import gradio as gr import insightface from insightface.app import FaceAnalysis wellcomingMessage = """

Face Swapping by Suraj Yadav

""" assert insightface.__version__>='0.7' value = 0 app = FaceAnalysis(name='buffalo_l') app.prepare(ctx_id=0, det_size=(640, 640)) swapper = insightface.model_zoo.get_model('inswapper_128.onnx', download=True, download_zip=True) def swap_faces(faceSource, sourceFaceId, faceDestination, destFaceId): faces = app.get(faceSource) faces = sorted(faces, key = lambda x : x.bbox[0]) if len(faces) < sourceFaceId or sourceFaceId < 1: raise gr.Error(f"Source image only contains {len(faces)} faces, but you requested face {sourceFaceId}") source_face = faces[sourceFaceId-1] res_faces = app.get(faceDestination) res_faces = sorted(res_faces, key = lambda x : x.bbox[0]) if len(res_faces) < destFaceId or destFaceId < 1: raise gr.Error(f"Destination image only contains {len(res_faces)} faces, but you requested face {destFaceId}") res_face = res_faces[destFaceId-1] result = swapper.get(faceDestination, res_face, source_face, paste_back=True) global value value = value + 1 print(f"processed: {value}...") # for face in faces: # res = swapper.get(res, face, source_face, paste_back=True) # cv2.imwrite("./t1_swapped.jpg", res) return result gr.Interface(swap_faces, [ gr.Image(), gr.Number(precision=0, value=1, info='face position (from left, starting at 1)'), gr.Image(), gr.Number(precision=0, value=1, info='face position (from left, starting at 1)') ], gr.Image(), description=wellcomingMessage, title="Face Swap by Suraj Yadav", examples=[ ['./Images/kim.jpg', 1, './Images/marilyn.jpg', 1], ['./Images/friends.jpg', 2, './Images/friends.jpg', 1], ], ).launch()