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Merge pull request #324 from s0md3v/next-polishing

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Next polishing
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Henry Ruhs 2023-06-04 19:08:14 +02:00 committed by GitHub
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5 changed files with 73 additions and 71 deletions
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10
README.md
View File

@ -45,12 +45,12 @@ options:
--all-faces swap all faces in frame
--max-memory MAX_MEMORY
maximum amount of RAM in GB to be used
--cpu-threads CPU_THREADS
number of threads to be use for CPU mode
--cpu-cores CPU_CORES
number of CPU cores to use
--gpu-threads GPU_THREADS
number of threads to be use for GPU moded
--gpu-vendor {amd,intel,nvidia}
choice your gpu vendor
number of threads to be use for the GPU
--gpu-vendor {apple,amd,intel,nvidia}
choice your GPU vendor
```
Looking for a CLI mode? Using the -f/--face argument will make the program in cli mode.

5
requirements.txt
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@ -1,3 +1,5 @@
--extra-index-url https://download.pytorch.org/whl/cu118
numpy==1.23.5
opencv-python==4.7.0.72
onnx==1.14.0
@ -5,7 +7,7 @@ insightface==0.7.3
psutil==5.9.5
tk==0.1.0
pillow==9.5.0
torch==2.0.1
torch==2.0.1+cu118
onnxruntime==1.15.0; sys_platform == 'darwin' and platform_machine != 'arm64'
onnxruntime-silicon==1.13.1; sys_platform == 'darwin' and platform_machine == 'arm64'
onnxruntime-gpu==1.15.0; sys_platform != 'darwin'
@ -13,5 +15,4 @@ tensorflow==2.13.0rc1; sys_platform == 'darwin'
tensorflow==2.12.0; sys_platform != 'darwin'
opennsfw2==0.10.2
protobuf==4.23.2
pynvml==11.5.0
tqdm==4.65.0

115
roop/core.py
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@ -2,6 +2,9 @@
import os
import sys
# single thread doubles performance of gpu-mode - needs to be set before torch import
if any(arg.startswith('--gpu-vendor=') for arg in sys.argv):
os.environ['OMP_NUM_THREADS'] = '1'
import platform
import signal
import shutil
@ -20,7 +23,6 @@ from roop.utils import is_img, detect_fps, set_fps, create_video, add_audio, ext
from roop.analyser import get_face_single
import roop.ui as ui
signal.signal(signal.SIGINT, lambda signal_number, frame: quit())
parser = argparse.ArgumentParser()
parser.add_argument('-f', '--face', help='use this face', dest='source_img')
@ -30,26 +32,31 @@ parser.add_argument('--keep-fps', help='maintain original fps', dest='keep_fps',
parser.add_argument('--keep-frames', help='keep frames directory', dest='keep_frames', action='store_true', default=False)
parser.add_argument('--all-faces', help='swap all faces in frame', dest='all_faces', action='store_true', default=False)
parser.add_argument('--max-memory', help='maximum amount of RAM in GB to be used', dest='max_memory', type=int)
parser.add_argument('--max-cores', help='number of cores to use at max', dest='max_cores', type=int, default=max(psutil.cpu_count() - 2, 2))
parser.add_argument('--gpu-threads', help='number of threads to be use for GPU mode', dest='gpu_threads', type=int, default=4)
parser.add_argument('--gpu-vendor', help='choice your gpu vendor', dest='gpu_vendor', choices=['apple', 'amd', 'intel', 'nvidia'])
parser.add_argument('--cpu-cores', help='number of CPU cores to use', dest='cpu_cores', type=int, default=max(psutil.cpu_count() / 2, 2))
parser.add_argument('--gpu-threads', help='number of threads to be use for the GPU', dest='gpu_threads', type=int, default=4)
parser.add_argument('--gpu-vendor', help='choice your GPU vendor', dest='gpu_vendor', choices=['apple', 'amd', 'intel', 'nvidia'])
args = {}
for name, value in vars(parser.parse_args()).items():
args[name] = value
args = parser.parse_known_args()[0]
if 'all_faces' in args:
roop.globals.all_faces = True
if args['max_cores']:
roop.globals.max_cores = args['max_cores']
if args.cpu_cores:
roop.globals.cpu_cores = int(args.cpu_cores)
if args['gpu_threads']:
roop.globals.gpu_threads = args['gpu_threads']
# cpu thread fix for mac
if sys.platform == 'darwin':
roop.globals.cpu_cores = 1
if args['gpu_vendor']:
roop.globals.gpu_vendor = args['gpu_vendor']
if args.gpu_threads:
roop.globals.gpu_threads = int(args.gpu_threads)
# gpu thread fix for amd
if args.gpu_vendor == 'amd':
roop.globals.gpu_threads = 1
if args.gpu_vendor:
roop.globals.gpu_vendor = args.gpu_vendor
else:
roop.globals.providers = ['CPUExecutionProvider']
@ -59,8 +66,8 @@ if os.name == "nt":
def limit_resources():
if args['max_memory']:
memory = args['max_memory'] * 1024 * 1024 * 1024
if args.max_memory:
memory = args.max_memory * 1024 * 1024 * 1024
if str(platform.system()).lower() == 'windows':
import ctypes
kernel32 = ctypes.windll.kernel32
@ -81,13 +88,13 @@ def pre_check():
if roop.globals.gpu_vendor == 'apple':
if 'CoreMLExecutionProvider' not in roop.globals.providers:
quit("You are using --gpu=apple flag but CoreML isn't available or properly installed on your system.")
