Normalize ARGS
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henryruhs
parent
b116f2001a
commit
4420ba5bdd
92
roop/core.py
92
roop/core.py
@ -24,47 +24,46 @@ from roop.utils import is_img, detect_fps, set_fps, create_video, add_audio, ext
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from roop.analyser import get_face_single
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import roop.ui as ui
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signal.signal(signal.SIGINT, lambda signal_number, frame: quit())
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parser = argparse.ArgumentParser()
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parser.add_argument('-f', '--face', help='use this face', dest='source_img')
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parser.add_argument('-t', '--target', help='replace this face', dest='target_path')
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parser.add_argument('-o', '--output', help='save output to this file', dest='output_file')
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parser.add_argument('--keep-fps', help='maintain original fps', dest='keep_fps', action='store_true', default=False)
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parser.add_argument('--keep-frames', help='keep frames directory', dest='keep_frames', action='store_true', default=False)
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parser.add_argument('--all-faces', help='swap all faces in frame', dest='all_faces', action='store_true', default=False)
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parser.add_argument('--max-memory', help='maximum amount of RAM in GB to be used', dest='max_memory', type=int)
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parser.add_argument('--cpu-cores', help='number of CPU cores to use', dest='cpu_cores', type=int, default=max(psutil.cpu_count() / 2, 1))
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parser.add_argument('--gpu-threads', help='number of threads to be use for the GPU', dest='gpu_threads', type=int, default=8)
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parser.add_argument('--gpu-vendor', help='choice your GPU vendor', dest='gpu_vendor', choices=['apple', 'amd', 'intel', 'nvidia'])
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args = parser.parse_known_args()[0]
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def handle_parse():
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global args
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signal.signal(signal.SIGINT, lambda signal_number, frame: quit())
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parser = argparse.ArgumentParser()
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parser.add_argument('-f', '--face', help='use this face', dest='source_target')
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parser.add_argument('-t', '--target', help='replace this face', dest='target_path')
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parser.add_argument('-o', '--output', help='save output to this file', dest='output_path')
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parser.add_argument('--keep-fps', help='maintain original fps', dest='keep_fps', action='store_true', default=False)
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parser.add_argument('--keep-frames', help='keep frames directory', dest='keep_frames', action='store_true', default=False)
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parser.add_argument('--all-faces', help='swap all faces in frame', dest='all_faces', action='store_true', default=False)
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parser.add_argument('--max-memory', help='maximum amount of RAM in GB to be used', dest='max_memory', type=int)
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parser.add_argument('--cpu-cores', help='number of CPU cores to use', dest='cpu_cores', type=int, default=max(psutil.cpu_count() / 2, 1))
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parser.add_argument('--gpu-threads', help='number of threads to be use for the GPU', dest='gpu_threads', type=int, default=8)
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parser.add_argument('--gpu-vendor', help='choice your GPU vendor', dest='gpu_vendor', choices=['apple', 'amd', 'intel', 'nvidia'])
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if 'all_faces' in args:
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roop.globals.all_faces = True
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args = parser.parse_known_args()[0]
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if args.cpu_cores:
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roop.globals.headless = args.source_target or args.target_path or args.output_path
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roop.globals.all_faces = args.all_faces
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if args.cpu_cores:
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roop.globals.cpu_cores = int(args.cpu_cores)
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# cpu thread fix for mac
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if sys.platform == 'darwin':
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# cpu thread fix for mac
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if sys.platform == 'darwin':
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roop.globals.cpu_cores = 1
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if args.gpu_threads:
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if args.gpu_threads:
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roop.globals.gpu_threads = int(args.gpu_threads)
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# gpu thread fix for amd
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if args.gpu_vendor == 'amd':
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# gpu thread fix for amd
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if args.gpu_vendor == 'amd':
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roop.globals.gpu_threads = 1
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if args.gpu_vendor:
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if args.gpu_vendor:
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roop.globals.gpu_vendor = args.gpu_vendor
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else:
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else:
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roop.globals.providers = ['CPUExecutionProvider']
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sep = "/"
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if os.name == "nt":
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sep = "\\"
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def limit_resources():
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# prevent tensorflow memory leak
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@ -141,18 +140,18 @@ def preview_video(video_path):
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def status(string):
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value = "Status: " + string
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if 'cli_mode' in args:
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if roop.globals.headless:
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print(value)
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else:
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ui.update_status_label(value)
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def process_video_multi_cores(source_img, frame_paths):
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def process_video_multi_cores(source_target, frame_paths):
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n = len(frame_paths) // roop.globals.cpu_cores
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if n > 2:
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processes = []
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for i in range(0, len(frame_paths), n):
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p = POOL.apply_async(process_video, args=(source_img, frame_paths[i:i + n],))
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p = POOL.apply_async(process_video, args=(source_target, frame_paths[i:i + n],))
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processes.append(p)
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for p in processes:
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p.get()
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@ -161,24 +160,24 @@ def process_video_multi_cores(source_img, frame_paths):
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def start(preview_callback = None):
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if not args.source_img or not os.path.isfile(args.source_img):
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if not args.source_target or not os.path.isfile(args.source_target):
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print("\n[WARNING] Please select an image containing a face.")
