yolov10/tests/test_cli.py
Glenn Jocher a5410ed79e
DDP, Comet, URLError fixes, improved error handling (#658)
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Tungway1990 <68179274+Tungway1990@users.noreply.github.com>
2023-01-28 01:31:41 +01:00

76 lines
2.5 KiB
Python

# Ultralytics YOLO 🚀, GPL-3.0 license
import subprocess
from pathlib import Path
from ultralytics.yolo.utils import ROOT, SETTINGS
MODEL = Path(SETTINGS['weights_dir']) / 'yolov8n'
CFG = 'yolov8n'
def run(cmd):
# Run a subprocess command with check=True
subprocess.run(cmd.split(), check=True)
def test_special_modes():
run('yolo checks')
run('yolo settings')
run('yolo help')
# Train checks ---------------------------------------------------------------------------------------------------------
def test_train_det():
run(f'yolo train detect model={CFG}.yaml data=coco8.yaml imgsz=32 epochs=1')
def test_train_seg():
run(f'yolo train segment model={CFG}-seg.yaml data=coco8-seg.yaml imgsz=32 epochs=1')
def test_train_cls():
run(f'yolo train classify model={CFG}-cls.yaml data=mnist160 imgsz=32 epochs=1')
# Val checks -----------------------------------------------------------------------------------------------------------
def test_val_detect():
run(f'yolo val detect model={MODEL}.pt data=coco8.yaml imgsz=32')
def test_val_segment():
run(f'yolo val segment model={MODEL}-seg.pt data=coco8-seg.yaml imgsz=32')
def test_val_classify():
run(f'yolo val classify model={MODEL}-cls.pt data=mnist160 imgsz=32')
# Predict checks -------------------------------------------------------------------------------------------------------
def test_predict_detect():
run(f"yolo predict detect model={MODEL}.pt source={ROOT / 'assets'} imgsz=32")
run(f"yolo predict detect model={MODEL}.pt source=https://ultralytics.com/images/bus.jpg imgsz=32")
run(f"yolo predict detect model={MODEL}.pt source=https://ultralytics.com/assets/decelera_landscape.mov imgsz=32")
run(f"yolo predict detect model={MODEL}.pt source=https://ultralytics.com/assets/decelera_portrait.mov imgsz=32")
def test_predict_segment():
run(f"yolo predict segment model={MODEL}-seg.pt source={ROOT / 'assets'} imgsz=32")
def test_predict_classify():
run(f"yolo predict segment model={MODEL}-cls.pt source={ROOT / 'assets'} imgsz=32")
# Export checks --------------------------------------------------------------------------------------------------------
def test_export_detect_torchscript():
run(f'yolo export model={MODEL}.pt format=torchscript')
def test_export_segment_torchscript():
run(f'yolo export model={MODEL}-seg.pt format=torchscript')
def test_export_classify_torchscript():
run(f'yolo export model={MODEL}-cls.pt format=torchscript')