elif roop.globals.gpu_vendor == 'amd':
if roop.globals.gpu_vendor == 'amd':
if 'ROCMExecutionProvider' not in roop.globals.providers:
quit("You are using --gpu=amd flag but ROCM isn't available or properly installed on your system.")
elif roop.globals.gpu_vendor == 'nvidia':
if roop.globals.gpu_vendor == 'nvidia':
CUDA_VERSION = torch.version.cuda
CUDNN_VERSION = torch.backends.cudnn.version()
if not torch.cuda.is_available() or not CUDA_VERSION:
if not torch.cuda.is_available():
quit("You are using --gpu=nvidia flag but CUDA isn't available or properly installed on your system.")
if CUDA_VERSION > '11.8':
quit(f"CUDA version {CUDA_VERSION} is not supported - please downgrade to 11.8")
@ -97,8 +104,6 @@ def pre_check():
quit(f"CUDNN version {CUDNN_VERSION} is not supported - please upgrade to 8.9.1")
if CUDNN_VERSION > 8910:
quit(f"CUDNN version {CUDNN_VERSION} is not supported - please downgrade to 8.9.1")
else:
roop.globals.providers = ['CPUExecutionProvider']
def get_video_frame(video_path, frame_number = 1):
@ -138,40 +143,40 @@ def status(string):
def process_video_multi_cores(source_img, frame_paths):
n = len(frame_paths) // roop.globals.max_cores
n = len(frame_paths) // roop.globals.cpu_cores
if n > 2:
processes = []
for i in range(0, len(frame_paths), n):
p = pool.apply_async(process_frames, args=(source_img, frame_paths[i:i+n],))
p = POOL.apply_async(process_video, args=(source_img, frame_paths[i:i + n],))
processes.append(p)
for p in processes:
p.get()
pool.close()
pool.join()
POOL.close()
POOL.join()
def start(preview_callback = None):
if not args['source_img'] or not os.path.isfile(args['source_img']):
if not args.source_img or not os.path.isfile(args.source_img):
print("\n[WARNING] Please select an image containing a face.")
return
elif not args['target_path'] or not os.path.isfile(args['target_path']):
elif not args.target_path or not os.path.isfile(args.target_path):
print("\n[WARNING] Please select a video/image to swap face in.")
return
if not args['output_file']:
target_path = args['target_path']
args['output_file'] = rreplace(target_path, "/", "/swapped-", 1) if "/" in target_path else "swapped-" + target_path
target_path = args['target_path']
test_face = get_face_single(cv2.imread(args['source_img']))
if not args.output_file:
target_path = args.target_path
args.output_file = rreplace(target_path, "/", "/swapped-", 1) if "/" in target_path else "swapped-" + target_path
target_path = args.target_path
test_face = get_face_single(cv2.imread(args.source_img))
if not test_face:
print("\n[WARNING] No face detected in source image. Please try with another one.\n")
return
if is_img(target_path):
if predict_image(target_path) > 0.85:
quit()
process_img(args['source_img'], target_path, args['output_file'])
process_img(args.source_img, target_path, args.output_file)
status("swap successful!")
return
seconds, probabilities = predict_video_frames(video_path=args['target_path'], frame_interval=100)
seconds, probabilities = predict_video_frames(video_path=args.target_path, frame_interval=100)
if any(probability > 0.85 for probability in probabilities):
quit()
video_name_full = target_path.split("/")[-1]
@ -180,7 +185,7 @@ def start(preview_callback = None):
Path(output_dir).mkdir(exist_ok=True)
status("detecting video's FPS...")
