forked from zakaria/chicken-counting-sukawarna-det
proitlab
d31ad05f0a
- Remove shared DetectionTracker across cameras to prevent state leakage - Add task="detect" to YOLO constructor to suppress warning - Add export_engine.py script for .pt to .engine conversion - Regenerate ONNX and TensorRT engine with latest settings
79 lines
2.3 KiB
Python
79 lines
2.3 KiB
Python
#!/usr/bin/env python3
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"""Export a YOLO .pt model to TensorRT .engine.
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Usage:
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python3 export_engine.py chicken-detection-model-v26n-300e-best-2026-05-02-NEW.pt
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python3 export_engine.py model.pt --imgsz 640 --half --workspace 4
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"""
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from __future__ import annotations
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import argparse
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import sys
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from pathlib import Path
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def export_engine(
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model_path: str | Path,
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*,
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imgsz: int = 640,
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half: bool = True,
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int8: bool = False,
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batch: int = 1,
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workspace: int = 4, # GB
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simplify: bool = True,
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opset: int = 17,
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verbose: bool = True,
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) -> str:
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from ultralytics import YOLO
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model = YOLO(model_path, task="detect")
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output = model.export(
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format="engine",
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imgsz=imgsz,
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half=half,
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int8=int8,
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batch=batch,
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workspace=workspace,
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simplify=simplify,
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opset=opset,
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verbose=verbose,
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)
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print(f"\nExported to: {output}")
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return str(output)
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def main():
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parser = argparse.ArgumentParser(description="Export YOLO .pt → TensorRT .engine")
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parser.add_argument("model", help="Path to .pt model file")
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parser.add_argument("--imgsz", type=int, default=640, help="Input image size (default: 640)")
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parser.add_argument("--half", action="store_true", default=True, help="FP16 precision (default: on)")
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parser.add_argument("--no-half", dest="half", action="store_false", help="FP32 precision")
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parser.add_argument("--int8", action="store_true", help="INT8 quantization (needs calibration)")
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parser.add_argument("--batch", type=int, default=1, help="Batch size (default: 1)")
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parser.add_argument("--workspace", type=int, default=4, help="GPU workspace in GB (default: 4)")
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parser.add_argument("--opset", type=int, default=17, help="ONNX opset version (default: 17)")
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parser.add_argument("--quiet", action="store_true", help="Suppress verbose output")
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args = parser.parse_args()
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if not Path(args.model).exists():
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print(f"error: model file not found: {args.model}", file=sys.stderr)
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sys.exit(1)
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export_engine(
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args.model,
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imgsz=args.imgsz,
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half=args.half,
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int8=args.int8,
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batch=args.batch,
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workspace=args.workspace,
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opset=args.opset,
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verbose=not args.quiet,
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)
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if __name__ == "__main__":
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main()
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