# Ultralytics YOLO 🚀, GPL-3.0 license # YOLO Continuous Integration (CI) GitHub Actions tests name: Ultralytics CI on: push: branches: [main] pull_request: branches: [main] schedule: - cron: '0 0 * * *' # runs at 00:00 UTC every day jobs: HUB: if: github.repository == 'ultralytics/ultralytics' && (github.event_name == 'schedule' || github.event_name == 'push') runs-on: ${{ matrix.os }} strategy: fail-fast: false matrix: os: [ubuntu-latest] python-version: ['3.10'] model: [yolov5n] steps: - uses: actions/checkout@v3 - uses: actions/setup-python@v4 with: python-version: ${{ matrix.python-version }} cache: 'pip' # caching pip dependencies - name: Install requirements shell: bash # for Windows compatibility run: | python -m pip install --upgrade pip wheel pip install -e . --extra-index-url https://download.pytorch.org/whl/cpu - name: Check environment run: | 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 HUB training shell: python env: APIKEY: ${{ secrets.ULTRALYTICS_HUB_APIKEY }} run: | import os from ultralytics import hub key = os.environ['APIKEY'] hub.reset_model(key) hub.start(key) Benchmarks: runs-on: ${{ matrix.os }} strategy: fail-fast: false matrix: os: [ubuntu-latest] python-version: ['3.10'] model: [yolov8n] steps: - uses: actions/checkout@v3 - uses: actions/setup-python@v4 with: python-version: ${{ matrix.python-version }} cache: 'pip' # caching pip dependencies - name: Install requirements shell: bash # for Windows compatibility run: | python -m pip install --upgrade pip wheel if [ "${{ matrix.os }}" == "macos-latest" ]; then pip install -e . coremltools openvino-dev tensorflow-macos --extra-index-url https://download.pytorch.org/whl/cpu else pip install -e . coremltools openvino-dev tensorflow-cpu --extra-index-url https://download.pytorch.org/whl/cpu fi yolo export format=tflite - name: Check environment run: | 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 ${{ github.repository_owner }}" python --version pip --version pip list - name: Benchmark DetectionModel shell: python run: | from ultralytics.yolo.utils.benchmarks import benchmark benchmark(model='${{ matrix.model }}.pt', imgsz=160, half=False, hard_fail=0.20) - name: Benchmark SegmentationModel shell: python run: | from ultralytics.yolo.utils.benchmarks import benchmark benchmark(model='${{ matrix.model }}-seg.pt', imgsz=160, half=False, hard_fail=0.14) - name: Benchmark ClassificationModel shell: python run: | from ultralytics.yolo.utils.benchmarks import benchmark benchmark(model='${{ matrix.model }}-cls.pt', imgsz=160, half=False, hard_fail=0.61) - name: Benchmark Summary run: | cat benchmarks.log echo "$(cat benchmarks.log)" >> $GITHUB_STEP_SUMMARY Tests: timeout-minutes: 60 runs-on: ${{ matrix.os }} strategy: fail-fast: false matrix: os: [ubuntu-latest] python-version: ['3.7', '3.8', '3.9', '3.10'] model: [yolov8n] torch: [latest] include: - os: ubuntu-latest python-version: '3.8' # torch 1.7.0 requires python >=3.6, <=3.8 model: yolov8n torch: '1.8.0' # min torch version CI https://pypi.org/project/torchvision/ steps: - uses: actions/checkout@v3 - uses: actions/setup-python@v4 with: python-version: ${{ matrix.python-version }} cache: 'pip' # caching pip dependencies - name: Install requirements shell: bash # for Windows compatibility run: | python -m pip install --upgrade pip wheel if [ "${{ matrix.torch }}" == "1.8.0" ]; then pip install -e . torch==1.8.0 torchvision==0.9.0 pytest --extra-index-url https://download.pytorch.org/whl/cpu else pip install -e . pytest --extra-index-url https://download.pytorch.org/whl/cpu fi - name: Check environment run: | 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: | yolo task=detect mode=train data=coco8.yaml model=yolov8n.yaml epochs=1 imgsz=32 yolo task=detect mode=train data=coco8.yaml model=yolov8n.pt epochs=1 imgsz=32 yolo task=detect mode=val data=coco8.yaml model=runs/detect/train/weights/last.pt imgsz=32 yolo task=detect mode=predict model=runs/detect/train/weights/last.pt imgsz=32 source=ultralytics/assets/bus.jpg yolo mode=export model=runs/detect/train/weights/last.pt imgsz=32 format=torchscript - name: Test segmentation shell: bash # for Windows compatibility run: | yolo task=segment mode=train data=coco8-seg.yaml model=yolov8n-seg.yaml epochs=1 imgsz=32 yolo task=segment mode=train data=coco8-seg.yaml model=yolov8n-seg.pt epochs=1 imgsz=32 yolo task=segment mode=val data=coco8-seg.yaml model=runs/segment/train/weights/last.pt imgsz=32 yolo task=segment mode=predict model=runs/segment/train/weights/last.pt imgsz=32 source=ultralytics/assets/bus.jpg yolo mode=export model=runs/segment/train/weights/last.pt imgsz=32 format=torchscript - name: Test classification shell: bash # for Windows compatibility run: | yolo task=classify mode=train data=imagenet10 model=yolov8n-cls.yaml epochs=1 imgsz=32 yolo task=classify mode=train data=imagenet10 model=yolov8n-cls.pt epochs=1 imgsz=32 yolo task=classify mode=val data=imagenet10 model=runs/classify/train/weights/last.pt imgsz=32 yolo task=classify mode=predict model=runs/classify/train/weights/last.pt imgsz=32 source=ultralytics/assets/bus.jpg yolo mode=export model=runs/classify/train/weights/last.pt imgsz=32 format=torchscript - name: Pytest tests shell: bash # for Windows compatibility run: pytest tests