YOLOv5 CI #471
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| # YOLOv5 🚀 by Ultralytics, GPL-3.0 license | |
| # YOLOv5 Continuous Integration (CI) GitHub Actions tests | |
| name: YOLOv5 CI | |
| on: | |
| push: | |
| branches: [ master ] | |
| pull_request: | |
| branches: [ master ] | |
| schedule: | |
| - cron: '0 0 * * *' # runs at 00:00 UTC every day | |
| jobs: | |
| Benchmarks: | |
| runs-on: ${{ matrix.os }} | |
| strategy: | |
| fail-fast: false | |
| matrix: | |
| 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 | |
| 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 | |
| - uses: actions/setup-python@v4 | |
| with: | |
| python-version: ${{ matrix.python-version }} | |
| - name: Get cache dir | |
| # https://github.com/actions/cache/blob/master/examples.md#multiple-oss-in-a-workflow | |
| id: pip-cache | |
| run: echo "::set-output name=dir::$(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- | |
| - name: Install requirements | |
| run: | | |
| 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 ${{ github.repository_owner }}" | |
| python --version | |
| pip --version | |
| pip list | |
| - name: Test detection | |
| shell: bash # for Windows compatibility | |
| run: | | |
| # export PYTHONPATH="$PWD" # to run '$ python *.py' files in subdirectories | |
| 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 $m.pt --img 64 --include torchscript # export | |
| python - <<EOF | |
| import torch | |
| im = torch.zeros([1, 3, 64, 64]) | |
| for path in '$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 |