add application file

app.py

@@ -0,0 +1,371 @@
+import matplotlib.pyplot as plt
+import IPython.display as ipd
+import os
+import json
+import math
+import torch
+import commons
+import utils
+from models import SynthesizerTrn
+from text.symbols import symbols
+from text import text_to_sequence
+from scipy.io.wavfile import write
+import gradio as gr
+import numpy as np
+from PIL import Image
+import numpy as np
+import os
+from pathlib import Path
+
+
+
+
+LANGUAGES = ['EN','CN','JP']
+SPEAKER_ID = 0
+COVER = "models/Yuuka/cover.png"
+speaker_choice = "Yuuka"
+MODEL_ZH_NAME = "早濑优香"
+EXAMPLE_TEXT = "先生。今日も全力であなたをアシストしますね。"
+#USER_INPUT_TEXT = ""
+
+CONFIG_PATH = "configs/config2.json"
+MODEL_PATH = "models/parappa/path.pth"
+
+hps = utils.get_hparams_from_file(CONFIG_PATH)
+net_g = SynthesizerTrn(
+    len(hps.symbols),
+    hps.data.filter_length // 2 + 1,
+    hps.train.segment_size // hps.data.hop_length,
+    n_speakers=hps.data.n_speakers,
+    **hps.model)
+
+model = net_g.eval()
+model = utils.load_checkpoint(MODEL_PATH, net_g, None)
+
+def load_model():
+    global hps,net_g,model
+
+    hps = utils.get_hparams_from_file(CONFIG_PATH)
+    net_g = SynthesizerTrn(
+    len(hps.symbols),
+    hps.data.filter_length // 2 + 1,
+    hps.train.segment_size // hps.data.hop_length,
+    n_speakers=hps.data.n_speakers,
+    **hps.model)
+
+    model = net_g.eval()
+    model = utils.load_checkpoint(MODEL_PATH, net_g, None)
+
+def get_text(text, hps):
+    text_norm = text_to_sequence(text, hps.data.text_cleaners)
+    if hps.data.add_blank:
+        text_norm = commons.intersperse(text_norm, 0)
+    text_norm = torch.LongTensor(text_norm)
+    return text_norm
+
+def tts_fn(text, noise_scale, noise_scale_w, length_scale):
+  stn_tst = get_text(text, hps)
+  with torch.no_grad():
+    x_tst = stn_tst.unsqueeze(0)
+    x_tst_lengths = torch.LongTensor([stn_tst.size(0)])
+    sid = torch.LongTensor([SPEAKER_ID])
+    audio = net_g.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=noise_scale, noise_scale_w=noise_scale_w, length_scale=length_scale)[0][0,0].data.cpu().float().numpy()
+  return  (22050, audio)
+
+def add_model_fn(example_text, cover, speakerID, name_en, name_cn, language):
+
+    # 检查必填字段是否为空
+    if not speakerID or not name_en or not language:
+        raise gr.Error("Please fill in all required fields!")
+        return "Failed to add model"
+
+    ### 保存上传的文件
+
+    # 生成文件路径
+    model_save_dir = Path("models")
+    model_save_dir = model_save_dir / name_en
+    img_save_dir = model_save_dir
+    model_save_dir.mkdir(parents=True, exist_ok=True)
+
+    Model_name = name_en + ".pth"
+    model_save_dir = model_save_dir / Model_name
+
+    # 保存上传的图片
+    if cover is not None:
+        img = np.array(cover)
+        img = Image.fromarray(img)
+        img.save(os.path.join(img_save_dir, 'cover.png'))
+
+    #获取用户输入
+    new_model = {
+        "name_en": name_en,
+        "name_zh": name_cn,
+        "cover": img_save_dir / "cover.png",
+        "sid": speakerID,
+        "example": example_text,
+        "language": language,
+        "type": "single",
+        "model_path": model_save_dir
+    }
+
+    #写入json
+    with open("models/model_info.json", "r", encoding="utf-8") as f:
+        models_info = json.load(f)
+
+    models_info[name_en] = new_model
+    with open("models/model_info.json", "w") as f:
+        json.dump(models_info, f, cls=CustomEncoder)
+
+
+    return "Success"
+
+def clear_input_text():
+    return ""
+
+def clear_add_model_info():
+    return "",None,"","","",""
+
+def get_options():
+  with open("models/model_info.json", "r", encoding="utf-8") as f:
+    global models_info
+    models_info = json.load(f)
+
+  for i,model_info in models_info.items():
+    global name_en
+    name_en = model_info['name_en']
+
+def reset_options():
+  value_model_choice = models_info['Yuuka']['name_en']
+  value_speaker_id = models_info['Yuuka']['sid']
+  return value_model_choice,value_speaker_id
+
+def refresh_options():
+  get_options()
+  value_model_choice = models_info[speaker_choice]['name_en']
+  value_speaker_id = models_info[speaker_choice]['sid']
+  return value_model_choice,value_speaker_id
+
+def change_dropdown(choice):
+  global speaker_choice
+  speaker_choice = choice
+  global COVER
+  COVER = str(models_info[speaker_choice]['cover'])
+  global MODEL_PATH
+  MODEL_PATH = str(models_info[speaker_choice]['model_path'])
+  global MODEL_ZH_NAME
+  MODEL_ZH_NAME = str(models_info[speaker_choice]['name_zh'])
+  global EXAMPLE_TEXT
+  EXAMPLE_TEXT = str(models_info[speaker_choice]['example'])
+
+  speaker_id_change = gr.update(value=str(models_info[speaker_choice]['sid']))
+  cover_change = gr.update(value='<div align="center">'
+                f'<img style="width:auto;height:512px;" src="file/{COVER}">' if COVER else ""
