删除多余缩进

README.md

@@ -121,9 +121,7 @@ pip install -r requirements.txt
 
 0. Regarding image tags: Due to rapid updates in the codebase and the slow process of packaging and testing images, please check [Docker Hub](https://hub.docker.com/r/breakstring/gpt-sovits) for the currently packaged latest images and select as per your situation, or alternatively, build locally using a Dockerfile according to your own needs.
 1. Environment Variables：
-
+   - is_half: Controls half-precision/double-precision. This is typically the cause if the content under the directories 4-cnhubert/5-wav32k is not generated correctly during the "SSL extracting" step. Adjust to True or False based on your actual situation.
-- is_half: Controls half-precision/double-precision. This is typically the cause if the content under the directories 4-cnhubert/5-wav32k is not generated correctly during the "SSL extracting" step. Adjust to True or False based on your actual situation.
-
 2. Volumes Configuration，The application's root directory inside the container is set to /workspace. The default docker-compose.yaml lists some practical examples for uploading/downloading content.
 3. shm_size： The default available memory for Docker Desktop on Windows is too small, which can cause abnormal operations. Adjust according to your own situation.
 4. Under the deploy section, GPU-related settings should be adjusted cautiously according to your system and actual circumstances.
@@ -158,7 +156,7 @@ docker run --rm -it --gpus=all --env=is_half=False --volume=G:\GPT-SoVITS-Docker
 
 4. For Chinese ASR (additionally), download models from [Damo ASR Model](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/files), [Damo VAD Model](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/files), and [Damo Punc Model](https://modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/files) and place them in `tools/asr/models`.
 
-5. For English or Japanese ASR (additionally), download models from [Faster Whisper Large V3](https://huggingface.co/Systran/faster-whisper-large-v3) and place them in `tools/asr/models`. Also, [other models](https://huggingface.co/Systran) may have the similar effect with smaller disk footprint. 
+5. For English or Japanese ASR (additionally), download models from [Faster Whisper Large V3](https://huggingface.co/Systran/faster-whisper-large-v3) and place them in `tools/asr/models`. Also, [other models](https://huggingface.co/Systran) may have the similar effect with smaller disk footprint.
 
 ## Dataset Format
 
@@ -175,7 +173,7 @@ Language dictionary:
 - 'en': English
 - 'ko': Korean
 - 'yue': Cantonese
-  
+
 Example:
 
 ```
@@ -184,61 +182,56 @@ D:\GPT-SoVITS\xxx/xxx.wav|xxx|en|I like playing Genshin.
 
 ## Finetune and inference
 
- ### Open WebUI
+### Open WebUI
 
- #### Integrated Package Users
+#### Integrated Package Users
 
- Double-click `go-webui.bat`or use `go-webui.ps1`
+Double-click `go-webui.bat`or use `go-webui.ps1`
- if you want to switch to V1,then double-click`go-webui-v1.bat` or use `go-webui-v1.ps1`
+if you want to switch to V1,then double-click`go-webui-v1.bat` or use `go-webui-v1.ps1`
 
- #### Others
+#### Others
 
- ```bash
+```bash
- python webui.py <language(optional)>
+python webui.py <language(optional)>
- ```
+```
 
- if you want to switch to V1,then
+if you want to switch to V1,then
 
