Ultralytics CI #14

Workflow file for this run

	# 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 ${{ github.workflow }} ❌\n\n\nRepository: https://github.com/${{ github.repository }}\nAction: https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}\nAuthor: ${{ github.actor }}\nEvent: ${{ github.event_name }}\n"}
	env:
	SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK_URL_YOLO }}

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Ultralytics CI #14

Workflow file

Ultralytics CI #14

Jobs

Run details

Workflow file for this run