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app.py

@@ -1,132 +1,4 @@
-import nltk
-import ssl
-
-try:
-    _create_unverified_https_context = ssl._create_unverified_context
-except AttributeError:
-    pass
-else:
-    ssl._create_default_https_context = _create_unverified_https_context
-nltk.download("cmudict")
-
-import os
-import json
-import random
-import gradio as gr
-import numpy as np
-import torch
-import re_matching
-import utils
-from infer import infer, latest_version, get_net_g
-import gradio as gr
-from config import config
-from tools.webui import reload_javascript, get_character_html
-
-device = config.webui_config.device
-if device == "mps":
-    os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
-
-def speak_fn(
-        text: str,
-        exceed_flag,
-        speaker="TalkFlower_CNzh",
-        sdp_ratio=0.2,      # SDP/DP混合比
-        noise_scale=0.6,        # 感情
-        noise_scale_w=0.6,      # 音素长度
-        length_scale=0.9,       # 语速
-        language="ZH",
-        interval_between_para=0.2,      # 段间间隔
-        interval_between_sent=1,        # 句间间隔
-    ):
-    while text.find("\n\n") != -1:
-        text = text.replace("\n\n", "\n")
-    if len(text) > 100:
-        print(f"Too Long Text: {text}")
-        if exceed_flag:
-            text = "不要超过100字！"
-            audio_value = "./assets/audios/nomorethan100.wav"
-        else:
-            text = "这句太长了，憋坏我啦！"
-            audio_value = "./assets/audios/overlength.wav"
-        exceed_flag = not exceed_flag
-    else:
-        audio_list = []
-        if len(text) > 42:
-            print(f"Long Text: {text}")
-            para_list = re_matching.cut_para(text)
-            for p in para_list:
-                audio_list_sent = []
-                sent_list = re_matching.cut_sent(p)
-                for s in sent_list:
-                    audio = infer(
-                        s,
-                        sdp_ratio=sdp_ratio,
-                        noise_scale=noise_scale,
-                        noise_scale_w=noise_scale_w,
-                        length_scale=length_scale,
-                        sid=speaker,
-                        language=language,
-                        hps=hps,
-                        net_g=net_g,
-                        device=device,
-                    )
-                    audio_list_sent.append(audio)
-                    silence = np.zeros((int)(44100 * interval_between_sent))
-                    audio_list_sent.append(silence)
-                if (interval_between_para - interval_between_sent) > 0:
-                    silence = np.zeros((int)(44100 * (interval_between_para - interval_between_sent)))
-                    audio_list_sent.append(silence)
-                audio16bit = gr.processing_utils.convert_to_16_bit_wav(np.concatenate(audio_list_sent))  # 对完整句子做音量归一
-                audio_list.append(audio16bit)
-        else:
-            print(f"Short Text: {text}")
-            silence = np.zeros(hps.data.sampling_rate // 2, dtype=np.int16)
-            with torch.no_grad():
-                for piece in text.split("|"):
-                    audio = infer(
-                        piece,
-                        sdp_ratio=sdp_ratio,
-                        noise_scale=noise_scale,
-                        noise_scale_w=noise_scale_w,
-                        length_scale=length_scale,
-                        sid=speaker,
-                        language=language,
-                        hps=hps,
-                        net_g=net_g,
-                        device=device,
-                    )
-                    audio16bit = gr.processing_utils.convert_to_16_bit_wav(audio)
-                    audio_list.append(audio16bit)
-                    audio_list.append(silence)  # 将静音添加到列表中
-        
-        audio_concat = np.concatenate(audio_list)
-        audio_value = (hps.data.sampling_rate, audio_concat)
-        
-    return gr.update(value=audio_value, autoplay=True), get_character_html(text), exceed_flag, gr.update(interactive=True)
-
-
-def submit_lock_fn():    
-    return gr.update(interactive=False)
-
-
-def init_fn():
-    gr.Info("2023-11-24: 优化长句生成效果；增加示例；更新了一些小彩蛋；画了一些大饼）")
-    gr.Info("Only support Chinese now. Trying to train a mutilingual model. 欢迎在 Community 中提建议~")
-    
-    index = random.randint(1,7)
-    welcome_text = get_sentence("Welcome", index)
-    
-    return gr.update(value=f"./assets/audios/Welcome{index}.wav", autoplay=False), get_character_html(welcome_text)
-
-def get_sentence(category, index=-1):
-    if index == -1:
-        index = random.randint(1, len(full_lines[category]))
-    return full_lines[category][f"{index}"]
-
-with open("./css/style.css", "r", encoding="utf-8") as f:
-    customCSS = f.read()
-with open("./assets/lines.json", "r", encoding="utf-8") as f:
-    full_lines = json.load(f)
+from presets import *
 
 with gr.Blocks(css=customCSS) as demo:
     exceed_flag = gr.State(value=False)
@@ -162,9 +34,6 @@ with gr.Blocks(css=customCSS) as demo:
 
 
 if __name__ == "__main__":
-    hps = utils.get_hparams_from_file(config.webui_config.config_path)
-    version = hps.version if hasattr(hps, "version") else latest_version
-    net_g = get_net_g(model_path=config.webui_config.model, version=version, device=device, hps=hps)
     reload_javascript()
     demo.launch(
         allowed_paths=["./assets", "./javascript", "./css"],

javascript/main.js

@@ -65,14 +65,29 @@ function set_speak_examples() {
     buttons[0].addEventListener("click", function() {
         const randomString = praiseArray[Math.floor(Math.random() * praiseArray.length)];
         speak_input.value = randomString;
+        var event = new Event('input', {
+            bubbles: true,
+            cancelable: true,
+        });
+        speak_input.dispatchEvent(event);
     });
     buttons[1].addEventListener("click", function() {
         const randomString = scriptsArray[Math.floor(Math.random() * scriptsArray.length)];
         speak_input.value = randomString;
+        var event = new Event('input', {
+            bubbles: true,
+            cancelable: true,
+        });
+        speak_input.dispatchEvent(event);
     });
     buttons[2].addEventListener("click", function() {
         const randomString = memeArray[Math.floor(Math.random() * memeArray.length)];
         speak_input.value = randomString;
+        var event = new Event('input', {
+            bubbles: true,
+            cancelable: true,
+        });
+        speak_input.dispatchEvent(event);
     });
 
