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feat: readjust model path
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@ArkanDash
ArkanDash committed Aug 19, 2023
1 parent 068189d commit 8cdde8d
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Showing 2 changed files with 95 additions and 106 deletions.
9 changes: 9 additions & 0 deletions .github/workflows/python-app.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -43,3 +43,12 @@ jobs:
sudo apt-get install -qq -y aria2
aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/hubert_base.pt -d /home/runner/work/Advanced-RVC-Inference/Advanced-RVC-Inference -o hubert_base.pt
aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/rmvpe.pt -d /home/runner/work/Advanced-RVC-Inference/Advanced-RVC-Inference -o rmvpe.pt
- name: Test application
run: |
python infer.py &
sleep 180
- name: Exit application
run: |
pkill -f infer.py || true
192 changes: 86 additions & 106 deletions infer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
import gdown
import subprocess
import wave
from scipy.io import wavfile
from datetime import datetime
from urllib.parse import urlparse
from mega import Mega
Expand Down Expand Up @@ -58,32 +59,32 @@ def load_hubert():
load_hubert()

weight_root = "weights"
weights_path = []
weights_file = []
for _, dirs, _ in os.walk(weight_root):
for sub_dirs in dirs:
if sub_dirs.startswith("."):
continue
weights_path.append(os.path.join(weight_root, sub_dirs))
for _, _, files in os.walk(os.path.join(weight_root, sub_dirs)):
for file in files:
if file.endswith(".pth"):
weights_file.append(file)
index_root = "weights/index"
weights_model = []
weights_index = []
for _, _, model_files in os.walk(weight_root):
for file in model_files:
if file.endswith(".pth"):
weights_model.append(file)
for _, _, index_files in os.walk(index_root):
for file in index_files:
if file.endswith('.index') and "trained" not in file:
weights_index.append(os.path.join(index_root, file))

def check_models():
weights_path = []
weights_file = []
for _, dirs, _ in os.walk(weight_root):
for sub_dirs in dirs:
if sub_dirs.startswith("."):
continue
weights_path.append(os.path.join(weight_root, sub_dirs))
for _, _, files in os.walk(os.path.join(weight_root, sub_dirs)):
for file in files:
if file.endswith(".pth"):
weights_file.append(file)
weights_model = []
weights_index = []
for _, _, model_files in os.walk(weight_root):
for file in model_files:
if file.endswith(".pth"):
weights_model.append(file)
for _, _, index_files in os.walk(index_root):
for file in index_files:
if file.endswith('.index') and "trained" not in file:
weights_index.append(os.path.join(index_root, file))
return (
gr.Dropdown.update(choices=sorted(weights_file), value=weights_file[0])
gr.Dropdown.update(choices=sorted(weights_model), value=weights_model[0]),
gr.Dropdown.update(choices=sorted(weights_index))
)

def clean():
Expand All @@ -104,7 +105,6 @@ def vc_single(
f0_file,
f0_method,
file_index,
# file_big_npy,
index_rate,
filter_radius,
resample_sr,
Expand Down Expand Up @@ -220,19 +220,12 @@ def get_vc(sid, to_return_protect0):
return (
gr.Slider.update(maximum=2333, visible=False),
gr.Slider.update(visible=True),
gr.Dropdown.update(choices=[], value=""),
gr.Markdown.update(value="# <cover> No model selected")
gr.Dropdown.update(choices=sorted(weights_index), value=""),
gr.Markdown.update(value="# <center> No model selected")
)
current_model = ""
current_model_path = ""
for i, path in enumerate(weights_path):
file_path = os.path.join(path, weights_file[i])
if os.path.exists(file_path) and sid[:-4] in file_path:
current_model = file_path
current_model_path = path
break
print(f"Loading {sid} model...")
cpt = torch.load(current_model, map_location="cpu")
selected_model = sid[:-4]
cpt = torch.load(os.path.join(weight_root, sid), map_location="cpu")
tgt_sr = cpt["config"][-1]
cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]
if_f0 = cpt.get("f0", 1)
Expand All @@ -249,19 +242,16 @@ def get_vc(sid, to_return_protect0):
"__type__": "update",
}
version = cpt.get("version", "v1")
model_version = "Unknown"
if version == "v1":
if if_f0 == 1:
net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=config.is_half)
else:
net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
model_version = "v1 Model"
elif version == "v2":
if if_f0 == 1:
net_g = SynthesizerTrnMs768NSFsid(*cpt["config"], is_half=config.is_half)
else:
net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
model_version = "v2 Model"
del net_g.enc_q
print(net_g.load_state_dict(cpt["weight"], strict=False))
net_g.eval().to(config.device)
Expand All @@ -270,27 +260,20 @@ def get_vc(sid, to_return_protect0):
else:
net_g = net_g.float()
vc = VC(tgt_sr, config)
n_spk = cpt["config"][-3]
index_list = []
cover = gr.Markdown.update(
f'## <center> {sid[:-4]}\n'+
f'### <center> RVC {model_version}'
)
for _, _, files in os.walk(current_model_path):
for file in files:
if file.endswith('.index') and "trained" not in file:
index_list.append(os.path.join(current_model_path, file))
if file.endswith('.png') or file.endswith('.jpg') or file.endswith('.gif'):
cover = gr.Markdown.update(
f'## <center> {sid[:-4]}\n'+
f'### <center> RVC {model_version}\n'+
f'<center><img style="width:auto;height:250px; display:block; margin:auto;" src="file/{os.path.join(current_model_path, file)}" align="center"></center>'
)
n_spk = cpt["config"][-3]
selected_index = gr.Dropdown.update(value=weights_index[0])
for index, model_index in enumerate(weights_index):
if selected_model in model_index:
selected_index = gr.Dropdown.update(value=weights_index[index])
break
return (
gr.Slider.update(maximum=n_spk, visible=True),
to_return_protect0,
gr.Dropdown.update(choices=sorted(index_list), value=index_list[0]),
cover
selected_index,
gr.Markdown.update(
f'## <center> {selected_model}\n'+
f'### <center> RVC {version} Model'
)
)