fps, exact_fps = detect_fps(target_path)
if not args['keep_fps'] and fps > 30:
if not args.keep_fps and fps > 30:
this_path = output_dir + "/" + video_name + ".mp4"
set_fps(target_path, this_path, 30)
target_path, exact_fps = this_path, 30
@ -188,33 +193,33 @@ def start(preview_callback = None):
shutil.copy(target_path, output_dir)
status("extracting frames...")
extract_frames(target_path, output_dir)
args['frame_paths'] = tuple(sorted(
args.frame_paths = tuple(sorted(
glob.glob(output_dir + "/*.png"),
key=lambda x: int(x.split(sep)[-1].replace(".png", ""))
))
status("swapping in progress...")
if sys.platform != 'darwin' and not args['gpu_vendor']:
global pool
pool = mp.Pool(roop.globals.max_cores)
process_video_multi_cores(args['source_img'], args['frame_paths'])
if roop.globals.gpu_vendor is None and roop.globals.cpu_cores > 0:
global POOL
POOL = mp.Pool(roop.globals.cpu_cores)
process_video_multi_cores(args.source_img, args.frame_paths)
else:
process_video(args['source_img'], args["frame_paths"], preview_callback)
process_video(args.source_img, args.frame_paths)
status("creating video...")
create_video(video_name, exact_fps, output_dir)
status("adding audio...")
add_audio(output_dir, target_path, video_name_full, args['keep_frames'], args['output_file'])
save_path = args['output_file'] if args['output_file'] else output_dir + "/" + video_name + ".mp4"
add_audio(output_dir, target_path, video_name_full, args.keep_frames, args.output_file)
save_path = args.output_file if args.output_file else output_dir + "/" + video_name + ".mp4"
print("\n\nVideo saved as:", save_path, "\n\n")
status("swap successful!")
def select_face_handler(path: str):
args['source_img'] = path
args.source_img = path
def select_target_handler(path: str):
args['target_path'] = path
return preview_video(args['target_path'])
args.target_path = path
return preview_video(args.target_path)
def toggle_all_faces_handler(value: int):
@ -222,21 +227,21 @@ def toggle_all_faces_handler(value: int):
def toggle_fps_limit_handler(value: int):
args['keep_fps'] = int(value != 1)
args.keep_fps = int(value != 1)
def toggle_keep_frames_handler(value: int):
args['keep_frames'] = value
args.keep_frames = value
def save_file_handler(path: str):
args['output_file'] = path
args.output_file = path
def create_test_preview(frame_number):
return process_faces(
get_face_single(cv2.imread(args['source_img'])),
get_video_frame(args['target_path'], frame_number)
get_face_single(cv2.imread(args.source_img)),
get_video_frame(args.target_path, frame_number)
)
@ -245,16 +250,16 @@ def run():
pre_check()
limit_resources()
if args['source_img']:
args['cli_mode'] = True
if args.source_img:
args.cli_mode = True
start()
quit()
window = ui.init(
{
'all_faces': roop.globals.all_faces,
'keep_fps': args['keep_fps'],
'keep_frames': args['keep_frames']
'keep_fps': args.keep_fps,
'keep_frames': args.keep_frames
},
select_face_handler,
select_target_handler,

2
roop/globals.py
View File

@ -2,7 +2,7 @@ import onnxruntime
all_faces = None
log_level = 'error'
cpu_threads = None
cpu_cores = None
gpu_threads = None
gpu_vendor = None
providers = onnxruntime.get_available_providers()

12
roop/swapper.py
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@ -53,15 +53,11 @@ def process_frames(source_img, frame_paths, progress=None):
def multi_process_frame(source_img, frame_paths, progress):
# caculate the number of frames each threads processed
threads = []
num_threads = roop.globals.gpu_threads
num_frames_per_thread = len(frame_paths) // num_threads
remaining_frames = len(frame_paths) % num_threads
# initialize thread list
threads = []
# create thread and launch
start_index = 0
for _ in range(num_threads):
@ -89,10 +85,10 @@ def process_img(source_img, target_path, output_file):
print("\n\nImage saved as:", output_file, "\n\n")
def process_video(source_img, frame_paths, preview_callback):
def process_video(source_img, frame_paths):
progress_bar_format = '{l_bar}{bar}| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, {rate_fmt}{postfix}]'
with tqdm(total=len(frame_paths), desc="Processing", unit="frame", dynamic_ncols=True, bar_format=progress_bar_format) as progress:
if roop.globals.gpu_vendor == "nvidia": # multi-threading breaks in AMD
if roop.globals.gpu_vendor is not None and roop.globals.gpu_threads > 0:
multi_process_frame(source_img, frame_paths, progress)
else:
process_frames(source_img, frame_paths, progress)