||
| python classify/predict.py --weights ${{ matrix.model }}-cls.onnx --img 224 | ||
| # Timeout: https://stackoverflow.com/a/59076067/4521646 | ||
| Tests: | ||
| timeout-minutes: 60 | ||
| runs-on: ${{ matrix.os }} | ||
| strategy: | ||
| fail-fast: false | ||
| matrix: | ||
| os: [ ubuntu-latest, windows-latest ] # macos-latest bug https://github.com/ultralytics/yolov5/pull/9049 | ||
| python-version: [ '3.10' ] | ||
| model: [ yolov5n ] | ||
| include: | ||
| - os: ubuntu-latest | ||
| python-version: '3.7' # '3.6.8' min | ||
| model: yolov5n | ||
| - os: ubuntu-latest | ||
| python-version: '3.8' | ||
| model: yolov5n | ||
| - os: ubuntu-latest | ||
| python-version: '3.9' | ||
| model: yolov5n | ||
| - os: ubuntu-latest | ||
| python-version: '3.8' # torch 1.7.0 requires python >=3.6, <=3.8 | ||
| model: yolov5n | ||
| torch: '1.7.0' # min torch version CI https://pypi.org/project/torchvision/ | ||
| steps: | ||
| - uses: actions/checkout@v3 | ||
| - name: Set up Python ${{ matrix.python-version }} | ||
| uses: actions/setup-python@v3 | ||
| - uses: actions/setup-python@v4 | ||
| with: | ||
| python-version: ${{ matrix.python-version }} | ||
|
|
||
| # Note: This uses an internal pip API and may not always work | ||
| # https://github.com/actions/cache/blob/master/examples.md#multiple-oss-in-a-workflow | ||
| - name: Get pip cache | ||
| - name: Get cache dir | ||
| # https://github.com/actions/cache/blob/master/examples.md#multiple-oss-in-a-workflow | ||
| id: pip-cache | ||
| run: | | ||
| python -c "from pip._internal.locations import USER_CACHE_DIR; print('::set-output name=dir::' + USER_CACHE_DIR)" | ||
| run: echo "::set-output name=dir::$(pip cache dir)" | ||
| - name: Cache pip | ||
| uses: actions/cache@v3 | ||
| with: | ||
| path: ${{ steps.pip-cache.outputs.dir }} | ||
| key: ${{ runner.os }}-${{ matrix.python-version }}-pip-${{ hashFiles('requirements.txt') }} | ||
| restore-keys: | | ||
| ${{ runner.os }}-${{ matrix.python-version }}-pip- | ||
| # Known Keras 2.7.0 issue: https://github.com/ultralytics/yolov5/pull/5486 | ||
| - name: Install dependencies | ||
| restore-keys: ${{ runner.os }}-${{ matrix.python-version }}-pip- | ||
| - name: Install requirements | ||
| run: | | ||
| python -m pip install --upgrade pip | ||
| pip install -qr requirements.txt -f https://download.pytorch.org/whl/cpu/torch_stable.html \ | ||
| onnx tensorflow-cpu # wandb | ||
| python -m pip install --upgrade pip wheel | ||
| if [ "${{ matrix.torch }}" == "1.7.0" ]; then | ||
| pip install -r requirements.txt torch==1.7.0 torchvision==0.8.1 --extra-index-url https://download.pytorch.org/whl/cpu | ||
| else | ||
| pip install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cpu | ||
| fi | ||
| shell: bash # for Windows compatibility | ||
| - name: Check environment | ||
| run: | | ||
| python -c "import utils; utils.notebook_init()" | ||
| echo "RUNNER_OS is ${{ runner.os }}" | ||
| echo "GITHUB_EVENT_NAME is ${{ github.event_name }}" | ||
| echo "GITHUB_WORKFLOW is ${{ github.workflow }}" | ||
| echo "GITHUB_ACTOR is ${{ github.actor }}" | ||
| echo "GITHUB_REPOSITORY is ${{ github.repository }}" | ||
| echo "GITHUB_REPOSITORY_OWNER is ${{ github.repository_owner }}" | ||
| python --version | ||
| pip --version | ||
| pip list | ||
| shell: bash | ||
|
|
||
| # - name: W&B login | ||
| # run: wandb login 345011b3fb26dc8337fd9b20e53857c1d403f2aa | ||
|
|
||
| # - name: Download data | ||
| # run: | | ||
| # curl -L -o tmp.zip https://github.com/ultralytics/yolov5/releases/download/v1.0/coco128.zip | ||
| # unzip -q tmp.zip -d ../datasets | ||
|
|
||
| - name: Tests workflow | ||
| - name: Test detection | ||
| shell: bash # for Windows compatibility | ||
| run: | | ||
