-
-
Notifications
You must be signed in to change notification settings - Fork 16.3k
150 lines (145 loc) · 6.8 KB
/
ci-testing.yml
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
# Ultralytics YOLOv5 🚀, AGPL-3.0 license
# YOLOv5 Continuous Integration (CI) GitHub Actions tests
name: YOLOv5 CI
on:
push:
branches: [master]
pull_request:
branches: [master]
schedule:
- cron: "0 0 * * *" # runs at 00:00 UTC every day
workflow_dispatch:
jobs:
Benchmarks:
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
os: [ubuntu-latest]
python-version: ["3.11"] # requires python<=3.11
model: [yolov5n]
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
cache: "pip" # cache pip dependencies
- name: Install requirements
run: |
python -m pip install --upgrade pip wheel
pip install -r requirements.txt coremltools openvino-dev "tensorflow-cpu<2.15.1" --extra-index-url https://download.pytorch.org/whl/cpu
yolo checks
pip list
- name: Benchmark DetectionModel
run: |
python benchmarks.py --data coco128.yaml --weights ${{ matrix.model }}.pt --img 320 --hard-fail 0.29
- name: Benchmark SegmentationModel
run: |
python benchmarks.py --data coco128-seg.yaml --weights ${{ matrix.model }}-seg.pt --img 320 --hard-fail 0.22
- name: Test predictions
run: |
python export.py --weights ${{ matrix.model }}-cls.pt --include onnx --img 224
python detect.py --weights ${{ matrix.model }}.onnx --img 320
python segment/predict.py --weights ${{ matrix.model }}-seg.onnx --img 320
python classify/predict.py --weights ${{ matrix.model }}-cls.onnx --img 224
Tests:
timeout-minutes: 60
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
os: [ubuntu-latest, windows-latest, macos-14] # macos-latest bug https://github.com/ultralytics/yolov5/pull/9049
python-version: ["3.11"]
model: [yolov5n]
include:
- 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: [Benchmarks, 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.Benchmarks.result == 'failure' || needs.Tests.result == 'failure' || needs.Benchmarks.result == 'cancelled' || needs.Tests.result == 'cancelled') && github.repository == 'ultralytics/yolov5' && (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 }}