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73 lines
2.0 KiB
73 lines
2.0 KiB
# Ultralytics YOLO 🚀, GPL-3.0 license
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import subprocess
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from pathlib import Path
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from ultralytics.yolo.utils import ROOT, SETTINGS
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MODEL = Path(SETTINGS['weights_dir']) / 'yolov8n'
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CFG = 'yolov8n'
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def run(cmd):
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# Run a subprocess command with check=True
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subprocess.run(cmd.split(), check=True)
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def test_special_modes():
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run('yolo checks')
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run('yolo settings')
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run('yolo help')
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# Train checks ---------------------------------------------------------------------------------------------------------
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def test_train_det():
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run(f'yolo train detect model={CFG}.yaml data=coco8.yaml imgsz=32 epochs=1')
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def test_train_seg():
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run(f'yolo train segment model={CFG}-seg.yaml data=coco8-seg.yaml imgsz=32 epochs=1')
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def test_train_cls():
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run(f'yolo train classify model={CFG}-cls.yaml data=mnist160 imgsz=32 epochs=1')
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# Val checks -----------------------------------------------------------------------------------------------------------
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def test_val_detect():
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run(f'yolo val detect model={MODEL}.pt data=coco8.yaml imgsz=32 epochs=1')
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def test_val_segment():
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run(f'yolo val segment model={MODEL}-seg.pt data=coco8-seg.yaml imgsz=32 epochs=1')
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def test_val_classify():
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pass
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# Predict checks -------------------------------------------------------------------------------------------------------
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def test_predict_detect():
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run(f"yolo predict detect model={MODEL}.pt source={ROOT / 'assets'} imgsz=320 conf=0.25")
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def test_predict_segment():
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run(f"yolo predict segment model={MODEL}-seg.pt source={ROOT / 'assets'}")
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def test_predict_classify():
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pass
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# Export checks --------------------------------------------------------------------------------------------------------
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def test_export_detect_torchscript():
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run(f'yolo export model={MODEL}.pt format=torchscript')
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def test_export_segment_torchscript():
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run(f'yolo export model={MODEL}-seg.pt format=torchscript')
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def test_export_classify_torchscript():
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run(f'yolo export model={MODEL}-cls.pt format=torchscript')
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