From 57238ce1cd78d2405779887ca48fbf2994c0f918 Mon Sep 17 00:00:00 2001 From: Emberstar <969242373@qq.com> Date: Mon, 2 Oct 2023 00:00:14 +0800 Subject: [PATCH] update: docs --- README.md | 203 +++----------------------------------------------- README_zh.md | 205 +++------------------------------------------------ 2 files changed, 22 insertions(+), 386 deletions(-) diff --git a/README.md b/README.md index b1b6cd4..f4d06a7 100644 --- a/README.md +++ b/README.md @@ -5,7 +5,7 @@

- +

@@ -16,6 +16,7 @@ + # Feature - [x] VITS text-to-speech, voice conversion @@ -46,7 +47,7 @@ https://user-images.githubusercontent.com/73542220/237995061-c1f25b4e-dd86-438a- # Deploy -## Docker +## Docker(Recommended for Linux) ### Docker image pull script @@ -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 @@ -228,10 +227,12 @@ nvidia-smi ``` 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&target_arch=x86_64&target_version=10&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. @@ -273,190 +274,7 @@ pip install pyopenjtalk -i https://pypi.artrajz.cn/simple ## 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 @@ -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 diff --git a/README_zh.md b/README_zh.md index 80f5143..cbe5f40 100644 --- a/README_zh.md +++ b/README_zh.md @@ -5,7 +5,7 @@

- +

@@ -16,6 +16,7 @@ + # Feature - [x] VITS语音合成，语音转换 @@ -48,7 +49,7 @@ https://user-images.githubusercontent.com/73542220/237995061-c1f25b4e-dd86-438a- # 部署 -## Docker部署 +## Docker部署（Linux推荐） ### 镜像拉取脚本 @@ -137,17 +138,15 @@ DIMENSIONAL_EMOTION_MODEL = ABS_PATH + "/Model/model.yaml" ### 下载python依赖 -推荐使用python的虚拟环境，python版本 >= 3.9 +推荐使用python的虚拟环境 `pip install -r requirements.txt` windows下可能安装不了fasttext,可以用以下命令安装，附[wheels下载地址](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 ``` ### 下载VITS模型 @@ -222,14 +221,12 @@ nvidia-smi ### 安装GPU版pytorch -CUDA11.7对应的pytorch是用这个命令安装 +CUDA11.7对应的pytorch是用这个命令安装，推荐使用1.13.1+cu117，其他版本可能存在内存不稳定的问题。 ``` -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 ``` -对应版本的命令可以在[官网](https://pytorch.org/get-started/locally/)找到 - ## Linux 安装过程类似，但我没有相应的环境所以没办法测试 @@ -272,190 +269,9 @@ pip install pyopenjtalk -i https://pypi.artrajz.cn/simple ## 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 -``` +- 见`api_test.py` + + ## API KEY @@ -613,4 +429,5 @@ def voice_dimensional_emotion(upload_path): - 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