+                f'<a><strong>{speaker_choice}</strong></a>'
+                                                                                           '</div>')
+  title_change = gr.update(value=
+                '<div align="center">'
+                f'<h3><a><strong>{"语音名称: "}{MODEL_ZH_NAME}</strong></a>'
+                f'<h3><strong>{"checkpoint: "}{speaker_choice}</strong>'
+                                                                                           '</div>')
+
+
+  lan_change = gr.update(value=str(models_info[speaker_choice]['language']))
+
+  example_change = gr.update(value=EXAMPLE_TEXT)
+
+  load_model()
+
+  return [speaker_id_change,cover_change,title_change,lan_change,example_change]
+
+class CustomEncoder(json.JSONEncoder):
+    def default(self, obj):
+        if isinstance(obj, Path):
+            return str(obj)
+        return super().default(obj)
+
+download_audio_js = """
+() =>{{
+    let root = document.querySelector("body > gradio-app");
+    if (root.shadowRoot != null)
+        root = root.shadowRoot;
+    let audio = root.querySelector("#tts-audio-{audio_id}").querySelector("audio");
+    let text = root.querySelector("#input-text-{audio_id}").querySelector("textarea");
+    if (audio == undefined)
+        return;
+    text = text.value;
+    if (text == undefined)
+        text = Math.floor(Math.random()*100000000);
+    audio = audio.src;
+    let oA = document.createElement("a");
+    oA.download = text.substr(0, 20)+'.wav';
+    oA.href = audio;
+    document.body.appendChild(oA);
+    oA.click();
+    oA.remove();
+}}
+"""
+
+
+
+
+
+
+
+
+if __name__ == '__main__':
+
+    with open("models/model_info.json", "r", encoding="utf-8") as f:
+        models_info = json.load(f)
+
+    for i, model_info in models_info.items():
+        name_en = model_info['name_en']
+
+
+    theme = gr.themes.Base()
+
+    with gr.Blocks(theme=theme) as interface:
+        with gr.Tab("Text to Speech"):
+            with gr.Column():
+                cover_markdown = gr.Markdown(
+                    '<div align="center">'
+                    f'<img style="width:auto;height:512px;" src="file/{COVER}">' if COVER else ""
+                                                                                               '</div>')
+                title_markdown = gr.Markdown(
+                    '<div align="center">'
+                    f'<h3><a><strong>{"语音名称: "}{MODEL_ZH_NAME}</strong></a>'
+                    f'<h3><strong>{"checkpoint: "}{speaker_choice}</strong>'
+                    '</div>')
+
+                with gr.Row():
+                    with gr.Column(scale=4):
+                        input_text = gr.Textbox(
+                            label="Input",
+                            lines=2,
+                            placeholder="Enter the text you want to process here",
+                            elem_id=f"input-text-en-{name_en.replace(' ', '')}",
+                            scale=2
+                        )
+                    with gr.Column(scale=1):
+                        gen_button = gr.Button("Generate", variant="primary")
+                        clear_input_button = gr.Button("Clear")
+
+                with gr.Row():
+                    with gr.Column(scale=2):
+                        lan = gr.Radio(label="Language", choices=LANGUAGES, value="JP")
+                        noise_scale = gr.Slider(minimum=0.1, maximum=1.0, step=0.1, label="Noise Scale (情感变化程度)",
+                                                value=0.6)
+                        noise_scale_w = gr.Slider(minimum=0.1, maximum=1.0, step=0.1, label="Noise Scale w (发音长度)",
+                                                  value=0.668)
+                        length_scale = gr.Slider(minimum=0.1, maximum=2.0, step=0.1, label="Length Scale (语速)",
+                                                 value=1.0)
+
+                    with gr.Column(scale=1):
+                        example_text_box = gr.Textbox(label="Example:",
+                                                      value=EXAMPLE_TEXT)
+
+                        output_audio = gr.Audio(label="Output", elem_id=f"tts-audio-en-{name_en.replace(' ', '')}")
+                        download_button = gr.Button("Download")
+
+                        # example = gr.Examples(
+                        #     examples = [EXAMPLE_TEXT],
+                        #     inputs=input_text,
+                        #     outputs = output_audio,
+                        #     fn=example_tts_fn,
+                        #     cache_examples=True
+                        # )
+
+            gen_button.click(
+                tts_fn,
+                inputs=[input_text, noise_scale, noise_scale_w, length_scale],
