nodes/SayanoAI-Comfy-RVC
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added bs roformer uvr + fixed caching

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SayanoAI
2024-06-01 14:44:06 -04:00
parent 029a388f17
commit af4371064e
6 changed files with 59 additions and 35 deletions
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custom_nodes/loaders.py
-1
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@@ -246,7 +246,6 @@ class LoadAudio:
sr = None if sr=="None" else int(sr)
audio = load_input_audio(audio_path,sr=sr)
return {"ui": {"preview": [{"filename": audio_name, "type": "input", "widgetId": widgetId}]}, "result": (audio_name, lambda:audio_to_bytes(*audio))}
# return (audio_name,lambda:audio_to_bytes(*audio))
@classmethod
def IS_CHANGED(cls, audio):
custom_nodes/rvc.py
+6 -5
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@@ -10,6 +10,7 @@ from ..lib import BASE_CACHE_DIR, BASE_MODELS_DIR
input_path = folder_paths.get_input_directory()
temp_path = folder_paths.get_temp_directory()
cache_dir = os.path.join(BASE_CACHE_DIR,"rvc")
# output_path = folder_paths.get_output_directory()
# base_path = os.path.dirname(input_path)
node_path = os.path.join(BASE_MODELS_DIR,"custom_nodes/ComfyUI-UVR5")
@@ -39,11 +40,11 @@ class RVCNode:
"step": 1, #Slider's step
"display": "slider"
}),
},
"optional": {
"format":(["wav", "flac", "mp3"],{
"default": "flac"
}),
},
"optional": {
"use_cache": ("BOOLEAN",{"default": True})
}
}
@@ -56,15 +57,15 @@ class RVCNode:
CATEGORY = "🌺RVC-Studio/rvc"
def convert(self, audio, model, hubert_model, pitch_extraction_params, format, use_cache=True, **kwargs):
def convert(self, audio, model, hubert_model, pitch_extraction_params, f0_up_key, format="flac", use_cache=True):
widgetId = get_hash(audio(), model, *pitch_extraction_params.items())
widgetId = get_hash(audio(), model, f0_up_key, *pitch_extraction_params.items())
cache_name = os.path.join(BASE_CACHE_DIR,"rvc",f"{widgetId}.{format}")
if use_cache and os.path.isfile(cache_name): output_audio = load_input_audio(cache_name)
else:
input_audio = bytes_to_audio(audio())
output_audio = vc_single(hubert_model=hubert_model(),input_audio=input_audio,**model(),**pitch_extraction_params,**kwargs)
output_audio = vc_single(hubert_model=hubert_model(),input_audio=input_audio,f0_up_key=f0_up_key,**model(),**pitch_extraction_params)
print(save_input_audio(cache_name, output_audio))
tempdir = os.path.join(temp_path,"preview")
custom_nodes/settings/downloader.py
+1 -1
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@@ -10,7 +10,7 @@ from ...lib import BASE_CACHE_DIR, BASE_MODELS_DIR
RVC_DOWNLOAD_LINK = 'https://huggingface.co/datasets/SayanoAI/RVC-Studio/resolve/main/'
MDX_MODELS = ["MDXNET/UVR-MDX-NET-vocal_FT.onnx"]
KARAFAN_MODELS = ["karafan/MDX23C-8KFFT-InstVoc_HQ.ckpt"]
VR_MODELS = ["UVR/UVR-DeEcho-DeReverb.pth","UVR/HP5-vocals+instrumentals.pth","UVR/5_HP-Karaoke-UVR.pth"]
VR_MODELS = ["UVR/UVR-DeEcho-DeReverb.pth","UVR/HP5-vocals+instrumentals.pth","UVR/5_HP-Karaoke-UVR.pth","UVR/model_bs_roformer_ep_317_sdr_12.9755.ckpt"]
RVC_MODELS = [
"RVC/Claire.pth",
"RVC/Sayano.pth",
custom_nodes/uvr.py
+47 -22
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@@ -1,8 +1,8 @@
import os
from ..lib.audio import audio_to_bytes, bytes_to_audio, save_input_audio
from ..lib.audio import audio_to_bytes, bytes_to_audio, save_input_audio, load_input_audio
import folder_paths
from ..lib.utils import get_filenames, get_hash, get_optimal_torch_device
from ..lib.utils import get_filenames, get_hash, get_file_hash, get_optimal_torch_device
from ..lib import BASE_CACHE_DIR, BASE_MODELS_DIR, karafan
from ..uvr5_cli import Separator
from .settings.downloader import KARAFAN_MODELS, MDX_MODELS, RVC_DOWNLOAD_LINK, VR_MODELS, download_file
@@ -20,7 +20,7 @@ class UVR5Node:
@classmethod
def INPUT_TYPES(cls):
model_list = MDX_MODELS + VR_MODELS + KARAFAN_MODELS + get_filenames(root=BASE_MODELS_DIR,format_func=lambda x: f"{os.path.basename(os.path.dirname(x))}/{os.path.basename(x)}",name_filters=["UVR","MDXNET","karafan"])
model_list = MDX_MODELS + VR_MODELS + KARAFAN_MODELS + get_filenames(root=BASE_MODELS_DIR,format_func=lambda x: f"{os.path.basename(os.path.dirname(x))}/{os.path.basename(x)}",name_filters=["UVR","MDX","karafan"])
model_list = list(set(model_list)) # dedupe
return {
@@ -29,6 +29,9 @@ class UVR5Node:
"model": (model_list,{
"default": "UVR/HP5-vocals+instrumentals.pth"
}),
},
"optional": {
"use_cache": ("BOOLEAN",{"default": True}),
"agg":("INT",{
"default": 10,
