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| """Thin wrapper around InsightFace's FaceAnalysis (RetinaFace detector + ArcFace embedder). | |
| Intentionally duplicated from ../app/face_engine.py: this folder is a separate, | |
| self-contained deployable (Hugging Face Spaces web demo) with its own | |
| requirements.txt (headless OpenCV, no GUI deps) and its own tuning defaults for | |
| a shared/free CPU, independent of the NUC/local app in ../app. | |
| """ | |
| from typing import List, Optional, Tuple | |
| import numpy as np | |
| import onnxruntime | |
| from insightface.app import FaceAnalysis | |
| from insightface.app.common import Face | |
| # We only ever read .bbox, .det_score, .normed_embedding, so the landmark_3d_68, | |
| # landmark_2d_106 and genderage models are pure overhead: excluding them via | |
| # allowed_modules skips loading AND running 3 extra ONNX forward passes per face. | |
| _REQUIRED_MODULES = ["detection", "recognition"] | |
| class FaceEngine: | |
| """Detects faces and produces L2-normalized 512-d ArcFace embeddings.""" | |
| def __init__( | |
| self, | |
| det_size: Tuple[int, int] = (320, 320), | |
| ctx_id: int = -1, | |
| model_name: str = "buffalo_s", | |
| num_threads: Optional[int] = None, | |
| ) -> None: | |
| # ctx_id=-1 -> CPUExecutionProvider only; ctx_id>=0 -> CUDAExecutionProvider device id. | |
| providers = ["CPUExecutionProvider"] if ctx_id < 0 else ["CUDAExecutionProvider", "CPUExecutionProvider"] | |
| sess_options = None | |
| if num_threads is not None and num_threads > 0: | |
| sess_options = onnxruntime.SessionOptions() | |
| sess_options.intra_op_num_threads = num_threads | |
| sess_options.inter_op_num_threads = 1 | |
| self.app = FaceAnalysis( | |
| name=model_name, | |
| providers=providers, | |
| allowed_modules=_REQUIRED_MODULES, | |
| sess_options=sess_options, | |
| ) | |
| self.app.prepare(ctx_id=ctx_id, det_size=det_size) | |
| def detect(self, frame_bgr: np.ndarray) -> List[Face]: | |
| """Returns InsightFace Face objects with .bbox, .det_score, .normed_embedding (512-d, L2-normed).""" | |
| return self.app.get(frame_bgr) | |