+                outputs=output_audio)
+            clear_input_button.click(
+                clear_input_text,
+                outputs=input_text
+            )
+            download_button.click(None, [], [], _js=download_audio_js.format(audio_id=f"en-{name_en.replace(' ', '')}"))
+
+        # ------------------------------------------------------------------------------------------------------------------------
+        with gr.Tab("AI Singer"):
+            input_text_singer = gr.Textbox()
+
+        # ------------------------------------------------------------------------------------------------------------------------
+        with gr.Tab("TTS with ChatGPT"):
+            input_text_gpt = gr.Textbox()
+
+        # ------------------------------------------------------------------------------------------------------------------------
+        with gr.Tab("Settings"):
+            with gr.Box():
+                gr.Markdown("""# Select Model""")
+                with gr.Row():
+                    with gr.Column(scale=5):
+                        model_choice = gr.Dropdown(label="Model",
+                                                   choices=[(model["name_en"]) for name, model in models_info.items()],
+                                                   interactive=True,
+                                                   value=models_info['Yuuka']['name_en']
+                                                   )
+                    with gr.Column(scale=5):
+                        speaker_id_choice = gr.Dropdown(label="Speaker ID",
+                                                        choices=[(str(model["sid"])) for name, model in
+                                                                 models_info.items()],
+                                                        interactive=True,
+                                                        value=str(models_info['Yuuka']['sid'])
+                                                        )
+
+                    with gr.Column(scale=1):
+                        refresh_button = gr.Button("Refresh", variant="primary")
+                        reset_button = gr.Button("Reset")
+
+            model_choice.change(fn=change_dropdown, inputs=model_choice,
+                                outputs=[speaker_id_choice, cover_markdown, title_markdown, lan, example_text_box])
+
+            refresh_button.click(fn=refresh_options, outputs=[model_choice, speaker_id_choice])
+            reset_button.click(reset_options, outputs=[model_choice, speaker_id_choice])
+
+            with gr.Box():
+                gr.Markdown("# Add Model\n"
+                            "> *为必填选项\n"
+                            "> 添加完成后将**checkpoints**文件放到对应生成的文件夹中"
+                            )
+
+                with gr.Row():
+                    # file = gr.Files(label = "VITS Model*", file_types=[".pth"])
+                    example_text = gr.Textbox(label="Example Text",
+                                              lines=16,
+                                              placeholder="Enter the example text here", )
+                    model_cover = gr.Image(label="Cover")
+
+                    with gr.Column():
+                        model_speaker_id = gr.Textbox(label="Speaker List*",
+                                                      placeholder="Single speaker model default=0")
+                        model_name_en = gr.Textbox(label="name_en*")
+                        model_name_cn = gr.Textbox(label="name_cn")
+                        model_language = gr.Dropdown(label="Language*",
+                                                     choices=LANGUAGES,
+                                                     interactive=True)
+                        with gr.Row():
+                            add_model_button = gr.Button("Add Model", variant="primary")
+                            clear_add_model_button = gr.Button("Clear")
+                with gr.Box():
+                    with gr.Row():
+                        message_box = gr.Textbox(label="Message")
+
+            add_model_button.click(add_model_fn,
+                                   inputs=[example_text, model_cover, model_speaker_id, model_name_en, model_name_cn,
+                                           model_language],
+                                   outputs=message_box
+                                   )
+            clear_add_model_button.click(clear_add_model_info,
+                                         outputs=[example_text, model_cover, model_speaker_id, model_name_en,
+                                                  model_name_cn, model_language]
+                                         )
+
+    interface.queue(concurrency_count=1).launch(debug=True)
+
+
+
+
+
+
+
+
+