Delete server.py

server.py

@@ -1,182 +0,0 @@
-from flask import Flask, request, Response
-from io import BytesIO
-import torch
-from av import open as avopen
-from typing import Dict, List
-import re_matching
-import utils
-from infer import infer, get_net_g, latest_version
-from scipy.io import wavfile
-import gradio as gr
-from config import config
-
-# Flask Init
-app = Flask(__name__)
-app.config["JSON_AS_ASCII"] = False
-
-
-def replace_punctuation(text, i=2):
-    punctuation = "，。？！"
-    for char in punctuation:
-        text = text.replace(char, char * i)
-    return text
-
-
-def wav2(i, o, format):
-    inp = avopen(i, "rb")
-    out = avopen(o, "wb", format=format)
-    if format == "ogg":
-        format = "libvorbis"
-
-    ostream = out.add_stream(format)
-
-    for frame in inp.decode(audio=0):
-        for p in ostream.encode(frame):
-            out.mux(p)
-
-    for p in ostream.encode(None):
-        out.mux(p)
-
-    out.close()
-    inp.close()
-
-
-net_g_List = []
-hps_List = []
-# 模型角色字典
-# 使用方法 chr_name = chrsMap[model_id][chr_id]
-chrsMap: List[Dict[int, str]] = list()
-
-# 加载模型
-models = config.server_config.models
-for model in models:
-    hps_List.append(utils.get_hparams_from_file(model["config"]))
-    # 添加角色字典
-    chrsMap.append(dict())
-    for name, cid in hps_List[-1].data.spk2id.items():
-        chrsMap[-1][cid] = name
-    version = (
-        hps_List[-1].version if hasattr(hps_List[-1], "version") else latest_version
-    )
-    net_g_List.append(
-        get_net_g(
-            model_path=model["model"],
-            version=version,
-            device=model["device"],
-            hps=hps_List[-1],
-        )
-    )
-
-
-def generate_audio(
-    slices,
-    sdp_ratio,
-    noise_scale,
-    noise_scale_w,
-    length_scale,
-    speaker,
-    language,
-):
-    audio_list = []
-    silence = np.zeros(hps.data.sampling_rate // 2, dtype=np.int16)
-    with torch.no_grad():
-        for piece in slices:
-            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
-    return audio_list
-
-
-@app.route("/")
-def main():
-    try:
-        model = int(request.args.get("model"))
-        speaker = request.args.get("speaker", "")  # 指定人物名
-        speaker_id = request.args.get("speaker_id", None)  # 直接指定id
-        text = request.args.get("text").replace("/n", "")
-        sdp_ratio = float(request.args.get("sdp_ratio", 0.2))
-        noise = float(request.args.get("noise", 0.5))
-        noisew = float(request.args.get("noisew", 0.6))
-        length = float(request.args.get("length", 1.2))
-        language = request.args.get("language")
-        if length >= 2:
-            return "Too big length"
-        if len(text) >= 250:
-            return "Too long text"
-        fmt = request.args.get("format", "wav")
-        if None in (speaker, text):
-            return "Missing Parameter"
-        if fmt not in ("mp3", "wav", "ogg"):
-            return "Invalid Format"
-        if language not in ("JP", "ZH", "EN", "mix"):
-            return "Invalid language"
-    except:
-        return "Invalid Parameter"
-
-    if speaker_id is not None:
-        if speaker_id.isdigit():
-            speaker = chrsMap[model][int(speaker_id)]
-    audio_list = []
-    if language == "mix":
-        bool_valid, str_valid = re_matching.validate_text(text)
-        if not bool_valid:
-            return str_valid, (
-                hps.data.sampling_rate,
-                np.concatenate([np.zeros(hps.data.sampling_rate // 2)]),
-            )
-        result = re_matching.text_matching(text)
-        for one in result:
-            _speaker = one.pop()
-            for lang, content in one:
-                audio_list.extend(
-                    generate_audio(
-                        content.split("|"),
-                        sdp_ratio,
-                        noise_scale,
-                        noise_scale_w,
-                        length_scale,
-                        _speaker,
-                        lang,
-                    )
-                )
-    else:
-        audio_list.extend(
-            generate_audio(
-                text.split("|"),
-                sdp_ratio,
-                noise_scale,
-                noise_scale_w,
-                length_scale,
-                speaker,
-                language,
-            )
-        )
-
-    audio_concat = np.concatenate(audio_list)
-    with BytesIO() as wav:
-        wavfile.write(wav, hps_List[model].data.sampling_rate, audio_concat)
-        torch.cuda.empty_cache()
-        if fmt == "wav":
-            return Response(wav.getvalue(), mimetype="audio/wav")
-        wav.seek(0, 0)
-        with BytesIO() as ofp:
-            wav2(wav, ofp, fmt)
-            return Response(
-                ofp.getvalue(), mimetype="audio/mpeg" if fmt == "mp3" else "audio/ogg"
-            )
-
-
-if __name__ == "__main__":
-    app.run(port=config.server_config.port, server_name="0.0.0.0")