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ci.yaml
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# Ultralytics YOLO 🚀, AGPL-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
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
raspberrypi:
description: "Run Raspberry Pi"
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: ${{ matrix.python-version }}
cache: "pip" # caching pip dependencies
- name: Install requirements
shell: bash # for Windows compatibility
run: |
python -m pip install --upgrade pip wheel
pip install -e ".[export]" "coverage[toml]" --extra-index-url https://download.pytorch.org/whl/cpu
- name: Check environment
run: |
yolo checks
pip list
- name: Benchmark ClassificationModel
shell: bash
run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ matrix.model }}-cls.pt' imgsz=160 verbose=0.166
- name: Benchmark YOLOWorld 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/${{ matrix.model }}-seg.pt' imgsz=160 verbose=0.279
- name: Benchmark PoseModel
shell: bash
run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ 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: Benchmark YOLOv10Model
shell: bash
run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/yolov10n.pt' imgsz=160 verbose=0.178
- 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: 360
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: ${{ matrix.python-version }}
cache: "pip" # caching pip dependencies
- name: Install requirements
shell: bash # for Windows compatibility
run: |
# CoreML must be installed before export due to protobuf error from AutoInstall
python -m pip install --upgrade pip wheel
slow=""
torch=""
if [ "${{ matrix.torch }}" == "1.8.0" ]; then
torch="torch==1.8.0 torchvision==0.9.0"
fi
if [[ "${{ github.event_name }}" =~ ^(schedule|workflow_dispatch)$ ]]; then
slow="pycocotools mlflow ray[tune]"
fi
pip install -e ".[export]" $torch $slow pytest-cov --extra-index-url https://download.pytorch.org/whl/cpu
- name: Check environment
run: |
yolo checks
pip list
- name: Pytest tests
shell: bash # for Windows compatibility
run: |
slow=""
if [[ "${{ github.event_name }}" =~ ^(schedule|workflow_dispatch)$ ]]; then
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: ${{ secrets.CODECOV_TOKEN }}
GPU:
if: github.repository == 'ultralytics/ultralytics' && (github.event_name != 'workflow_dispatch' || github.event.inputs.gpu == 'true')
timeout-minutes: 360
runs-on: gpu-latest
steps:
- uses: actions/checkout@v4
- name: Install requirements
run: pip install -e . pytest-cov
- name: Check environment
run: |
yolo checks
pip list
- name: Pytest tests
run: |
slow=""
if [[ "${{ github.event_name }}" =~ ^(schedule|workflow_dispatch)$ ]]; then
slow="--slow"
fi
pytest $slow --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: ${{ secrets.CODECOV_TOKEN }}
RaspberryPi:
if: github.repository == 'ultralytics/ultralytics' && (github.event_name == 'schedule' || github.event.inputs.raspberrypi == 'true')
timeout-minutes: 120
runs-on: raspberry-pi
steps:
- uses: actions/checkout@v4
- name: Activate Virtual Environment
run: |
python3.11 -m venv env
source env/bin/activate
echo PATH=$PATH >> $GITHUB_ENV
- name: Install requirements
run: |
python -m pip install --upgrade pip wheel
pip install -e ".[export]" pytest mlflow pycocotools "ray[tune]"
- name: Check environment
run: |
yolo checks
pip list
- name: Pytest tests
run: pytest --slow tests/
- name: Benchmark ClassificationModel
run: python -m ultralytics.cfg.__init__ benchmark model='yolov8n-cls.pt' imgsz=160 verbose=0.166
- name: Benchmark YOLOWorld DetectionModel
run: python -m ultralytics.cfg.__init__ benchmark model='yolov8s-worldv2.pt' imgsz=160 verbose=0.318
- name: Benchmark SegmentationModel
run: python -m ultralytics.cfg.__init__ benchmark model='yolov8n-seg.pt' imgsz=160 verbose=0.267
- name: Benchmark PoseModel
run: python -m ultralytics.cfg.__init__ benchmark model='yolov8n-pose.pt' imgsz=160 verbose=0.179
- name: Benchmark OBBModel
run: python -m ultralytics.cfg.__init__ benchmark model='yolov8n-obb.pt' imgsz=160 verbose=0.472
- name: Benchmark Summary
run: |
cat benchmarks.log
echo "$(cat benchmarks.log)" >> $GITHUB_STEP_SUMMARY
- name: Reboot # run a reboot command in the background to free resources for next run and not crash main thread
run: sudo bash -c "sleep 10; reboot" &
Conda:
if: github.repository == 'ultralytics/ultralytics' && (github.event_name == 'schedule' || 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: Cleanup toolcache
run: |
echo "Free space before deletion:"
df -h /
rm -rf /opt/hostedtoolcache
echo "Free space after deletion:"
df -h /
- name: Install Linux packages
run: |
# Fix cv2 ImportError: 'libEGL.so.1: cannot open shared object file: No such file or directory'
sudo apt-get update
sudo apt-get install -y libegl1 libopengl0
- 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
# Note this step must use the updated default bash environment, not a python environment
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, RaspberryPi, 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.RaspberryPi.result == 'failure' || needs.Conda.result == 'failure' ) && github.repository == 'ultralytics/ultralytics' && (github.event_name == 'schedule' || github.event_name == 'push')
uses: slackapi/[email protected]
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 }}