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update: docs
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@Artrajz
Artrajz committed Oct 1, 2023
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203 changes: 11 additions & 192 deletions README.md
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<br/>
<p>
<img src="https://img.shields.io/github/license/Artrajz/vits-simple-api">
<img src="https://img.shields.io/badge/python-3.9%7C3.10-green">
<img src="https://img.shields.io/badge/python-3.10-green">
<a href="https://hub.docker.com/r/artrajz/vits-simple-api">
<img src="https://img.shields.io/docker/pulls/artrajz/vits-simple-api"></a>
</p>
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# Feature

- [x] VITS text-to-speech, voice conversion
Expand Down Expand Up @@ -46,7 +47,7 @@ https://user-images.githubusercontent.com/73542220/237995061-c1f25b4e-dd86-438a-

# Deploy

## Docker
## Docker(Recommended for Linux)

### Docker image pull script

Expand Down Expand Up @@ -140,17 +141,15 @@ Run the docker image pull script again

### Download python dependencies

A python virtual environment is recommended，use python >= 3.9
A python virtual environment is recommended

`pip install -r requirements.txt`

Fasttext may not be installed on windows, you can install it with the following command,or download wheels [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#fasttext)

```
#python3.10 win_amd64
# python3.10 win_amd64
pip install https://github.com/Artrajz/archived/raw/main/fasttext/fasttext-0.9.2-cp310-cp310-win_amd64.whl
#python3.9 win_amd64
pip install https://github.com/Artrajz/archived/raw/main/fasttext/fasttext-0.9.2-cp39-cp39-win_amd64.whl
```

### Download VITS model
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```
Taking CUDA 11.7 as an example, download it from the [official website](https://developer.nvidia.com/cuda-11-7-0-download-archive?target_os=Windows&amp;target_arch=x86_64&amp;target_version=10&amp;target_type=exe_local)
### Install GPU version of PyTorch

1.13.1+cu117 is recommended, other versions may have memory instability issues.

```
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117
pip install torch==1.13.1+cu117 --extra-index-url https://download.pytorch.org/whl/cu117
```
You can find the corresponding command for the version you need on the [official website](https://pytorch.org/get-started/locally/)
## Linux
The installation process is similar, but I don't have the environment to test it.

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## POST

- python

```python
import re
import requests
import os
import random
import string
from requests_toolbelt.multipart.encoder import MultipartEncoder

abs_path = os.path.dirname(__file__)
base = "http://127.0.0.1:23456"


# 映射表
def voice_speakers():
url = f"{base}/voice/speakers"

res = requests.post(url=url)
json = res.json()
for i in json:
print(i)
for j in json[i]:
print(j)
return json


# 语音合成 voice vits
def voice_vits(text, id=0, format="wav", lang="auto", length=1, noise=0.667, noisew=0.8, max=50):
fields = {
"text": text,
"id": str(id),
"format": format,
"lang": lang,
"length": str(length),
"noise": str(noise),
"noisew": str(noisew),
"max": str(max)
}
boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))

m = MultipartEncoder(fields=fields, boundary=boundary)
headers = {"Content-Type": m.content_type}
url = f"{base}/voice"

res = requests.post(url=url, data=m, headers=headers)
fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
path = f"{abs_path}/{fname}"

with open(path, "wb") as f:
f.write(res.content)
print(path)
return path


# 语音转换 hubert-vits
def voice_hubert_vits(upload_path, id, format="wav", length=1, noise=0.667, noisew=0.8):
upload_name = os.path.basename(upload_path)
upload_type = f'audio/{upload_name.split(".")[1]}' # wav,ogg

with open(upload_path, 'rb') as upload_file:
fields = {
"upload": (upload_name, upload_file, upload_type),
"id": str(id),
"format": format,
"length": str(length),
"noise": str(noise),
"noisew": str(noisew),
}
boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))

m = MultipartEncoder(fields=fields, boundary=boundary)
headers = {"Content-Type": m.content_type}
url = f"{base}/voice/hubert-vits"

res = requests.post(url=url, data=m, headers=headers)
fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
path = f"{abs_path}/{fname}"

with open(path, "wb") as f:
f.write(res.content)
print(path)
return path


# 维度情感模型 w2v2-vits
def voice_w2v2_vits(text, id=0, format="wav", lang="auto", length=1, noise=0.667, noisew=0.8, max=50, emotion=0):
fields = {
"text": text,
"id": str(id),
"format": format,
"lang": lang,
"length": str(length),
"noise": str(noise),
"noisew": str(noisew),
"max": str(max),
"emotion": str(emotion)
}
boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))

m = MultipartEncoder(fields=fields, boundary=boundary)
headers = {"Content-Type": m.content_type}
url = f"{base}/voice/w2v2-vits"

res = requests.post(url=url, data=m, headers=headers)
fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
path = f"{abs_path}/{fname}"

with open(path, "wb") as f:
f.write(res.content)
print(path)
return path


# 语音转换 同VITS模型内角色之间的音色转换
def voice_conversion(upload_path, original_id, target_id):
upload_name = os.path.basename(upload_path)
upload_type = f'audio/{upload_name.split(".")[1]}' # wav,ogg

with open(upload_path, 'rb') as upload_file:
fields = {
"upload": (upload_name, upload_file, upload_type),
"original_id": str(original_id),
"target_id": str(target_id),
}
boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))
m = MultipartEncoder(fields=fields, boundary=boundary)

headers = {"Content-Type": m.content_type}
url = f"{base}/voice/conversion"

res = requests.post(url=url, data=m, headers=headers)

fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
path = f"{abs_path}/{fname}"

with open(path, "wb") as f:
f.write(res.content)
print(path)
return path


def voice_ssml(ssml):
fields = {
"ssml": ssml,
}
boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))

m = MultipartEncoder(fields=fields, boundary=boundary)
headers = {"Content-Type": m.content_type}
url = f"{base}/voice/ssml"

res = requests.post(url=url, data=m, headers=headers)
fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
path = f"{abs_path}/{fname}"

with open(path, "wb") as f:
f.write(res.content)
print(path)
return path

def voice_dimensional_emotion(upload_path):
upload_name = os.path.basename(upload_path)
upload_type = f'audio/{upload_name.split(".")[1]}' # wav,ogg

with open(upload_path, 'rb') as upload_file:
fields = {
"upload": (upload_name, upload_file, upload_type),
}
boundary = '----VoiceConversionFormBoundary' + ''.join(random.sample(string.ascii_letters + string.digits, 16))

m = MultipartEncoder(fields=fields, boundary=boundary)
headers = {"Content-Type": m.content_type}
url = f"{base}/voice/dimension-emotion"

res = requests.post(url=url, data=m, headers=headers)
fname = re.findall("filename=(.+)", res.headers["Content-Disposition"])[0]
path = f"{abs_path}/{fname}"

with open(path, "wb") as f:
f.write(res.content)
print(path)
return path
```
- See `api_test.py`

## API KEY

Expand Down Expand Up @@ -614,4 +432,5 @@ Learning and communication,now there is only Chinese [QQ group](https://qm.qq.co
- emotional-vits:https://github.com/innnky/emotional-vits
- vits-uma-genshin-honkai:https://huggingface.co/spaces/zomehwh/vits-uma-genshin-honkai
- vits_chinese:https://github.com/PlayVoice/vits_chinese
- Bert_VITS2:https://github.com/fishaudio/Bert-VITS2

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