RVC-Project / RVC-Project/Retrieval-based-Voice-Conversion-WebUI

使用伴奏人声分离HP2_all_vocals等等所有模型,输出信息都会Error,但后台没有报错

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Description

我拉取下来使用tool文件夹里面来获取assets的模型,然后启动go-web.bat,但是在使用 ”使用伴奏人声分离“ 功能页面中,所以模型都会导致输出信息Error,但是后台输出是正常的

onnx_dereverb_By_FoxJoy模型就比较就比较严重了,好像不知道自己已经生成好了音频文件,也不会回收GPU里使用的内存

使用的是python3.10 --> 以下是我的PIP 环境以及版本:

Package Version


absl-py 2.3.1
aiofiles 24.1.0
aiohappyeyeballs 2.6.1
aiohttp 3.12.14
aiosignal 1.4.0
altair 5.5.0
antlr4-python3-runtime 4.8
anyio 4.9.0
aria2 0.0.1b0
async-timeout 5.0.1
attrs 25.3.0
audioread 3.0.1
av 15.0.0
bitarray 3.5.0
certifi 2022.12.7
cffi 1.17.1
charset-normalizer 2.1.1
click 8.2.1
colorama 0.4.6
coloredlogs 15.0.1
contourpy 1.3.2
cycler 0.12.1
Cython 3.1.2
decorator 5.2.1
einops 0.8.1
exceptiongroup 1.3.0
fairseq 0.12.2
faiss-cpu 1.7.3
fastapi 0.88.0
ffmpeg-python 0.2.0
ffmpy 0.3.1
filelock 3.13.1
flatbuffers 25.2.10
fonttools 4.58.5
frozenlist 1.7.0
fsspec 2025.5.1
future 1.0.0
gradio 3.34.0
gradio_client 1.10.4
grpcio 1.73.1
h11 0.16.0
httpcore 1.0.9
httpx 0.28.1
huggingface-hub 0.33.4
humanfriendly 10.0
hydra-core 1.0.7
idna 3.4
Jinja2 3.1.3
joblib 1.5.1
json5 0.12.0
jsonschema 4.24.0
jsonschema-specifications 2025.4.1
kiwisolver 1.4.8
librosa 0.9.1
linkify-it-py 2.0.3
llvmlite 0.39.0
local-attention 1.10.0
lxml 6.0.0
Markdown 3.8.2
markdown-it-py 2.2.0
MarkupSafe 2.1.5
matplotlib 3.10.3
matplotlib-inline 0.1.7
mdit-py-plugins 0.3.3
mdurl 0.1.2
mpmath 1.3.0
multidict 6.6.3
narwhals 1.46.0
networkx 3.3
numba 0.56.4
numpy 1.23.5
omegaconf 2.0.6
onnxruntime-gpu 1.22.0
orjson 3.10.18
packaging 25.0
pandas 2.3.1
pillow 11.0.0
pip 23.0.1
platformdirs 4.3.8
pooch 1.8.2
portalocker 3.2.0
praat-parselmouth 0.4.6
propcache 0.3.2
protobuf 6.31.1
pyasn1 0.6.1
pyasn1_modules 0.4.2
pycparser 2.22
pydantic 1.10.22
pydub 0.25.1
Pygments 2.19.2
pyparsing 3.2.3
pyreadline3 3.5.4
python-dateutil 2.9.0.post0
python-dotenv 1.1.1
python-multipart 0.0.20
pytz 2025.2
pywin32 310
pyworld 0.3.2
PyYAML 6.0.2
referencing 0.36.2
regex 2024.11.6
requests 2.28.1
resampy 0.4.3
rpds-py 0.26.0
sacrebleu 2.5.1
scikit-learn 1.7.0
scipy 1.15.3
semantic-version 2.10.0
setuptools 65.5.0
six 1.17.0
sniffio 1.3.1
soundfile 0.13.1
starlette 0.22.0
sympy 1.13.3
tabulate 0.9.0
tensorboard 2.19.0
tensorboard-data-server 0.7.2
tensorboardX 2.6.4
threadpoolctl 3.6.0
torch 2.0.1+cu117
torchaudio 2.0.2+cu117
torchcrepe 0.0.20
torchfcpe 0.0.4
torchvision 0.15.2+cu117
tornado 6.5.1
tqdm 4.67.1
traitlets 5.14.3
typing_extensions 4.14.1
tzdata 2025.2
uc-micro-py 1.0.3
urllib3 1.26.13
uvicorn 0.35.0
websockets 15.0.1
Werkzeug 3.1.3
yarl 1.20.1

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Reproduce the issue from the “使用伴奏人声分离” page after downloading models through the tool folder and starting go-web.bat. Compare the displayed Error with backend output and generated audio, then check the onnx_dereverb_By_FoxJoy case for completion and GPU-memory cleanup; done means successful status reporting and released memory.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
audio-video-rtc, backend, machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
35/100

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