def download_audio(url, audio_provider):
Expand All @@ -310,9 +293,9 @@ def download_audio(url, audio_provider):
'key': 'FFmpegExtractAudio',
'preferredcodec': 'wav',
}],
"outtmpl": 'dl_audio/audio',
"outtmpl": 'result/dl_audio/audio',
}
audio_path = "dl_audio/audio.wav"
audio_path = "result/dl_audio/audio.wav"
with yt_dlp.YoutubeDL(ydl_opts) as ydl:
ydl.download([url])
logs.append("Download Complete.")
Expand All @@ -322,7 +305,7 @@ def cut_vocal_and_inst_yt(split_model):
logs = []
logs.append("Starting the audio splitting process...")
yield "\n".join(logs), None, None, None
command = f"demucs --two-stems=vocals -n {split_model} dl_audio/audio.wav -o output"
command = f"demucs --two-stems=vocals -n {split_model} result/dl_audio/audio.wav -o output"
result = subprocess.Popen(command.split(), stdout=subprocess.PIPE, text=True)
for line in result.stdout:
logs.append(line)
Expand All @@ -337,11 +320,7 @@ def cut_vocal_and_inst(split_model, audio_data):
logs = []
vocal_path = "output/result/audio.wav"
os.makedirs("output/result", exist_ok=True)
with wave.open(vocal_path, "w") as wave_file:
wave_file.setnchannels(1)
wave_file.setsampwidth(2)
wave_file.setframerate(audio_data[0])
wave_file.writeframes(audio_data[1].tobytes())
wavfile.write(vocal_path, audio_data[0], audio_data[1])
logs.append("Starting the audio splitting process...")
yield "\n".join(logs), None, None
command = f"demucs --two-stems=vocals -n {split_model} {vocal_path} -o output"
Expand All @@ -360,11 +339,7 @@ def combine_vocal_and_inst(audio_data, vocal_volume, inst_volume, split_model):
vocal_path = "output/result/output.wav"
output_path = "output/result/combine.mp3"
inst_path = f"output/{split_model}/audio/no_vocals.wav"
with wave.open(vocal_path, "w") as wave_file:
wave_file.setnchannels(1)
wave_file.setsampwidth(2)
wave_file.setframerate(audio_data[0])
wave_file.writeframes(audio_data[1].tobytes())
wavfile.write(vocal_path, audio_data[0], audio_data[1])
command = f'ffmpeg -y -i {inst_path} -i {vocal_path} -filter_complex [0:a]volume={inst_volume}[i];[1:a]volume={vocal_volume}[v];[i][v]amix=inputs=2:duration=longest[a] -map [a] -b:a 320k -c:a libmp3lame {output_path}'
result = subprocess.run(command.split(), stdout=subprocess.PIPE)
print(result.stdout.decode())
Expand All @@ -375,6 +350,7 @@ def download_and_extract_models(urls):
os.makedirs("zips", exist_ok=True)
os.makedirs(os.path.join("zips", "extract"), exist_ok=True)
os.makedirs(os.path.join(weight_root), exist_ok=True)
os.makedirs(os.path.join(index_root), exist_ok=True)
for link in urls.splitlines():
url = link.strip()
if not url:
Expand All @@ -394,41 +370,45 @@ def download_and_extract_models(urls):
logs.append(f"Extracting...")
yield "\n".join(logs)
for filename in os.listdir("zips"):
achived_file = os.path.join("zips", filename)
archived_file = os.path.join("zips", filename)
if filename.endswith(".zip"):
shutil.unpack_archive(achived_file, os.path.join("zips", "extract"), 'zip')
shutil.unpack_archive(archived_file, os.path.join("zips", "extract"), 'zip')
elif filename.endswith(".rar"):
with rarfile.RarFile(achived_file, 'r') as rar:
with rarfile.RarFile(archived_file, 'r') as rar:
rar.extractall(os.path.join("zips", "extract"))
for _, dirs, files in os.walk(os.path.join("zips", "extract")):
is_done = False
if files:
basename = ""
for file in files:
if file.endswith(".pth"):
basename = file[:-4]
os.makedirs(os.path.join(weight_root, basename), exist_ok=True)
shutil.move(os.path.join("zips", "extract", file), os.path.join(weight_root, basename, file))
is_done = True
