import cv2 import insightface import onnxruntime as ort from insightface.app import FaceAnalysis class FaceSwapper: def __init__(self, model_name: str = "buffalo_l", det_size=(640, 640)): self.providers = self._resolve_providers() self.app = FaceAnalysis(name=model_name, providers=self.providers) ctx_id = 0 if "CUDAExecutionProvider" in self.providers else -1 self.app.prepare(ctx_id=ctx_id, det_size=det_size) self.swapper = insightface.model_zoo.get_model( "inswapper_128.onnx", download=True, download_zip=True, providers=self.providers, ) @staticmethod def _resolve_providers(): available = ort.get_available_providers() if "CUDAExecutionProvider" in available: return ["CUDAExecutionProvider", "CPUExecutionProvider"] return ["CPUExecutionProvider"] def swap_faces(self, source_path, source_face_idx, target_path, target_face_idx): source_img = cv2.imread(source_path) target_img = cv2.imread(target_path) if source_img is None or target_img is None: raise ValueError("Could not read one or both images") source_faces = sorted(self.app.get(source_img), key=lambda x: x.bbox[0]) target_faces = sorted(self.app.get(target_img), key=lambda x: x.bbox[0]) if len(source_faces) < source_face_idx or source_face_idx < 1: raise ValueError(f"Source image contains {len(source_faces)} faces, but requested face {source_face_idx}") if len(target_faces) < target_face_idx or target_face_idx < 1: raise ValueError(f"Target image contains {len(target_faces)} faces, but requested face {target_face_idx}") source_face = source_faces[source_face_idx - 1] target_face = target_faces[target_face_idx - 1] return self.swapper.get(target_img, target_face, source_face, paste_back=True) def count_faces(self, img_path): img = cv2.imread(img_path) if img is None: raise ValueError(f"Could not read image: {img_path}") return len(self.app.get(img))