e8375d6c72
Adds ensure_blla_model.py which loads the blla segmentation model with ketos on every container start. If the model is missing or in the legacy PyTorch ZIP format (incompatible with ketos 7), it re-downloads the correct CoreML protobuf model from Zenodo (DOI 10.5281/zenodo.14602569). The Dockerfile now uses entrypoint.sh which runs this check before starting uvicorn. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
78 lines
2.3 KiB
Python
78 lines
2.3 KiB
Python
"""Validates the blla segmentation base model and downloads it if needed.
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Run at container startup before uvicorn. ketos 7 requires the model in
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CoreML protobuf or safetensors format — legacy PyTorch ZIP archives
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(torch.save output from kraken <4) are not loadable and will be replaced.
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Exits non-zero on failure so Docker marks the container unhealthy rather
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than silently starting with a broken model.
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"""
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import glob
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import logging
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import os
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import shutil
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import subprocess
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import sys
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logging.basicConfig(
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level=logging.INFO,
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format="%(levelname)s:ensure_blla_model:%(message)s",
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)
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log = logging.getLogger(__name__)
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BLLA_MODEL_PATH = os.environ.get("BLLA_MODEL_PATH", "/app/models/blla.mlmodel")
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# DOI for "General segmentation model for print and handwriting" — ketos 7 compatible.
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BLLA_MODEL_DOI = "10.5281/zenodo.14602569"
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HTRMOPO_DIR = os.path.expanduser("~/.local/share/htrmopo")
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def _model_is_loadable(path: str) -> bool:
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try:
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from kraken.lib import vgsl
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vgsl.TorchVGSLModel.load_model(path)
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return True
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except Exception as e:
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log.warning("Model at %s failed to load: %s", path, e)
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return False
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def _download_blla() -> str:
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log.info("Downloading blla model (DOI %s) ...", BLLA_MODEL_DOI)
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result = subprocess.run(
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["kraken", "get", BLLA_MODEL_DOI],
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capture_output=True,
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text=True,
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)
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if result.returncode != 0:
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log.error("kraken get failed: %s", result.stderr)
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sys.exit(1)
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candidates = sorted(glob.glob(os.path.join(HTRMOPO_DIR, "*/blla.mlmodel")))
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if not candidates:
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log.error("Downloaded blla.mlmodel not found under %s", HTRMOPO_DIR)
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sys.exit(1)
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return candidates[-1]
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def main() -> None:
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if os.path.exists(BLLA_MODEL_PATH):
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if _model_is_loadable(BLLA_MODEL_PATH):
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log.info("blla model OK: %s", BLLA_MODEL_PATH)
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return
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log.warning(
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"blla model at %s is in an incompatible format — replacing", BLLA_MODEL_PATH
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)
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os.rename(BLLA_MODEL_PATH, BLLA_MODEL_PATH + ".incompatible")
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os.makedirs(os.path.dirname(BLLA_MODEL_PATH), exist_ok=True)
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downloaded = _download_blla()
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shutil.copy2(downloaded, BLLA_MODEL_PATH)
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log.info("Installed blla model at %s", BLLA_MODEL_PATH)
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if __name__ == "__main__":
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main()
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