# 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
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]
python-version : [ "3.11" ]
model : [ yolov8n]
steps :
- uses : actions/checkout@v4
- uses : actions/setup-python@v5
with :
python-version : ${{ matrix.python-version }}
cache : "pip" # caching pip dependencies
- name : Install requirements
shell : bash # for Windows compatibility
run : |
python -m pip install --upgrade pip wheel
pip install -e ".[export]" "coverage[toml]" --extra-index-url https://download.pytorch.org/whl/cpu
# Fix SavedModel issue "partially initialized module 'jax' has no attribute 'version' (most likely due to a circular import)" in https://github.com/google/jax/discussions/14036
# pip install -U 'jax!=0.4.15' 'jaxlib!=0.4.15'
yolo export format=tflite imgsz=32 || true
- name : Check environment
run : |
yolo checks
pip list
# - name: Benchmark DetectionModel
# shell: bash
# run: coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ matrix.model }}.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/${{ matrix.model }}-seg.pt' imgsz=160 verbose=0.286
- name : Benchmark ClassificationModel
shell : bash
run : coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ 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/${{ matrix.model }}-pose.pt' imgsz=160 verbose=0.185
- name : Benchmark OBBModel
shell : bash
run : coverage run -a --source=ultralytics -m ultralytics.cfg.__init__ benchmark model='path with spaces/${{ matrix.model }}-obb.pt' imgsz=160 verbose=0.360
- 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]
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 . $torch pytest-cov "coremltools>=7.0" --extra-index-url https://download.pytorch.org/whl/cpu
- name : Check environment
run : |
yolo checks
pip list
- name : Pytest tests
shell : bash # for Windows compatibility
run : |
slow=""
if [[ "${{ 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 : |
pip install pytest 'coremltools>=7.0'
- 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 }}