update

README.md

@@ -1,7 +1,7 @@
 # CosyVoice
 
 ## 👉🏻 [CosyVoice2 Demos](https://funaudiollm.github.io/cosyvoice2/) 👈🏻
-[[CosyVoice2 Paper](https://fun-audio-llm.github.io/pdf/CosyVoice_v1.pdf)][[CosyVoice2 Studio](https://www.modelscope.cn/studios/iic/CosyVoice-300M)]
+[[CosyVoice2 Paper](https://fun-audio-llm.github.io/pdf/CosyVoice_v1.pdf)][[CosyVoice2 Studio](https://www.modelscope.cn/studios/iic/CosyVoice2-0.5B)]
 
 ## 👉🏻 [CosyVoice Demos](https://fun-audio-llm.github.io/) 👈🏻
 [[CosyVoice Paper](https://fun-audio-llm.github.io/pdf/CosyVoice_v1.pdf)][[CosyVoice Studio](https://www.modelscope.cn/studios/iic/CosyVoice-300M)][[CosyVoice Code](https://github.com/FunAudioLLM/CosyVoice)]

webui.py

@@ -22,7 +22,7 @@ import random
 import librosa
 ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
 sys.path.append('{}/third_party/Matcha-TTS'.format(ROOT_DIR))
-from cosyvoice.cli.cosyvoice import CosyVoice
+from cosyvoice.cli.cosyvoice import CosyVoice, CosyVoice2
 from cosyvoice.utils.file_utils import load_wav, logging
 from cosyvoice.utils.common import set_all_random_seed
 
@@ -51,7 +51,7 @@ def postprocess(speech, top_db=60, hop_length=220, win_length=440):
     )
     if speech.abs().max() > max_val:
         speech = speech / speech.abs().max() * max_val
-    speech = torch.concat([speech, torch.zeros(1, int(target_sr * 0.2))], dim=1)
+    speech = torch.concat([speech, torch.zeros(1, int(cosyvoice.sample_rate * 0.2))], dim=1)
     return speech
 
 
@@ -71,31 +71,31 @@ def generate_audio(tts_text, mode_checkbox_group, sft_dropdown, prompt_text, pro
     if mode_checkbox_group in ['自然语言控制']:
         if cosyvoice.frontend.instruct is False:
             gr.Warning('您正在使用自然语言控制模式, {}模型不支持此模式, 请使用iic/CosyVoice-300M-Instruct模型'.format(args.model_dir))
-            yield (target_sr, default_data)
+            yield (cosyvoice.sample_rate, default_data)
         if instruct_text == '':
             gr.Warning('您正在使用自然语言控制模式, 请输入instruct文本')
-            yield (target_sr, default_data)
+            yield (cosyvoice.sample_rate, default_data)
         if prompt_wav is not None or prompt_text != '':
             gr.Info('您正在使用自然语言控制模式, prompt音频/prompt文本会被忽略')
     # if cross_lingual mode, please make sure that model is iic/CosyVoice-300M and tts_text prompt_text are different language
     if mode_checkbox_group in ['跨语种复刻']:
         if cosyvoice.frontend.instruct is True:
             gr.Warning('您正在使用跨语种复刻模式, {}模型不支持此模式, 请使用iic/CosyVoice-300M模型'.format(args.model_dir))
-            yield (target_sr, default_data)
+            yield (cosyvoice.sample_rate, default_data)
         if instruct_text != '':
             gr.Info('您正在使用跨语种复刻模式, instruct文本会被忽略')
         if prompt_wav is None:
             gr.Warning('您正在使用跨语种复刻模式, 请提供prompt音频')
-            yield (target_sr, default_data)
+            yield (cosyvoice.sample_rate, default_data)
         gr.Info('您正在使用跨语种复刻模式, 请确保合成文本和prompt文本为不同语言')
     # if in zero_shot cross_lingual, please make sure that prompt_text and prompt_wav meets requirements
     if mode_checkbox_group in ['3s极速复刻', '跨语种复刻']:
         if prompt_wav is None:
             gr.Warning('prompt音频为空，您是否忘记输入prompt音频？')
-            yield (target_sr, default_data)
+            yield (cosyvoice.sample_rate, default_data)
         if torchaudio.info(prompt_wav).sample_rate < prompt_sr:
             gr.Warning('prompt音频采样率{}低于{}'.format(torchaudio.info(prompt_wav).sample_rate, prompt_sr))
-            yield (target_sr, default_data)
+            yield (cosyvoice.sample_rate, default_data)
     # sft mode only use sft_dropdown
     if mode_checkbox_group in ['预训练音色']:
         if instruct_text != '' or prompt_wav is not None or prompt_text != '':
@@ -104,7 +104,7 @@ def generate_audio(tts_text, mode_checkbox_group, sft_dropdown, prompt_text, pro
     if mode_checkbox_group in ['3s极速复刻']:
         if prompt_text == '':
             gr.Warning('prompt文本为空，您是否忘记输入prompt文本？')
-            yield (target_sr, default_data)
+            yield (cosyvoice.sample_rate, default_data)
         if instruct_text != '':
             gr.Info('您正在使用3s极速复刻模式，预训练音色/instruct文本会被忽略！')
 