- ```bash
+```bash
- python webui.py v1 <language(optional)>
+python webui.py v1 <language(optional)>
- ```
+```
 Or maunally switch version in WebUI
 
- ### Finetune
+### Finetune
 
- #### Path Auto-filling is now supported
+#### Path Auto-filling is now supported
 
-     1.Fill in the audio path
+    1. Fill in the audio path
+    2. Slice the audio into small chunks
+    3. Denoise(optinal)
+    4. ASR
+    5. Proofreading ASR transcriptions
+    6. Go to the next Tab, then finetune the model
 
-     2.Slice the audio into small chunks
+### Open Inference WebUI
 
-     3.Denoise(optinal)
+#### Integrated Package Users
 
-     4.ASR
+Double-click `go-webui-v2.bat` or use `go-webui-v2.ps1` ,then open the inference webui at  `1-GPT-SoVITS-TTS/1C-inference`
 
-     5.Proofreading ASR transcriptions
+#### Others
 
-     6.Go to the next Tab, then finetune the model
+```bash
+python GPT_SoVITS/inference_webui.py <language(optional)>
+```
+OR
 
- ### Open Inference WebUI
+```bash
-
+python webui.py
- #### Integrated Package Users
+```
-
- Double-click `go-webui-v2.bat` or use `go-webui-v2.ps1` ,then open the inference webui at  `1-GPT-SoVITS-TTS/1C-inference` 
-
- #### Others
-
- ```bash
- python GPT_SoVITS/inference_webui.py <language(optional)>
- ```
- OR
-
- ```bash
- python webui.py
- ```
 then open the inference webui at `1-GPT-SoVITS-TTS/1C-inference`
 
- ## V2 Release Notes
+## V2 Release Notes
 
 New Features:
 
@@ -248,11 +241,11 @@ New Features:
 
 3. Pre-trained model extended from 2k hours to 5k hours
 
-4. Improved synthesis quality for low-quality reference audio 
+4. Improved synthesis quality for low-quality reference audio
 
-    [more details](https://github.com/RVC-Boss/GPT-SoVITS/wiki/GPT%E2%80%90SoVITS%E2%80%90v2%E2%80%90features-(%E6%96%B0%E7%89%B9%E6%80%A7) ) 
+    [more details](https://github.com/RVC-Boss/GPT-SoVITS/wiki/GPT%E2%80%90SoVITS%E2%80%90v2%E2%80%90features-(%E6%96%B0%E7%89%B9%E6%80%A7))
 
-Use v2 from v1 environment: 
+Use v2 from v1 environment:
 
 1. `pip install -r requirements.txt` to update some packages
 
@@ -262,7 +255,7 @@ Use v2 from v1 environment:
 
     Chinese v2 additional: [G2PWModel_1.1.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/g2p/G2PWModel_1.1.zip)（Download G2PW models,  unzip and rename to `G2PWModel`, and then place them in `GPT_SoVITS/text`.
 
- ## V3 Release Notes
+## V3 Release Notes
 
 New Features:
 
@@ -270,9 +263,9 @@ New Features:
 
 2. GPT model is more stable, with fewer repetitions and omissions, and it is easier to generate speech with richer emotional expression.
 
-    [more details](https://github.com/RVC-Boss/GPT-SoVITS/wiki/GPT%E2%80%90SoVITS%E2%80%90v3%E2%80%90features-(%E6%96%B0%E7%89%B9%E6%80%A7) ) 
+    [more details](https://github.com/RVC-Boss/GPT-SoVITS/wiki/GPT%E2%80%90SoVITS%E2%80%90v3%E2%80%90features-(%E6%96%B0%E7%89%B9%E6%80%A7))
 
-Use v3 from v2 environment: 
+Use v3 from v2 environment:
 
 1. `pip install -r requirements.txt` to update some packages
 
@@ -310,7 +303,7 @@ python tools/uvr5/webui.py "<infer_device>" <is_half> <webui_port_uvr5>
 ```
 <!-- If you can't open a browser, follow the format below for UVR processing,This is using mdxnet for audio processing
 ```
-python mdxnet.py --model --input_root --output_vocal --output_ins --agg_level --format --device --is_half_precision 
+python mdxnet.py --model --input_root --output_vocal --output_ins --agg_level --format --device --is_half_precision
 ``` -->
 This is how the audio segmentation of the dataset is done using the command line
 ```
@@ -319,7 +312,7 @@ python audio_slicer.py \
     --output_root "<directory_where_subdivided_audio_clips_will_be_saved>" \
     --threshold <volume_threshold> \
     --min_length <minimum_duration_of_each_subclip> \
-    --min_interval <shortest_time_gap_between_adjacent_subclips> 
+    --min_interval <shortest_time_gap_between_adjacent_subclips>
     --hop_size <step_size_for_computing_volume_curve>
 ```
 This is how dataset ASR processing is done using the command line(Only Chinese)