 }

presets.py

@@ -0,0 +1,135 @@
+import nltk, ssl
+try:
+    _create_unverified_https_context = ssl._create_unverified_context
+except AttributeError:
+    pass
+else:
+    ssl._create_default_https_context = _create_unverified_https_context
+nltk.download("cmudict")
+
+import os, logging, datetime, json, random
+import gradio as gr
+import numpy as np
+import torch
+import re_matching
+import utils
+from infer import infer, latest_version, get_net_g
+import gradio as gr
+from config import config
+from tools.webui import reload_javascript, get_character_html
+
+logging.basicConfig(
+    level=logging.INFO,
+    format='[%(levelname)s|%(asctime)s]%(message)s',
+    datefmt='%Y-%m-%d %H:%M:%S'
+)
+
+device = config.webui_config.device
+if device == "mps":
+    os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
+    
+hps = utils.get_hparams_from_file(config.webui_config.config_path)
+version = hps.version if hasattr(hps, "version") else latest_version
+net_g = get_net_g(model_path=config.webui_config.model, version=version, device=device, hps=hps)
+
+with open("./css/style.css", "r", encoding="utf-8") as f:
+    customCSS = f.read()
+with open("./assets/lines.json", "r", encoding="utf-8") as f:
+    full_lines = json.load(f)
+
+def speak_fn(
+        text: str,
+        exceed_flag,
+        speaker="TalkFlower_CNzh",
+        sdp_ratio=0.2,      # SDP/DP混合比
+        noise_scale=0.6,        # 感情
+        noise_scale_w=0.6,      # 音素长度
+        length_scale=0.9,       # 语速
+        language="ZH",
+        interval_between_para=0.2,      # 段间间隔
+        interval_between_sent=1,        # 句间间隔
+    ):
+    while text.find("\n\n") != -1:
+        text = text.replace("\n\n", "\n")
+    if len(text) > 100:
+        logging.info(f"Too Long Text: {text}")
+        if exceed_flag:
+            text = "不要超过100字！"
+            audio_value = "./assets/audios/nomorethan100.wav"
+        else:
+            text = "这句太长了，憋坏我啦！"
+            audio_value = "./assets/audios/overlength.wav"
+        exceed_flag = not exceed_flag
+    else:
+        audio_list = []
+        if len(text) > 42:
+            logging.info(f"Long Text: {text}")
+            para_list = re_matching.cut_para(text)
+            for p in para_list:
+                audio_list_sent = []
+                sent_list = re_matching.cut_sent(p)
+                for s in sent_list:
+                    audio = infer(
+                        s,
+                        sdp_ratio=sdp_ratio,
+                        noise_scale=noise_scale,
+                        noise_scale_w=noise_scale_w,
+                        length_scale=length_scale,
+                        sid=speaker,
+                        language=language,
+                        hps=hps,
+                        net_g=net_g,
+                        device=device,
+                    )
+                    audio_list_sent.append(audio)
+                    silence = np.zeros((int)(44100 * interval_between_sent))
+                    audio_list_sent.append(silence)
+                if (interval_between_para - interval_between_sent) > 0:
+                    silence = np.zeros((int)(44100 * (interval_between_para - interval_between_sent)))
+                    audio_list_sent.append(silence)
+                audio16bit = gr.processing_utils.convert_to_16_bit_wav(np.concatenate(audio_list_sent))  # 对完整句子做音量归一
+                audio_list.append(audio16bit)
+        else:
+            logging.info(f"Short Text: {text}")
+            silence = np.zeros(hps.data.sampling_rate // 2, dtype=np.int16)
+            with torch.no_grad():
+                for piece in text.split("|"):
+                    audio = infer(
+                        piece,
+                        sdp_ratio=sdp_ratio,
+                        noise_scale=noise_scale,
+                        noise_scale_w=noise_scale_w,
+                        length_scale=length_scale,
+                        sid=speaker,
+                        language=language,
+                        hps=hps,
+                        net_g=net_g,
+                        device=device,
+                    )
+                    audio16bit = gr.processing_utils.convert_to_16_bit_wav(audio)
+                    audio_list.append(audio16bit)
+                    audio_list.append(silence)  # 将静音添加到列表中
+        
+        audio_concat = np.concatenate(audio_list)
+        audio_value = (hps.data.sampling_rate, audio_concat)
+        
+    return gr.update(value=audio_value, autoplay=True), get_character_html(text), exceed_flag, gr.update(interactive=True)
+
+
+def submit_lock_fn():    
+    return gr.update(interactive=False)
+
+
+def init_fn():
+    gr.Info("2023-11-24: 优化长句生成效果；增加示例；更新了一些小彩蛋；画了一些大饼）")
+    gr.Info("Only support Chinese now. Trying to train a mutilingual model. 欢迎在 Community 中提建议~")
+    
+    index = random.randint(1,7)
+    welcome_text = get_sentence("Welcome", index)
+    
+    return gr.update(value=f"./assets/audios/Welcome{index}.wav", autoplay=False), get_character_html(welcome_text)
+
+def get_sentence(category, index=-1):
+    if index == -1:
+        index = random.randint(1, len(full_lines[category]))
+    return full_lines[category][f"{index}"]