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