@@ -112,24 +112,24 @@ def generate_audio(tts_text, mode_checkbox_group, sft_dropdown, prompt_text, pro
         logging.info('get sft inference request')
         set_all_random_seed(seed)
         for i in cosyvoice.inference_sft(tts_text, sft_dropdown, stream=stream, speed=speed):
-            yield (target_sr, i['tts_speech'].numpy().flatten())
+            yield (cosyvoice.sample_rate, i['tts_speech'].numpy().flatten())
     elif mode_checkbox_group == '3s极速复刻':
         logging.info('get zero_shot inference request')
         prompt_speech_16k = postprocess(load_wav(prompt_wav, prompt_sr))
         set_all_random_seed(seed)
         for i in cosyvoice.inference_zero_shot(tts_text, prompt_text, prompt_speech_16k, stream=stream, speed=speed):
-            yield (target_sr, i['tts_speech'].numpy().flatten())
+            yield (cosyvoice.sample_rate, i['tts_speech'].numpy().flatten())
     elif mode_checkbox_group == '跨语种复刻':
         logging.info('get cross_lingual inference request')
         prompt_speech_16k = postprocess(load_wav(prompt_wav, prompt_sr))
         set_all_random_seed(seed)
         for i in cosyvoice.inference_cross_lingual(tts_text, prompt_speech_16k, stream=stream, speed=speed):
-            yield (target_sr, i['tts_speech'].numpy().flatten())
+            yield (cosyvoice.sample_rate, i['tts_speech'].numpy().flatten())
     else:
         logging.info('get instruct inference request')
         set_all_random_seed(seed)
         for i in cosyvoice.inference_instruct(tts_text, sft_dropdown, instruct_text, stream=stream, speed=speed):
-            yield (target_sr, i['tts_speech'].numpy().flatten())
+            yield (cosyvoice.sample_rate, i['tts_speech'].numpy().flatten())
 
 
 def main():
@@ -178,11 +178,11 @@ if __name__ == '__main__':
                         default=8000)
     parser.add_argument('--model_dir',
                         type=str,
-                        default='pretrained_models/CosyVoice-300M',
+                        default='pretrained_models/CosyVoice2-0.5B',
                         help='local path or modelscope repo id')
     args = parser.parse_args()
-    cosyvoice = CosyVoice(args.model_dir)
+    cosyvoice = CosyVoice2(args.model_dir) if 'CosyVoice2' in args.model_dir else CosyVoice(args.model_dir)
     sft_spk = cosyvoice.list_avaliable_spks()
-    prompt_sr, target_sr = 16000, 22050
-    default_data = np.zeros(target_sr)
+    prompt_sr = 16000
+    default_data = np.zeros(cosyvoice.sample_rate)
     main()