Upload audiobook.py

audiobook.py

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+import json
+import re
+import numpy as np
+import IPython.display as ipd
+import torch
+import commons
+import utils
+from models import SynthesizerTrn
+from text.symbols import symbols
+from text import text_to_sequence
+import gradio as gr
+import time
+import json
+import datetime
+import os
+import pickle
+from scipy.io.wavfile import write
+import librosa
+import romajitable
+from mel_processing import spectrogram_torch
+import soundfile as sf
+from scipy import signal
+class VitsGradio:
+    def __init__(self):
+        self.lan = ["中文","日文","自动"]
+        self.modelPaths = []
+        for root,dirs,files in os.walk("checkpoints"):
+            for dir in dirs:
+                self.modelPaths.append(dir)
+        with gr.Blocks() as self.Vits:
+            with gr.Tab("小说合成"):
+                with gr.Row():
+                    with gr.Column():
+                        with gr.Row():
+                            with gr.Column():
+                                self.Text = gr.File(label="Text")
+                                self.audio_path = gr.TextArea(label="音频路径",lines=1,value = 'audiobook/chapter.wav')
+                                btnbook = gr.Button("小说合成")
+                                btnbook.click(self.tts_fn, inputs=[self.Text,self.audio_path])
+            with gr.Tab("TTS设定"):
+                with gr.Row():
+                    with gr.Column():
+                        with gr.Row():
+                            with gr.Column():
+                                self.input1 = gr.Dropdown(label = "模型", choices = self.modelPaths, value = self.modelPaths[0], type = "value")
+                                self.input2 = gr.Dropdown(label="Language", choices=self.lan, value="自动", interactive=True)                                
+                                self.input3 = gr.Dropdown(label="Speaker", choices=list(range(1001)), value=0, interactive=True)
+                                self.input4 = gr.Slider(minimum=0, maximum=1.0, label="更改噪声比例(noise scale)，以控制情感", value=0.6)
+                                self.input5 = gr.Slider(minimum=0, maximum=1.0, label="更改噪声偏差(noise scale w)，以控制音素长短", value=0.667)
+                                self.input6 = gr.Slider(minimum=0.1, maximum=10, label="duration", value=1)
+                                statusa = gr.TextArea()
+                                btnVC = gr.Button("完成vits TTS端设定")
+                btnVC.click(self.create_tts_fn, inputs=[self.input1, self.input2, self.input3, self.input4, self.input5, self.input6], outputs = [statusa])
+    
+    def is_japanese(self,string):
+        for ch in string:
+            if ord(ch) > 0x3040 and ord(ch) < 0x30FF:
+                return True
+        return False
+    
+    def is_english(self,string):
+        import re
+        pattern = re.compile('^[A-Za-z0-9.,:;!?()_*"\' ]+$')
+        if pattern.fullmatch(string):
+            return True
+        else:
+            return False
+    
+    def get_text(self,text, hps, cleaned=False):
+        if cleaned:
+            text_norm = text_to_sequence(text, self.hps_ms.symbols, [])
+        else:
+            text_norm = text_to_sequence(text, self.hps_ms.symbols, self.hps_ms.data.text_cleaners)
+        if self.hps_ms.data.add_blank:
+            text_norm = commons.intersperse(text_norm, 0)
+        text_norm = torch.LongTensor(text_norm)
+        return text_norm
+
+    def get_label(self,text, label):
+        if f'[{label}]' in text:
+            return True, text.replace(f'[{label}]', '')
+        else:
+            return False, text
+
+    def sle(self,language,text):
+        text = text.replace('\n','。').replace(' ',',')
+        if language == "中文":
+            tts_input1 = "[ZH]" + text + "[ZH]"
+            return tts_input1
+        elif language == "自动":
+            tts_input1 = f"[JA]{text}[JA]" if self.is_japanese(text) else f"[ZH]{text}[ZH]"
+            return tts_input1
+        elif language == "日文":
+            tts_input1 = "[JA]" + text + "[JA]"
+            return tts_input1
+
+    def create_tts_fn(self,path, input2, input3, n_scale= 0.667,n_scale_w = 0.8, l_scale = 1 ):
+        self.language = input2
+        self.speaker_id = int(input3)
+        self.n_scale = n_scale
+        self.n_scale_w = n_scale_w
+        self.l_scale = l_scale
+        self.dev = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+        self.hps_ms = utils.get_hparams_from_file(f"checkpoints/{path}/config.json")
