| import cv2 |
| import insightface |
| from insightface.app import FaceAnalysis |
| import os |
|
|
| class FaceSwapper: |
| def __init__(self): |
| |
| self.app = FaceAnalysis( |
| name='buffalo_l', |
| providers=['CUDAExecutionProvider', 'CPUExecutionProvider'] |
| ) |
| self.app.prepare(ctx_id=0, det_size=(640, 640)) |
| |
| self.swapper = insightface.model_zoo.get_model( |
| 'inswapper_128.onnx', |
| download=True, |
| download_zip=True |
| ) |
| print("✅ FaceSwapper initialized with GPU support") |
|
|
| 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 = self.app.get(source_img) |
| target_faces = self.app.get(target_img) |
|
|
| source_faces = sorted(source_faces, key=lambda x: x.bbox[0]) |
| target_faces = sorted(target_faces, 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] |
|
|
| result = self.swapper.get(target_img, target_face, source_face, paste_back=True) |
| return result |
