42 lines
1.5 KiB
Python
42 lines
1.5 KiB
Python
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from __future__ import annotations
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import argparse
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from pathlib import Path
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from PIL import Image
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def main() -> int:
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parser = argparse.ArgumentParser(description="Run inference with a fine-tuned RF-DETR checkpoint.")
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parser.add_argument("--weights", type=Path, required=True, help="Path to checkpoint_best_total.pth (or similar)")
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parser.add_argument("--image", type=Path, required=True, help="Path to an image")
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parser.add_argument("--threshold", type=float, default=0.5)
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args = parser.parse_args()
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if not args.weights.exists():
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raise SystemExit(f"Weights not found: {args.weights}")
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if not args.image.exists():
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raise SystemExit(f"Image not found: {args.image}")
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from rfdetr import RFDETRBase
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model = RFDETRBase(pretrain_weights=str(args.weights))
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image = Image.open(args.image).convert("RGB")
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detections = model.predict(image, threshold=args.threshold)
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# Print detections in a simple, script-friendly way.
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# `detections` is a supervision.Detections object.
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print(f"num_detections={len(detections)}")
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for i in range(len(detections)):
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xyxy = detections.xyxy[i].tolist()
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conf = float(detections.confidence[i]) if detections.confidence is not None else None
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cls = int(detections.class_id[i]) if detections.class_id is not None else None
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print({"i": i, "class_id": cls, "confidence": conf, "xyxy": xyxy})
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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