+        self.n_speakers = self.hps_ms.data.n_speakers if 'n_speakers' in self.hps_ms.data.keys() else 0
+        self.n_symbols = len(self.hps_ms.symbols) if 'symbols' in self.hps_ms.keys() else 0
+        self.net_g_ms = SynthesizerTrn(
+            self.n_symbols,
+            self.hps_ms.data.filter_length // 2 + 1,
+            self.hps_ms.train.segment_size // self.hps_ms.data.hop_length,
+            n_speakers=self.n_speakers,
+            **self.hps_ms.model).to(self.dev)
+        _ = self.net_g_ms.eval()
+        _ = utils.load_checkpoint(f"checkpoints/{path}/model.pth", self.net_g_ms)
+        return 'success'
+
+    def transfer(self,text):
+        text = re.sub("<[^>]*>","",text)
+        result_list = re.split(r'\n', text)
+        final_list = []
+        for j in result_list:
+            result_list2 = re.split(r'。|！|——|：|；|……|——|。|！', j)
+            for i in result_list2:
+                if self.is_english(i):
+                    i = romajitable.to_kana(i).katakana
+                for m in range(20):
+                    i = i.replace('\n','').replace(' ','').replace('……','。').replace('…','。').replace('还','孩').replace('“','').replace('”','').replace('！','。').replace('」','').replace('「','')
+            #Current length of single sentence: 50 
+                if len(i)>1:
+                    if len(i) > 50:
+                        try:
+                            cur_list = re.split(r'。|！|——|，|：', i)
+                            for i in cur_list:
+                                if len(i)>1:
+                                    final_list.append(i+'。')
+                        except:
+                            pass
+                    else:
+                        final_list.append(i)
+        final_list = [x for x in final_list if x != '']
+        return final_list
+
+    def tts_fn(self,text,audio_path):
+        with open(text.name, "r", encoding="utf-8") as f:
+            text = f.read()
+        a = ['【','[','(','（','〔']
+        b = ['】',']',')','）','〕']
+        for i in a:
+            text = text.replace(i,'<')
+        for i in b:
+            text = text.replace(i,'>')
+        final_list = self.transfer(text)
+        split_list = []
+        while len(final_list) > 0:
+            split_list.append(final_list[:1000])
+            final_list = final_list[1000:]
+        c0 = 0
+        for lists in split_list:
+            audio_fin = []
+            t = datetime.timedelta(seconds=0)
+            c = 0
+            f1 = open(audio_path.replace('.wav',str(c0)+".srt"),'w',encoding='utf-8')
+            for sentence in lists:
+                try:
+                    c +=1
+                    with torch.no_grad():
+                        stn_tst = self.get_text(self.sle(self.language,sentence), self.hps_ms, cleaned=False)
+                        x_tst = stn_tst.unsqueeze(0).to(self.dev)
+                        x_tst_lengths = torch.LongTensor([stn_tst.size(0)]).to(self.dev)
+                        sid = torch.LongTensor([self.speaker_id]).to(self.dev)
+                        t1 = time.time()
+                        audio = self.net_g_ms.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=self.n_scale, noise_scale_w=self.n_scale_w, length_scale=self.l_scale)[0][
+                            0, 0].data.cpu().float().numpy()
+                        t2 = time.time()
+                        spending_time = "第"+str(c)+"句的推理时间为："+str(t2-t1)+"s"
+                        print(spending_time)
+                        time_start = str(t).split(".")[0] + "," + str(t.microseconds)[:3]
+                        last_time = datetime.timedelta(seconds=len(audio)/float(22050))
+                        t+=last_time
+                        time_end = str(t).split(".")[0] + "," + str(t.microseconds)[:3]
+                        print(time_end)
+                        f1.write(str(c-1)+'\n'+time_start+' --> '+time_end+'\n'+sentence.replace('。','')+'\n\n')
+                    resampled_audio_data = signal.resample(audio, len(audio) * 2)
+                    audio_fin.append(resampled_audio_data)
+                except:
+                    pass
+            sf.write(audio_path.replace('.wav',str(c0)+'.wav'), np.concatenate(audio_fin), 44100, 'PCM_24')
+            c0 += 1
+        file_path = audio_path.replace('.wav',str(c0)+".srt")
+
+if __name__ == '__main__':
+    print("开始部署")
+    grVits = VitsGradio()
+    grVits.Vits.launch()