# 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 epochs=1') def test_val_segment(): run(f'yolo val segment model={MODEL}-seg.pt data=coco8-seg.yaml imgsz=32 epochs=1') def test_val_classify(): pass # Predict checks ------------------------------------------------------------------------------------------------------- def test_predict_detect(): run(f"yolo predict detect model={MODEL}.pt source={ROOT / 'assets'} imgsz=320 conf=0.25") def test_predict_segment(): run(f"yolo predict segment model={MODEL}-seg.pt source={ROOT / 'assets'}") def test_predict_classify(): pass # 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')