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94 lines
2.7 KiB
94 lines
2.7 KiB
# Ultralytics YOLO 🚀, GPL-3.0 license |
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from pathlib import Path |
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from ultralytics.yolo.cfg import get_cfg |
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from ultralytics.yolo.utils import DEFAULT_CFG_PATH, ROOT, SETTINGS |
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from ultralytics.yolo.v8 import classify, detect, segment |
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CFG_DET = 'yolov8n.yaml' |
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CFG_SEG = 'yolov8n-seg.yaml' |
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CFG_CLS = 'squeezenet1_0' |
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CFG = get_cfg(DEFAULT_CFG_PATH) |
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MODEL = Path(SETTINGS['weights_dir']) / 'yolov8n' |
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SOURCE = ROOT / "assets" |
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def test_detect(): |
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overrides = {"data": "coco8.yaml", "model": CFG_DET, "imgsz": 32, "epochs": 1, "save": False} |
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CFG.data = "coco8.yaml" |
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# Trainer |
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trainer = detect.DetectionTrainer(overrides=overrides) |
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trainer.train() |
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# Validator |
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val = detect.DetectionValidator(args=CFG) |
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val(model=trainer.best) # validate best.pt |
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# Predictor |
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pred = detect.DetectionPredictor(overrides={"imgsz": [64, 64]}) |
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result = pred(source=SOURCE, model=f"{MODEL}.pt") |
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assert len(result), "predictor test failed" |
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overrides["resume"] = trainer.last |
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trainer = detect.DetectionTrainer(overrides=overrides) |
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try: |
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trainer.train() |
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except Exception as e: |
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print(f"Expected exception caught: {e}") |
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return |
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Exception("Resume test failed!") |
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def test_segment(): |
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overrides = {"data": "coco8-seg.yaml", "model": CFG_SEG, "imgsz": 32, "epochs": 1, "save": False} |
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CFG.data = "coco8-seg.yaml" |
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CFG.v5loader = False |
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# YOLO(CFG_SEG).train(**overrides) # works |
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# trainer |
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trainer = segment.SegmentationTrainer(overrides=overrides) |
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trainer.train() |
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# Validator |
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val = segment.SegmentationValidator(args=CFG) |
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val(model=trainer.best) # validate best.pt |
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# Predictor |
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pred = segment.SegmentationPredictor(overrides={"imgsz": [64, 64]}) |
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result = pred(source=SOURCE, model=f"{MODEL}-seg.pt") |
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assert len(result) == 2, "predictor test failed" |
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# Test resume |
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overrides["resume"] = trainer.last |
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trainer = segment.SegmentationTrainer(overrides=overrides) |
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try: |
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trainer.train() |
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except Exception as e: |
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print(f"Expected exception caught: {e}") |
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return |
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Exception("Resume test failed!") |
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def test_classify(): |
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overrides = {"data": "mnist160", "model": "yolov8n-cls.yaml", "imgsz": 32, "epochs": 1, "batch": 64, "save": False} |
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CFG.data = "mnist160" |
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CFG.imgsz = 32 |
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CFG.batch = 64 |
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# YOLO(CFG_SEG).train(**overrides) # works |
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# Trainer |
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trainer = classify.ClassificationTrainer(overrides=overrides) |
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trainer.train() |
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# Validator |
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val = classify.ClassificationValidator(args=CFG) |
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val(model=trainer.best) |
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# Predictor |
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pred = classify.ClassificationPredictor(overrides={"imgsz": [64, 64]}) |
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result = pred(source=SOURCE, model=trainer.best) |
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assert len(result) == 2, "predictor test failed"
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