"min": 0, #Minimum value
@@ -39,9 +42,6 @@ class UVR5Node:
"format":(["wav", "flac", "mp3"],{
"default": "flac"
}),
},
"optional": {
"use_cache": ("BOOLEAN",{"default": True})
}
}
@@ -52,7 +52,7 @@ class UVR5Node:
CATEGORY = "🌺RVC-Studio/uvr"
def split(self, audio, model, **kwargs):
def split(self, audio, model, use_cache=True, agg=10, format='flac'):
filename = os.path.basename(model)
subfolder = os.path.dirname(model)
model_path = os.path.join(BASE_MODELS_DIR,subfolder,filename)
@@ -62,22 +62,47 @@ class UVR5Node:
if download_file(params): print(f"successfully downloaded: {model_path}")
input_audio = bytes_to_audio(audio())
audio_path = os.path.join(temp_path,"uvr",f"{get_hash(audio(),model, *kwargs.items())}.wav")
if not os.path.isfile(audio_path):
os.makedirs(os.path.dirname(audio_path),exist_ok=True)
print(save_input_audio(audio_path,input_audio))
if "karafan" in model_path:
vocals, instrumental, input_audio = karafan.inference.Process(audio_path,cache_dir=cache_dir,**kwargs)
hash_name = get_hash(audio(), model, agg, format)
audio_path = os.path.join(temp_path,"uvr",f"{hash_name}.wav")
vocal_path = os.path.join(cache_dir,hash_name,f"primary.{format}")
instrumental_path = os.path.join(cache_dir,hash_name,f"secondary.{format}")
if os.path.isfile(vocal_path) and os.path.isfile(instrumental_path) and use_cache:
vocals = load_input_audio(vocal_path)
instrumental = load_input_audio(instrumental_path)
else:
model = Separator(
model_path=model_path,
device=device,
is_half="cuda" in str(device),
cache_dir=cache_dir,
**kwargs
)
vocals, instrumental, input_audio = model.run_inference(audio_path,format=kwargs.get("format"))
if not os.path.isfile(audio_path):
os.makedirs(os.path.dirname(audio_path),exist_ok=True)
print(save_input_audio(audio_path,input_audio))
vocals=instrumental=None
try: # try original RVC implementation
model = Separator(
model_path=model_path,
device=device,
is_half="cuda" in str(device),
cache_dir=cache_dir,
agg=agg
)
vocals, instrumental, input_audio = model.run_inference(audio_path,format=format)
except Exception as e:
print(f"Error: {e}")
if "karafan" in model_path: # try karafan implementation
vocals, instrumental, input_audio = karafan.inference.Process(audio_path,cache_dir=temp_path,format=format)
else: # try python-audio-separator implementation
import audio_separator.separator as uvr
model_dir = os.path.dirname(model_path)
model_name = os.path.basename(model_path)
vr_params={"batch_size": 4, "window_size": 512, "aggression": agg, "enable_tta": False, "enable_post_process": False, "post_process_threshold": 0.2, "high_end_process": "mirroring"}
model = uvr.Separator(model_file_dir=os.path.join(BASE_MODELS_DIR,model_dir),output_dir=temp_path,output_format=format,vr_params=vr_params)
model.load_model(model_name)
output_files = model.separate(audio_path)
print(f"{output_files=}")
vocals = load_input_audio(os.path.join(temp_path,output_files[0]))
instrumental = load_input_audio(os.path.join(temp_path,output_files[1]))
finally:
if vocals is not None and instrumental is not None and use_cache:
print(save_input_audio(vocal_path,vocals))
print(save_input_audio(instrumental_path,instrumental))
return (lambda:audio_to_bytes(*vocals), lambda:audio_to_bytes(*instrumental), audio)
lib/utils.py
+4 -4
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@@ -19,9 +19,9 @@ CWD = get_cwd()
def get_hash(*args):
return hashlib.md5("".join(str(data) for data in args).encode()).hexdigest()
def get_file_hash(fname,size=10*1024**2):
if hasattr(fname,"read"):
with open(fname,"rb") as f: return hashlib.md5(f.read(-size)).hexdigest()
def get_file_hash(fname: str, size=10*1024**2):
with open(fname,"rb") as f:
return hashlib.md5(f.read(size)).hexdigest()
def get_subprocesses(pid = os.getpid()):
# Get a list of all subprocesses started by the current process
@@ -45,7 +45,7 @@ def get_filenames(root=CWD,folder="**",exts=["*"],name_filters=[""],filter_func=
fnames = []
for ext in exts:
fnames.extend(glob.glob(f"{root}/{folder}/*.{ext}",recursive=True))
return sorted([format_func(ele) for ele in fnames if filter_func([nf.lower() in os.path.basename(ele).lower() for nf in name_filters])])
return sorted([format_func(ele) for ele in fnames if filter_func([nf.lower() in ele.lower() for nf in name_filters])])
def get_index(arr,value):
if arr is not None:
requirements.txt
+1 -2
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@@ -5,10 +5,9 @@ faiss-cpu
ffmpeg-python
tqdm
audioread
audio-separator[gpu]
onnxruntime-gpu
onnxruntime
ffmpy
accelerate
samplerate
pyaudio
spacy