| # export PYTHONPATH="$PWD" # to run '$ python *.py' files in subdirectories | ||
| d=cpu # device | ||
| weights=runs/train/exp/weights/best.pt | ||
| # Train | ||
| python train.py --img 64 --batch 32 --weights ${{ matrix.model }}.pt --cfg ${{ matrix.model }}.yaml --epochs 1 --device $d | ||
| # Val | ||
| python val.py --img 64 --batch 32 --weights ${{ matrix.model }}.pt --device $d | ||
| python val.py --img 64 --batch 32 --weights $weights --device $d | ||
| # Detect | ||
| python detect.py --weights ${{ matrix.model }}.pt --device $d | ||
| python detect.py --weights $weights --device $d | ||
| python hubconf.py # hub | ||
| # Export | ||
| python models/yolo.py --cfg ${{ matrix.model }}.yaml # build PyTorch model | ||
| python models/tf.py --weights ${{ matrix.model }}.pt # build TensorFlow model | ||
| python export.py --weights ${{ matrix.model }}.pt --img 64 --include torchscript onnx # export | ||
| # Python | ||
| m=${{ matrix.model }} # official weights | ||
| b=runs/train/exp/weights/best # best.pt checkpoint | ||
| python train.py --imgsz 64 --batch 32 --weights $m.pt --cfg $m.yaml --epochs 1 --device cpu # train | ||
| for d in cpu; do # devices | ||
| for w in $m $b; do # weights | ||
| python val.py --imgsz 64 --batch 32 --weights $w.pt --device $d # val | ||
| python detect.py --imgsz 64 --weights $w.pt --device $d # detect | ||
| done | ||
| done | ||
| python hubconf.py --model $m # hub | ||
| # python models/tf.py --weights $m.pt # build TF model | ||
| python models/yolo.py --cfg $m.yaml # build PyTorch model | ||
| python export.py --weights $m.pt --img 64 --include torchscript # export | ||
| python - <<EOF | ||
| import torch | ||
| # model = torch.hub.load('ultralytics/yolov5', 'custom', path=$weights) | ||
| im = torch.zeros([1, 3, 64, 64]) | ||
| for path in '$m', '$b': | ||
| model = torch.hub.load('.', 'custom', path=path, source='local') | ||
| print(model('data/images/bus.jpg')) | ||
| model(im) # warmup, build grids for trace | ||
| torch.jit.trace(model, [im]) | ||
| EOF | ||
| - name: Test segmentation | ||
| shell: bash # for Windows compatibility | ||
| run: | | ||
| m=${{ matrix.model }}-seg # official weights | ||
| b=runs/train-seg/exp/weights/best # best.pt checkpoint | ||
| python segment/train.py --imgsz 64 --batch 32 --weights $m.pt --cfg $m.yaml --epochs 1 --device cpu # train | ||
| python segment/train.py --imgsz 64 --batch 32 --weights '' --cfg $m.yaml --epochs 1 --device cpu # train | ||
| for d in cpu; do # devices | ||
| for w in $m $b; do # weights | ||
| python segment/val.py --imgsz 64 --batch 32 --weights $w.pt --device $d # val | ||
| python segment/predict.py --imgsz 64 --weights $w.pt --device $d # predict | ||
| python export.py --weights $w.pt --img 64 --include torchscript --device $d # export | ||
| done | ||
| done | ||
| - name: Test classification | ||
| shell: bash # for Windows compatibility | ||
| run: | | ||
| m=${{ matrix.model }}-cls.pt # official weights | ||
| b=runs/train-cls/exp/weights/best.pt # best.pt checkpoint | ||
| python classify/train.py --imgsz 32 --model $m --data mnist2560 --epochs 1 # train | ||
| python classify/val.py --imgsz 32 --weights $b --data ../datasets/mnist2560 # val | ||
| python classify/predict.py --imgsz 32 --weights $b --source ../datasets/mnist2560/test/7/60.png # predict | ||
| python classify/predict.py --imgsz 32 --weights $m --source data/images/bus.jpg # predict | ||
| python export.py --weights $b --img 64 --imgsz 224 --include torchscript # export | ||
| python - <<EOF | ||
| import torch | ||
| for path in '$m', '$b': | ||
| model = torch.hub.load('.', 'custom', path=path, source='local') | ||
| EOF | ||
| shell: bash |
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