Fix GPU for NVIDIA

run.py

@@ -8,24 +8,24 @@ import glob
 import argparse
 import multiprocessing as mp
 import os
-import random
+import torch
 from pathlib import Path
 import tkinter as tk
 from tkinter import filedialog
 from opennsfw2 import predict_image as face_check
 from tkinter.filedialog import asksaveasfilename
-import core.globals
-from core.processor import process_video, process_img
-from core.utils import is_img, detect_fps, set_fps, create_video, add_audio, extract_frames, rreplace
-from core.config import get_face
 import webbrowser
 import psutil
 import cv2
 import threading
 from PIL import Image, ImageTk
+import core.globals
+from core.processor import process_video, process_img
+from core.utils import is_img, detect_fps, set_fps, create_video, add_audio, extract_frames, rreplace
+from core.config import get_face
 
-if 'ROCMExecutionProvider' not in core.globals.providers:
-    import torch
+if 'ROCMExecutionProvider' in core.globals.providers:
+    del torch
 
 pool = None
 args = {}
@@ -69,8 +69,7 @@ def pre_check():
     if not os.path.isfile(model_path):
         quit('File "inswapper_128.onnx" does not exist!')
     if '--gpu' in sys.argv:
-        NVIDIA_PROVIDERS = ['CUDAExecutionProvider', 'TensorrtExecutionProvider']
-        if len(list(set(core.globals.providers) - set(NVIDIA_PROVIDERS))) == 1:
+        if 'ROCMExecutionProvider' not in core.globals.providers:
             CUDA_VERSION = torch.version.cuda
             CUDNN_VERSION = torch.backends.cudnn.version()
             if not torch.cuda.is_available() or not CUDA_VERSION:
@@ -89,10 +88,6 @@ def pre_check():
 
 def start_processing():
     start_time = time.time()
-    threshold = len(['frame_args']) if len(args['frame_paths']) <= 10 else 10
-    for i in range(threshold):
-        if face_check(random.choice(args['frame_paths'])) > 0.8:
-            quit("[WARNING] Unable to determine location of the face in the target. Please make sure the target isn't wearing clothes matching to their skin.")
     if args['gpu']:
         process_video(args['source_img'], args["frame_paths"])
         end_time = time.time()