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65 lines
1.9 KiB
65 lines
1.9 KiB
# Ultralytics YOLO 🚀, GPL-3.0 license |
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import os |
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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 test_checks(): |
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os.system('yolo mode=checks') |
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# Train checks --------------------------------------------------------------------------------------------------------- |
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def test_train_det(): |
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os.system(f'yolo mode=train task=detect model={CFG}.yaml data=coco128.yaml imgsz=32 epochs=1') |
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def test_train_seg(): |
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os.system(f'yolo mode=train task=segment model={CFG}-seg.yaml data=coco128-seg.yaml imgsz=32 epochs=1') |
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def test_train_cls(): |
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os.system(f'yolo mode=train task=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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os.system(f'yolo mode=val task=detect model={MODEL}.pt data=coco128.yaml imgsz=32 epochs=1') |
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def test_val_segment(): |
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os.system(f'yolo mode=val task=segment model={MODEL}-seg.pt data=coco128-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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os.system(f"yolo mode=predict model={MODEL}.pt source={ROOT / 'assets'}") |
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def test_predict_segment(): |
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os.system(f"yolo mode=predict 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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os.system(f'yolo mode=export model={MODEL}.pt format=torchscript') |
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def test_export_segment_torchscript(): |
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os.system(f'yolo mode=export model={MODEL}-seg.pt format=torchscript') |
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def test_export_classify_torchscript(): |
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pass
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