YOLOv3 CI #2452
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# Ultralytics YOLOv3 🚀, AGPL-3.0 license | |
# YOLOv3 Continuous Integration (CI) GitHub Actions tests | |
name: YOLOv3 CI | |
on: | |
push: | |
branches: [master] | |
pull_request: | |
branches: [master] | |
schedule: | |
- cron: "0 0 * * *" # runs at 00:00 UTC every day | |
workflow_dispatch: | |
jobs: | |
Tests: | |
timeout-minutes: 60 | |
runs-on: ${{ matrix.os }} | |
strategy: | |
fail-fast: false | |
matrix: | |
os: [ubuntu-latest, windows-latest] # macos-latest bug https://github.com/ultralytics/yolov5/pull/9049 | |
python-version: ["3.11"] | |
model: [yolov5n] | |
include: | |
# - os: ubuntu-latest | |
# python-version: "3.8" # '3.6.8' min (warning, this test is failing) | |
# model: yolov5n | |
- os: ubuntu-latest | |
python-version: "3.9" | |
model: yolov5n | |
- os: ubuntu-latest | |
python-version: "3.8" # torch 1.8.0 requires python >=3.6, <=3.8 | |
model: yolov5n | |
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: ${{ matrix.python-version }} | |
cache: "pip" # caching pip dependencies | |
- name: Install requirements | |
run: | | |
python -m pip install --upgrade pip wheel | |
torch="" | |
if [ "${{ matrix.torch }}" == "1.8.0" ]; then | |
torch="torch==1.8.0 torchvision==0.9.0" | |
fi | |
pip install -r requirements.txt $torch --extra-index-url https://download.pytorch.org/whl/cpu | |
shell: bash # for Windows compatibility | |
- name: Check environment | |
run: | | |
yolo checks | |
pip list | |
- name: Test detection | |
shell: bash # for Windows compatibility | |
run: | | |
# export PYTHONPATH="$PWD" # to run '$ python *.py' files in subdirectories | |
m=${{ matrix.model }} # official weights | |
b=runs/train/exp/weights/best # best.pt checkpoint | |
python train.py --imgsz 64 --batch 32 --weights $m.pt --cfg $m.yaml --epochs 1 --device cpu # train | |
for d in cpu; do # devices | |
for w in $m $b; do # weights | |
python val.py --imgsz 64 --batch 32 --weights $w.pt --device $d # val | |
python detect.py --imgsz 64 --weights $w.pt --device $d # detect | |
done | |
done | |
python hubconf.py --model $m # hub | |
# python models/tf.py --weights $m.pt # build TF model | |
python models/yolo.py --cfg $m.yaml # build PyTorch model | |
python export.py --weights $m.pt --img 64 --include torchscript # export | |
python - <<EOF | |
import torch | |
im = torch.zeros([1, 3, 64, 64]) | |
for path in '$m', '$b': | |
model = torch.hub.load('.', 'custom', path=path, source='local') | |
print(model('data/images/bus.jpg')) | |
model(im) # warmup, build grids for trace | |
torch.jit.trace(model, [im]) | |
EOF | |
- name: Test segmentation | |
shell: bash # for Windows compatibility | |
run: | | |
m=${{ matrix.model }}-seg # official weights | |
b=runs/train-seg/exp/weights/best # best.pt checkpoint | |
python segment/train.py --imgsz 64 --batch 32 --weights $m.pt --cfg $m.yaml --epochs 1 --device cpu # train | |
python segment/train.py --imgsz 64 --batch 32 --weights '' --cfg $m.yaml --epochs 1 --device cpu # train | |
for d in cpu; do # devices | |
for w in $m $b; do # weights | |
python segment/val.py --imgsz 64 --batch 32 --weights $w.pt --device $d # val | |
python segment/predict.py --imgsz 64 --weights $w.pt --device $d # predict | |
python export.py --weights $w.pt --img 64 --include torchscript --device $d # export | |
done | |
done | |
- name: Test classification | |
shell: bash # for Windows compatibility | |
run: | | |
m=${{ matrix.model }}-cls.pt # official weights | |
b=runs/train-cls/exp/weights/best.pt # best.pt checkpoint | |
python classify/train.py --imgsz 32 --model $m --data mnist160 --epochs 1 # train | |
python classify/val.py --imgsz 32 --weights $b --data ../datasets/mnist160 # val | |
python classify/predict.py --imgsz 32 --weights $b --source ../datasets/mnist160/test/7/60.png # predict | |
python classify/predict.py --imgsz 32 --weights $m --source data/images/bus.jpg # predict | |
python export.py --weights $b --img 64 --include torchscript # export | |
python - <<EOF | |
import torch | |
for path in '$m', '$b': | |
model = torch.hub.load('.', 'custom', path=path, source='local') | |
EOF | |
Summary: | |
runs-on: ubuntu-latest | |
needs: [Tests] # 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.Tests.result == 'failure' || needs.Tests.result == 'cancelled') && github.repository == 'ultralytics/yolov3' && (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 }} |