for file in files:
if file.endswith(".index"):
shutil.move(os.path.join("zips", "extract", file), os.path.join(weight_root, basename, file))
is_done = True
else:
for sub_dir in dirs:
for _, _, sub_files in os.walk(os.path.join("zips", "extract", sub_dir)):
basename = ""
for file in sub_files:
if file.endswith(".pth"):
basename = file[:-4]
os.makedirs(os.path.join(weight_root, basename), exist_ok=True)
shutil.move(os.path.join("zips", "extract", sub_dir, file), os.path.join(weight_root, basename, file))
is_done = True
for file in sub_files:
if file.endswith(".index"):
shutil.move(os.path.join("zips", "extract", sub_dir, file), os.path.join(weight_root, basename, file))
is_done = True
shutil.rmtree(os.path.join("zips", "extract", sub_dir))
for _, dirs, files in os.walk(os.path.join("zips", "extract")):
logs.append(f"Searching Model and Index...")
yield "\n".join(logs)
model = False
index = False
if files:
for file in files:
if file.endswith(".pth"):
basename = file[:-4]
shutil.move(os.path.join("zips", "extract", file), os.path.join(weight_root, file))
model = True
if file.endswith('.index') and "trained" not in file:
shutil.move(os.path.join("zips", "extract", file), os.path.join(index_root, file))
index = True
else:
logs.append("No model in main folder.")
yield "\n".join(logs)
logs.append("Searching in subfolders...")
yield "\n".join(logs)
for sub_dir in dirs:
for _, _, sub_files in os.walk(os.path.join("zips", "extract", sub_dir)):
for file in sub_files:
if file.endswith(".pth"):
basename = file[:-4]
shutil.move(os.path.join("zips", "extract", sub_dir, file), os.path.join(weight_root, file))
model = True
if file.endswith('.index') and "trained" not in file:
shutil.move(os.path.join("zips", "extract", sub_dir, file), os.path.join(index_root, file))
index = True
shutil.rmtree(os.path.join("zips", "extract", sub_dir))
if index is False:
logs.append("Model only file, no Index file detected.")
yield "\n".join(logs)
logs.append("Download Completed!")
yield "\n".join(logs)
logs.append("Successfully download all models! Refresh your model list to load the model")
Expand Down Expand Up @@ -557,11 +537,11 @@ def change_audio_mode(vc_audio_mode):
with gr.Row():
sid = gr.Dropdown(
label="Weight",
choices = sorted(weights_file),
choices=sorted(weights_model),
)
file_index = gr.Dropdown(
label="List of index file",
choices=[],
choices=sorted(weights_index),
interactive=True,
)
spk_item = gr.Slider(
Expand All @@ -576,7 +556,7 @@ def change_audio_mode(vc_audio_mode):
refresh_model = gr.Button("Refresh model list", variant="primary")
clean_button = gr.Button("Clear Model from memory", variant="primary")
refresh_model.click(
fn=check_models, inputs=[], outputs=[sid]
fn=check_models, inputs=[], outputs=[sid, file_index]
)
clean_button.click(fn=clean, inputs=[], outputs=[sid, spk_item])
with gr.TabItem("Inference"):
Expand Down Expand Up @@ -777,7 +757,7 @@ def change_audio_mode(vc_audio_mode):
gr.Markdown(
"# <center> Model Downloader (Beta)\n"+
"#### <center> To download multi link you have to put your link to the textbox and every link separated by space\n"+
"#### <center> Support Mega, Google Drive, etc"
"#### <center> Support Direct Link, Mega, Google Drive, etc"
)
with gr.Column():
md_text = gr.Textbox(label="URL")
Expand All @@ -788,7 +768,7 @@ def change_audio_mode(vc_audio_mode):
fn=download_and_extract_models,
inputs=[md_text],
outputs=[md_download_logs]
)
)
with gr.TabItem("Settings"):
gr.Markdown(
"# <center> Settings\n"+
Expand Down

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