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ultralytics 8.0.41 TF SavedModel and EdgeTPU export (#1034)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Noobtoss <96134731+Noobtoss@users.noreply.github.com>
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
This commit is contained in:
Glenn Jocher
2023-02-20 01:27:28 +01:00
committed by GitHub
parent 4b866c9718
commit f6e393c1d2
64 changed files with 604 additions and 351 deletions
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39
.github/workflows/ci.yaml vendored
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@ -17,7 +17,7 @@ jobs:
strategy:
fail-fast: false
matrix:
os: [ubuntu-latest]
os: [ubuntu-latest, windows-latest, macos-latest]
python-version: ['3.10'] # requires python<=3.9
model: [yolov8n]
steps:
@ -34,7 +34,8 @@ jobs:
- name: Install requirements
run: |
python -m pip install --upgrade pip wheel
pip install -e '.[export]' --extra-index-url https://download.pytorch.org/whl/cpu
pip install -e . coremltools openvino-dev tensorflow-cpu paddlepaddle x2paddle --extra-index-url https://download.pytorch.org/whl/cpu
yolo export format=tflite
- name: Check environment
run: |
echo "RUNNER_OS is ${{ runner.os }}"
@ -46,29 +47,21 @@ jobs:
python --version
pip --version
pip list
- name: TF Lite export
run: |
yolo export model=${{ matrix.model }}.pt format=tflite
yolo task=detect mode=predict model=yolov8n_saved_model/yolov8n_float16.tflite imgsz=640
- name: TF *.pb export
run: |
yolo export model=${{ matrix.model }}.pt format=pb
yolo task=detect mode=predict model=yolov8n.pb imgsz=640
- name: TF Lite Edge TPU export
run: |
yolo export model=${{ matrix.model }}.pt format=edgetpu
- name: TF.js export
run: |
yolo export model=${{ matrix.model }}.pt format=tfjs
- name: Benchmark DetectionModel
shell: python
run: |
# yolo benchmark model=${{ matrix.model }}.pt imgsz=320 min_metric=0.29
from ultralytics.yolo.utils.benchmarks import run_benchmarks
run_benchmarks(model='yolov8n.pt', imgsz=160, half=False, hard_fail=False)
- name: Benchmark SegmentationModel
shell: python
run: |
# yolo benchmark model=${{ matrix.model }}-seg.pt imgsz=320 min_metric=0.29
from ultralytics.yolo.utils.benchmarks import run_benchmarks
run_benchmarks(model='yolov8n-seg.pt', imgsz=160, half=False, hard_fail=False)
- name: Benchmark ClassificationModel
shell: python
run: |
# yolo benchmark model=${{ matrix.model }}-cls.pt imgsz=224 min_metric=0.29
from ultralytics.yolo.utils.benchmarks import run_benchmarks
run_benchmarks(model='yolov8n-cls.pt', imgsz=160, half=False, hard_fail=False)
Tests:
timeout-minutes: 60
@ -76,7 +69,7 @@ jobs:
strategy:
fail-fast: false
matrix:
os: [ubuntu-latest, windows-latest, macos-latest]
os: [ubuntu-latest]
python-version: ['3.10']
model: [yolov8n]
torch: [latest]
@ -155,9 +148,9 @@ jobs:
- name: Test classification
shell: bash # for Windows compatibility
run: |
yolo task=classify mode=train data=mnist160 model=yolov8n-cls.yaml epochs=1 imgsz=32
yolo task=classify mode=train data=mnist160 model=yolov8n-cls.pt epochs=1 imgsz=32
yolo task=classify mode=val data=mnist160 model=runs/classify/train/weights/last.pt imgsz=32
yolo task=classify mode=train data=imagenet10 model=yolov8n-cls.yaml epochs=1 imgsz=32
yolo task=classify mode=train data=imagenet10 model=yolov8n-cls.pt epochs=1 imgsz=32
yolo task=classify mode=val data=imagenet10 model=runs/classify/train/weights/last.pt imgsz=32
yolo task=classify mode=predict model=runs/classify/train/weights/last.pt imgsz=32 source=ultralytics/assets/bus.jpg
yolo mode=export model=runs/classify/train/weights/last.pt imgsz=32 format=torchscript
- name: Pytest tests