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return
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elif not args.target_path or not os.path.isfile(args.target_path):
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print("\n[WARNING] Please select a video/image to swap face in.")
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return
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if not args.output_file:
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if not args.output_path:
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target_path = args.target_path
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args.output_file = rreplace(target_path, "/", "/swapped-", 1) if "/" in target_path else "swapped-" + target_path
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args.output_path = rreplace(target_path, "/", "/swapped-", 1) if "/" in target_path else "swapped-" + target_path
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target_path = args.target_path
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test_face = get_face_single(cv2.imread(args.source_img))
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test_face = get_face_single(cv2.imread(args.source_target))
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if not test_face:
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print("\n[WARNING] No face detected in source image. Please try with another one.\n")
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return
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if is_img(target_path):
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if predict_image(target_path) > 0.85:
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quit()
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process_img(args.source_img, target_path, args.output_file)
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process_img(args.source_target, target_path, args.output_path)
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status("swap successful!")
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return
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seconds, probabilities = predict_video_frames(video_path=args.target_path, frame_interval=100)
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@ -200,29 +199,29 @@ def start(preview_callback = None):
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extract_frames(target_path, output_dir)
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args.frame_paths = tuple(sorted(
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glob.glob(output_dir + "/*.png"),
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key=lambda x: int(x.split(sep)[-1].replace(".png", ""))
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key=lambda x: int(x.split(os.sep)[-1].replace(".png", ""))
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))
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status("swapping in progress...")
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if roop.globals.gpu_vendor is None and roop.globals.cpu_cores > 1:
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global POOL
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POOL = mp.Pool(roop.globals.cpu_cores)
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process_video_multi_cores(args.source_img, args.frame_paths)
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process_video_multi_cores(args.source_target, args.frame_paths)
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else:
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process_video(args.source_img, args.frame_paths)
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process_video(args.source_target, args.frame_paths)
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# prevent out of memory while using ffmpeg with cuda
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if args.gpu_vendor == 'nvidia':
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torch.cuda.empty_cache()
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status("creating video...")
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create_video(video_name, exact_fps, output_dir)
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status("adding audio...")
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add_audio(output_dir, target_path, video_name_full, args.keep_frames, args.output_file)
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save_path = args.output_file if args.output_file else output_dir + "/" + video_name + ".mp4"
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add_audio(output_dir, target_path, video_name_full, args.keep_frames, args.output_path)
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save_path = args.output_path if args.output_path else output_dir + "/" + video_name + ".mp4"
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print("\n\nVideo saved as:", save_path, "\n\n")
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status("swap successful!")
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def select_face_handler(path: str):
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args.source_img = path
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args.source_target = path
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def select_target_handler(path: str):
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@ -243,26 +242,24 @@ def toggle_keep_frames_handler(value: int):
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def save_file_handler(path: str):
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args.output_file = path
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args.output_path = path
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def create_test_preview(frame_number):
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return process_faces(
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get_face_single(cv2.imread(args.source_img)),
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get_face_single(cv2.imread(args.source_target)),
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get_video_frame(args.target_path, frame_number)
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)
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def run():
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global all_faces, keep_frames, limit_fps
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handle_parse()
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pre_check()
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limit_resources()
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if args.source_img:
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args.cli_mode = True
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if roop.globals.headless:
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start()
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quit()
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window = ui.init(
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{
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'all_faces': roop.globals.all_faces,
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@ -279,5 +276,4 @@ def run():
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get_video_frame,
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create_test_preview
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)
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window.mainloop()
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@ -5,6 +5,7 @@ log_level = 'error'
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cpu_cores = None
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gpu_threads = None
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gpu_vendor = None
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headless = None
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providers = onnxruntime.get_available_providers()
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if 'TensorrtExecutionProvider' in providers:
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