# -*- coding:UTF-8 -*- # !/usr/bin/env python import spaces import numpy as np import gradio as gr import gradio.exceptions import roop.globals from roop.core import ( start, decode_execution_providers, ) from roop.processors.frame.core import get_frame_processors_modules from roop.utilities import normalize_output_path import os from PIL import Image import uuid import onnxruntime as ort import cv2 from roop.face_analyser import get_one_face from cryptography.hazmat.primitives.asymmetric import rsa, padding from cryptography.hazmat.primitives import serialization, hashes from cryptography.hazmat.backends import default_backend from cryptography.hazmat.primitives.asymmetric import utils import base64 import json import datetime def load_public_key_from_file(file_path): with open(file_path, "rb") as key_file: public_key = serialization.load_pem_public_key( key_file.read(), backend=default_backend() ) return public_key def verify_signature(public_key, data, signature): """ Verify a signature with a public key. Converts the data to bytes if it's not already in byte format. """ # Ensure the data is in bytes. If it's a string, encode it to UTF-8. if isinstance(data, str): data = data.encode('utf-8') try: # Verify the signature public_key.verify( signature, data, padding.PSS( mgf=padding.MGF1(hashes.SHA256()), salt_length=padding.PSS.MAX_LENGTH ), hashes.SHA256() ) return True except Exception as e: print("Verification failed:", e) return False public_key = load_public_key_from_file("./nsfwais.pubkey.pem") @spaces.GPU def swap_face(source_file, target_file, doFaceEnhancer, skey): skey = json.loads(skey) #first validate skey signature = base64.b64decode(skey["s"]) if not verify_signature(public_key, skey["t"], signature): raise Exception("verify authkey failed.") timestamp_requested = int(skey["t"]) timestamp_now = int(datetime.datetime.utcnow().replace(tzinfo=datetime.timezone.utc).timestamp()) if timestamp_now - timestamp_requested > 600: raise Exception(f"authkey timeout, {timestamp_now - timestamp_requested}") print(f"authkey pass, {timestamp_now - timestamp_requested}") session_id = str(uuid.uuid4()) # Tạo một UUID duy nhất cho mỗi phiên làm việc session_dir = f"temp/{session_id}" os.makedirs(session_dir, exist_ok=True) source_path = os.path.join(session_dir, "input.jpg") target_path = os.path.join(session_dir, "target.jpg") source_image = Image.fromarray(source_file) source_image.save(source_path) target_image = Image.fromarray(target_file) target_image.save(target_path) print("source_path: ", source_path) print("target_path: ", target_path) # Check if a face is detected in the source image source_face = get_one_face(cv2.imread(source_path)) if source_face is None: raise gradio.exceptions.Error("No face in source path detected.") # Check if a face is detected in the target image target_face = get_one_face(cv2.imread(target_path)) if target_face is None: raise gradio.exceptions.Error("No face in target path detected.") output_path = os.path.join(session_dir, "output.jpg") normalized_output_path = normalize_output_path(source_path, target_path, output_path) frame_processors = ["face_swapper", "face_enhancer"] if doFaceEnhancer else ["face_swapper"] for frame_processor in get_frame_processors_modules(frame_processors): if not frame_processor.pre_check(): print(f"Pre-check failed for {frame_processor}") raise gradio.exceptions.Error(f"Pre-check failed for {frame_processor}") roop.globals.source_path = source_path roop.globals.target_path = target_path roop.globals.output_path = normalized_output_path roop.globals.frame_processors = frame_processors roop.globals.headless = True roop.globals.keep_fps = True roop.globals.keep_audio = True roop.globals.keep_frames = False roop.globals.many_faces = False roop.globals.video_encoder = "libx264" roop.globals.video_quality = 18 roop.globals.execution_providers = ["CUDAExecutionProvider"] roop.globals.reference_face_position = 0 roop.globals.similar_face_distance = 0.6 roop.globals.max_memory = 60 roop.globals.execution_threads = 50 start() return normalized_output_path app = gr.Interface( fn=swap_face, inputs=[ gr.Image(), gr.Image(), gr.Checkbox(label="Face Enhancer?", info="Do face enhancement?"), gr.Textbox(visible=False) ], outputs="image" ) app.launch()