ultralytics/.github/workflows/ci.yaml

# Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLO Continuous Integration (CI) GitHub Actions tests

name: Ultralytics CI

on:
  push:
    branches: [main]
    paths-ignore:
      - "docs/**"
      - "mkdocs.yml"
  pull_request:
    branches: [main]
    paths-ignore:
      - "docs/**"
  schedule:
    - cron: "0 0 * * *" # runs at 00:00 UTC every day
  workflow_dispatch:
    inputs:
      hub:
        description: "Run HUB"
        default: false
        type: boolean
      benchmarks:
        description: "Run Benchmarks"
        default: false
        type: boolean
      tests:
        description: "Run Tests"
        default: false
        type: boolean
      gpu:
        description: "Run GPU"
        default: false
        type: boolean
      conda:
        description: "Run Conda"
        default: false
        type: boolean

jobs:
  HUB:
    if: github.repository == 'ultralytics/ultralytics' && (github.event_name == 'schedule' || github.event_name == 'push' || (github.event_name == 'workflow_dispatch' && github.event.inputs.hub == 'true'))
    runs-on: ${{ matrix.os }}
    strategy:
      fail-fast: false
      matrix:
        os: [ubuntu-latest]
        python-version: ["3.11"]
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        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: |
          yolo checks
          pip list          
      - name: Test HUB training
        shell: python
        env:
          API_KEY: ${{ secrets.ULTRALYTICS_HUB_API_KEY }}
          MODEL_ID: ${{ secrets.ULTRALYTICS_HUB_MODEL_ID }}
        run: |
          import os
          from ultralytics import YOLO, hub
          api_key, model_id = os.environ['API_KEY'], os.environ['MODEL_ID']
          hub.login(api_key)
          hub.reset_model(model_id)
          model = YOLO('https://hub.ultralytics.com/models/' + model_id)
          model.train()          
      - name: Test HUB inference API
        shell: python
        env:
          API_KEY: ${{ secrets.ULTRALYTICS_HUB_API_KEY }}
          MODEL_ID: ${{ secrets.ULTRALYTICS_HUB_MODEL_ID }}
        run: |
          import os
          import requests
          import json
          api_key, model_id = os.environ['API_KEY'], os.environ['MODEL_ID']
          url = f"https://api.ultralytics.com/v1/predict/{model_id}"
          headers = {"x-api-key": api_key}
          data = {"size": 320, "confidence": 0.25, "iou": 0.45}
          with open("ultralytics/assets/zidane.jpg", "rb") as f:
              response = requests.post(url, headers=headers, data=data, files={"image": f})
          assert response.status_code == 200, f'Status code {response.status_code}, Reason {response.reason}'
          print(json.dumps(response.json(), indent=2))          

  Benchmarks:
    if: github.event_name != 'workflow_dispatch' || github.event.inputs.benchmarks == 'true'
    runs-on: ${{ matrix.os }}
    strategy:
      fail-fast: false
      matrix:
        os: [ubuntu-latest, macos-14]
        python-version: ["3.11"]
        model: [yolov8n]
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: ${{ matrix.python-version }}
          cache: "pip" # caching pip dependencies
      - name: Install requirements
        shell: bash # for Windows compatibility
        run: |
          python -m pip install --upgrade pip wheel
          pip install -e ".[export]" "coverage[toml]" --extra-index-url https://download.pytorch.org/whl/cpu
          # yolo export format=tflite imgsz=32 || true          
      - name: Check environment
        run: |
          yolo checks
          pip list          
      - name: Benchmark World DetectionModel
        shell: bash
        run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/yolov8s-worldv2.pt' imgsz=160 verbose=0.318
      - name: Benchmark SegmentationModel
        shell: bash
        run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ matrix.model }}-seg.pt' imgsz=160 verbose=0.281
      - name: Benchmark ClassificationModel
        shell: bash
        run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ matrix.model }}-cls.pt' imgsz=160 verbose=0.166
      - name: Benchmark PoseModel
        shell: bash
        run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ matrix.model }}-pose.pt' imgsz=160 verbose=0.183
      - name: Benchmark OBBModel
        shell: bash
        run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ matrix.model }}-obb.pt' imgsz=160 verbose=0.472
      - name: Merge Coverage Reports
        run: |
                    coverage xml -o coverage-benchmarks.xml
      - name: Upload Coverage Reports to CodeCov
        if: github.repository == 'ultralytics/ultralytics'
        uses: codecov/codecov-action@v4
        with:
          flags: Benchmarks
        env:
          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
      - name: Benchmark Summary
        run: |
          cat benchmarks.log
          echo "$(cat benchmarks.log)" >> $GITHUB_STEP_SUMMARY          

