mirror of
https://github.com/azaion/detections.git
synced 2026-04-22 22:56:31 +00:00
Oleksandr Bezdieniezhnykh
26900d0aee
- Added image specifications for services in `docker-compose.demo-jetson.yml` and `docker-compose.jetson.yml` to streamline deployment. - Updated `Dockerfile.gpu` to use the development version of the CUDA runtime for enhanced compatibility. - Modified `Dockerfile.jetson` to switch to a newer JetPack base image and adjusted the requirements file to include additional dependencies for improved functionality. - Removed obsolete deployment scripts and calibration cache generation script to clean up the project structure. Made-with: Cursor
64 lines
1.9 KiB
Python
64 lines
1.9 KiB
Python
#!/usr/bin/env python3
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"""
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Sample a random subset of images from a YOLO dataset for INT8 calibration.
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Run locally (on your dev machine) before deploying to Jetson:
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python3 scripts/jetson/sample_calibration_images.py \
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--dataset /path/to/dataset-2025-05-22 \
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--output /tmp/calibration \
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--num-samples 500
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The output directory can then be passed directly to deploy_demo_jetson.sh
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via --calibration-images, or to generate_int8_cache.py via --images-dir.
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"""
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import argparse
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import random
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import shutil
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import sys
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from pathlib import Path
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def parse_args():
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parser = argparse.ArgumentParser()
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parser.add_argument("--dataset", required=True, help="Root of the YOLO dataset (must contain images/)")
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parser.add_argument("--output", required=True, help="Destination directory for sampled images")
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parser.add_argument("--num-samples", type=int, default=500)
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parser.add_argument("--seed", type=int, default=42)
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return parser.parse_args()
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def collect_images(dataset_root: Path) -> list[Path]:
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images_dir = dataset_root / "images"
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if not images_dir.is_dir():
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print(f"ERROR: {images_dir} not found", file=sys.stderr)
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sys.exit(1)
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images: list[Path] = []
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for pattern in ("**/*.jpg", "**/*.jpeg", "**/*.png"):
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images += sorted(images_dir.glob(pattern))
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return images
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def main():
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args = parse_args()
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dataset_root = Path(args.dataset)
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output_dir = Path(args.output)
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images = collect_images(dataset_root)
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if not images:
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print(f"ERROR: no images found in {dataset_root / 'images'}", file=sys.stderr)
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sys.exit(1)
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rng = random.Random(args.seed)
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sample = rng.sample(images, min(args.num_samples, len(images)))
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output_dir.mkdir(parents=True, exist_ok=True)
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for src in sample:
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shutil.copy2(src, output_dir / src.name)
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print(f"Sampled {len(sample)} images → {output_dir}")
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if __name__ == "__main__":
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main()
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