37 lines
1.4 KiB
Python
37 lines
1.4 KiB
Python
"""Shared loader for the sae_embed nanobind module (SCRFD + ArcFace).
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sae_embed.FaceEmbedder loads both ONNX sessions once and exposes an
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embed(path) -> FaceResult method, avoiding the per-process model reload cost
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of spawning the embed_faces CLI binary for every image.
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"""
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import sys
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from pathlib import Path
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def load_embedder(build_dir: str, models_dir: str, arcface: str | None = None,
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conf: float = 0.5, nms: float = 0.4, max_side: int = 500):
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"""Import sae_embed from build_dir and construct a FaceEmbedder.
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Exits with a clear error if the module or models are missing — there is
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no subprocess fallback.
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"""
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build_path = Path(build_dir).resolve()
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sys.path.insert(0, str(build_path))
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try:
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import sae_embed
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except ImportError as e:
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sys.exit(
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f"sae_embed module not found in {build_path}: {e}\n"
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f"Build it first: cmake --build {build_dir} --target sae_embed"
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)
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models_path = Path(models_dir)
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detector_path = str(models_path / "scrfd_500m_bnkps.onnx")
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arcface_path = arcface if arcface else str(models_path / "arcface_w600k_r50.onnx")
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for model, name in [(detector_path, "SCRFD"), (arcface_path, "ArcFace")]:
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if not Path(model).is_file():
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sys.exit(f"{name} model not found: {model}\nRun: bash scripts/download_models.sh")
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return sae_embed.FaceEmbedder(detector_path, arcface_path, conf, nms, max_side)
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