  Tests:
    if: github.event_name != 'workflow_dispatch' || github.event.inputs.tests == 'true'
    timeout-minutes: 60
    runs-on: ${{ matrix.os }}
    strategy:
      fail-fast: false
      matrix:
        os: [ubuntu-latest, macos-14]
        python-version: ["3.11"]
        torch: [latest]
        include:
          - os: ubuntu-latest
            python-version: "3.8" # torch 1.8.0 requires python >=3.6, <=3.8
            torch: "1.8.0" # min torch version CI https://pypi.org/project/torchvision/
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: ${{ matrix.python-version }}
          cache: "pip" # caching pip dependencies
      - name: Install requirements
        shell: bash # for Windows compatibility
        run: |
          # CoreML must be installed before export due to protobuf error from AutoInstall
          python -m pip install --upgrade pip wheel
          torch=""
          if [ "${{ matrix.torch }}" == "1.8.0" ]; then
              torch="torch==1.8.0 torchvision==0.9.0"
          fi
          pip install -e . $torch pytest-cov "coremltools>=7.0; platform_system != 'Windows' and python_version <= '3.11'" --extra-index-url https://download.pytorch.org/whl/cpu          
      - name: Check environment
        run: |
          yolo checks
          pip list          
      - name: Pytest tests
        shell: bash # for Windows compatibility
        run: |
          slow=""
          if [[ "${{ github.event_name }}" == "schedule" ]] || [[ "${{ github.event_name }}" == "workflow_dispatch" ]]; then
              pip install mlflow pycocotools 'ray[tune]'
              slow="--slow"
          fi
          pytest $slow --cov=ultralytics/ --cov-report xml tests/          
      - name: Upload Coverage Reports to CodeCov
        if: github.repository == 'ultralytics/ultralytics' # && matrix.os == 'ubuntu-latest' && matrix.python-version == '3.11'
        uses: codecov/codecov-action@v4
        with:
          flags: Tests
        env:
          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}

  GPU:
    if: github.repository == 'ultralytics/ultralytics' && (github.event_name != 'workflow_dispatch' || github.event.inputs.gpu == 'true')
    timeout-minutes: 60
    runs-on: gpu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Install requirements
        run: pip install -e .
      - name: Check environment
        run: |
          yolo checks
          pip list          
      - name: Pytest tests
        run: pytest --cov=ultralytics/ --cov-report xml tests/test_cuda.py
      - name: Upload Coverage Reports to CodeCov
        uses: codecov/codecov-action@v4
        with:
          flags: GPU
        env:
          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}

  Conda:
    if: github.repository == 'ultralytics/ultralytics' && (github.event_name == 'schedule_disabled' || github.event.inputs.conda == 'true')
    runs-on: ${{ matrix.os }}
    strategy:
      fail-fast: false
      matrix:
        os: [ubuntu-latest]
        python-version: ["3.11"]
    defaults:
      run:
        shell: bash -el {0}
    steps:
      - uses: conda-incubator/setup-miniconda@v3
        with:
          python-version: ${{ matrix.python-version }}
          mamba-version: "*"
          channels: conda-forge,defaults
          channel-priority: true
          activate-environment: anaconda-client-env
      - name: Install Libmamba
        run: |
                    conda config --set solver libmamba
      - name: Install Ultralytics package from conda-forge
        run: |
                    conda install -c pytorch -c conda-forge pytorch torchvision ultralytics openvino
      - name: Install pip packages
        run: |
          # CoreML must be installed before export due to protobuf error from AutoInstall
          pip install pytest "coremltools>=7.0; platform_system != 'Windows' and python_version <= '3.11'"          
      - name: Check environment
        run: |
                    conda list
      - name: Test CLI
        run: |
          yolo predict model=yolov8n.pt imgsz=320
          yolo train model=yolov8n.pt data=coco8.yaml epochs=1 imgsz=32
          yolo val model=yolov8n.pt data=coco8.yaml imgsz=32
          yolo export model=yolov8n.pt format=torchscript imgsz=160          
      - name: Test Python
        run: |
          python -c "
          from ultralytics import YOLO
          model = YOLO('yolov8n.pt')
          results = model.train(data='coco8.yaml', epochs=3, imgsz=160)
          results = model.val(imgsz=160)
          results = model.predict(imgsz=160)
          results = model.export(format='onnx', imgsz=160)
          "          
      - name: PyTest
        run: |
          git clone https://github.com/ultralytics/ultralytics
          pytest ultralytics/tests          

  Summary:
    runs-on: ubuntu-latest
    needs: [HUB, Benchmarks, Tests, GPU, Conda] # Add job names that you want to check for failure
    if: always() # This ensures the job runs even if previous jobs fail
    steps:
      - name: Check for failure and notify
        if: (needs.HUB.result == 'failure' || needs.Benchmarks.result == 'failure' || needs.Tests.result == 'failure' || needs.GPU.result == 'failure' || needs.Conda.result == 'failure') && github.repository == 'ultralytics/ultralytics' && (github.event_name == 'schedule' || github.event_name == 'push')
        uses: slackapi/slack-github-action@v1.25.0
        with:
          payload: |
                        {"text": "<!channel> GitHub Actions error for ${{ github.workflow }} ❌\n\n\n*Repository:* https://github.com/${{ github.repository }}\n*Action:* https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}\n*Author:* ${{ github.actor }}\n*Event:* ${{ github.event_name }}\n"}
        env:
          SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK_URL_YOLO }}