feat(module3): add simple competition workflow
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#!/usr/bin/env python3
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import argparse
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from datetime import datetime
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from pathlib import Path
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import cv2
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from ultralytics import YOLO
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HERE = Path(__file__).resolve().parent
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("source", help="Фото, видео, папка с фото или 0 для веб-камеры")
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parser.add_argument("--weights", default=str(HERE / "models/latest.pt"))
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parser.add_argument("--conf", type=float, default=0.25)
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args = parser.parse_args()
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source = int(args.source) if args.source.isdigit() else args.source
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model = YOLO(args.weights)
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log_path = HERE / "logs/simple_module_b.log"
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log_path.parent.mkdir(exist_ok=True)
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still_images = False
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if isinstance(source, str):
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path = Path(source)
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still_images = path.is_dir() or path.suffix.lower() in {
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".jpg",
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".jpeg",
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".png",
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".bmp",
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".webp",
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}
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with log_path.open("a", encoding="utf-8") as log:
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results = model.predict(source=source, conf=args.conf, stream=True, verbose=False)
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for result in results:
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now = datetime.now().isoformat(timespec="seconds")
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detections = []
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if result.boxes is not None:
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for box in result.boxes:
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name = result.names[int(box.cls.item())]
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confidence = float(box.conf.item())
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detections.append(f"{name} {confidence:.2f}")
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line = f"{now} | {', '.join(detections) if detections else 'ничего не найдено'}"
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print(line)
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log.write(line + "\n")
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log.flush()
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cv2.imshow("YOLO: q или Esc для выхода", result.plot())
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key = cv2.waitKey(0 if still_images else 1) & 0xFF
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if key in (ord("q"), 27):
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break
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cv2.destroyAllWindows()
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if __name__ == "__main__":
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main()
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