Add files via upload

2023-08-03 18:42:59 +08:00
parent 304f1b03a8
commit 7775f24070
1 changed files with 110 additions and 0 deletions
--- a/server.py
+++ b/server.py
@@ -0,0 +1,110 @@
+from flask import Flask, request, Response
+from io import BytesIO
+import ffmpeg
+import base64
+import os
+import sys
+import json
+import math
+import torch
+from torch import nn
+from torch.nn import functional as F
+from torch.utils.data import DataLoader
+
+import time
+import commons
+import utils
+from models import SynthesizerTrn
+from text.symbols import symbols
+from text import text_to_sequence
+from scipy.io import wavfile
+
+# Get ffmpeg path
+ffmpeg_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "ffmpeg")
+
+# Flask Init
+app = Flask(__name__)
+app.config['JSON_AS_ASCII'] = False
+# Text Preprocess
+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
+
+# Load Generator
+hps_mt = utils.get_hparams_from_file("/GPUFS/sysu_hpcedu_123/vits/configs/genshin_xm37.json")
+
+net_g_mt = SynthesizerTrn(
+    len(symbols),
+    hps_mt.data.filter_length // 2 + 1,
+    hps_mt.train.segment_size // hps_mt.data.hop_length,
+    n_speakers=hps_mt.data.n_speakers,
+    **hps_mt.model).cuda()
+_ = net_g_mt.eval()
+
+_ = utils.load_checkpoint("/GPUFS/sysu_hpcedu_123/vits/logs/xm37/G_xm37_361200.pth", net_g_mt, None)
+
+npcList = ['空', '荧', '派蒙', '纳西妲', '阿贝多', '温迪', '枫原万叶', '钟离', '荒泷一斗', '八重神子', '艾尔海森', '提纳里', '迪希雅', '卡维', '宵宫', '莱依拉', '赛诺', '诺艾尔', '托马', '凝光', '莫娜', '北斗', '神里绫华', '雷电将军', '芭芭拉', '鹿野院平藏', '五郎', '迪奥娜', '凯亚', '安柏', '班尼特', '琴', '柯莱', '夜兰', '妮露', '辛焱', '珐露珊', '魈', '香菱', '达达利亚', '砂糖', '早柚', '云堇', '刻晴', '丽莎', '迪卢克', '烟绯', '重云', '珊瑚宫心海', '胡桃', '可莉', '流浪者', '久岐忍', '神里绫人', '甘雨', '戴因斯雷布', '优菈', '菲谢尔', '行秋', '白术', '九条裟罗', '雷泽', '申鹤', '迪娜泽黛', '凯瑟琳', '多莉', '坎蒂丝', '萍姥姥', '罗莎莉亚', '留云借风真君', '绮良良', '瑶瑶', '七七', '奥兹', '米卡', '夏洛蒂', '埃洛伊', '博士', '女士', '大慈树王', '三月七', '娜塔莎', '希露瓦', '虎克', '克拉拉', '丹恒', '希儿', '布洛妮娅', '瓦尔特', '杰帕德', '佩拉', '姬子', '艾丝妲', '白露', '星', '穹', '桑博', '伦纳德', '停云', '罗刹', '卡芙卡', '彦卿', '史瓦罗', '螺丝咕姆', '阿兰', '银狼', '素裳', '丹枢', '黑塔', '景元', '帕姆', '可可利亚', '半夏', '符玄', '公输师傅', '奥列格', '青雀', '大毫', '青镞', '费斯曼', '绿芙蓉', '镜流', '信使', '丽塔', '失落迷迭', '缭乱星棘', '伊甸', '伏特加女孩', '狂热蓝调', '莉莉娅', '萝莎莉娅', '八重樱', '八重霞', '卡莲', '第六夜想曲', '卡萝尔', '姬子', '极地战刃', '布洛妮娅', '次生银翼', '理之律者', '真理之律者', '迷城骇兔', '希儿', '魇夜星渊', '黑希儿', '帕朵菲莉丝', '天元骑英', '幽兰黛尔', '德丽莎', '月下初拥', '朔夜观星', '暮光骑士', '明日香', '李素裳', '格蕾修', '梅比乌斯', '渡鸦', '人之律者', '爱莉希雅', '爱衣', '天穹游侠', '琪亚娜', '空之律者', '终焉之律者', '薪炎之律者', '云墨丹心', '符华', '识之律者', '维尔薇', '始源之律者', '芽衣', '雷之律者', '苏莎娜', '阿波尼亚', '陆景和', '莫弈', '夏彦', '左然', '标贝']
+
+@app.route("/",methods=['GET','POST'])
+def main():
+    if request.method == 'GET':
+        try:
+            speaker = request.args.get('speaker')
+            text = request.args.get('text').replace("/n","")
+            noise = float(request.args.get("noise", 0.5))
+            noisew = float(request.args.get("noisew", 0.6))
+            length = float(request.args.get("length", 1.3))
+            if length >= 2:
+                return "Too big length"
+            if len(text) >=200:
+                return "Too long text"
+            fmt = request.args.get("format", "wav")
+            if None in (speaker, text):
+                return "Missing Parameter"
+            if fmt not in ("mp3", "wav"):
+                return "Invalid Format"
+        except:
+            return "Invalid Parameter"
+
+        stn_tst_mt = get_text(text, hps_mt)
+
+        with torch.no_grad():
+            x_tst_mt = stn_tst_mt.cuda().unsqueeze(0)
+            x_tst_mt_lengths = torch.LongTensor([stn_tst_mt.size(0)]).cuda()
+            sid_mt = torch.LongTensor([npcList.index(speaker)]).cuda()
+            audio_mt = net_g_mt.infer(x_tst_mt, x_tst_mt_lengths, sid=sid_mt, noise_scale=noise, noise_scale_w=noisew, length_scale=length)[0][0,0].data.cpu().float().numpy()
+
+        wav = BytesIO()
+        wavfile.write(wav, hps_mt.data.sampling_rate, audio_mt)
+        torch.cuda.empty_cache()
+        if fmt == "mp3":
+            process = (
+	        ffmpeg
+            .input("pipe:", format='wav', channel_layout="mono")
+            .output("pipe:", format='mp3', audio_bitrate="320k")
+            .run_async(pipe_stdin=True, pipe_stdout=True, pipe_stderr=True, cmd=ffmpeg_path)
+        )
+            out, _ = process.communicate(input=wav.read())
+            return Response(out, mimetype="audio/mpeg")
+        return Response(wav.read(), mimetype="audio/wav")
+    elif request.method == 'POST':
+        receive = request.get_data(as_text=True)
+        data = json.loads(receive)
+        speaker = data["speaker"]
+        text = data["text"].replace("/n","")
+        stn_tst_mt = get_text(text, hps_mt)
+
+        with torch.no_grad():
+            x_tst_mt = stn_tst_mt.cuda().unsqueeze(0)
+            x_tst_mt_lengths = torch.LongTensor([stn_tst_mt.size(0)]).cuda()
+            sid_mt = torch.LongTensor([npcList.index(speaker)]).cuda()
+            audio_mt = net_g_mt.infer(x_tst_mt, x_tst_mt_lengths, sid=sid_mt, noise_scale=0.667, noise_scale_w=0.8, length_scale=1.15)[0][0,0].data.cpu().float().numpy()
+
+        wav = BytesIO()
+        wavfile.write(wav, hps_mt.data.sampling_rate, audio_mt)
+        torch.cuda.empty_cache()
+        return Response(base64.b64encode(wav.read()))
+        #return Response(wav.read(), mimetype="audio/wav")