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# -*- coding: utf-8 -*-
import numpy as np
import soundfile
import audresample
import text_utils
import re
import srt
import subprocess
import markdown
import json
from pathlib import Path
from types import SimpleNamespace
from flask import Flask, request, send_from_directory
from flask_cors import CORS
from audiocraft.audiogen import AudioGen, audio_write
sound_generator = AudioGen.get_pretrained('facebook/audiogen-medium')
sound_generator.set_generation_params(duration=4)
# ====STYLE VECTOR====
# AFFECTIVE = True
# VOICE = 'en_UK/apope_low' # en_US/m-ailabs_low#mary_ann
# _dir = '/' if AFFECTIVE else '_v2/'
# precomputed_style_vector = msinference.compute_style(
# 'assets/wavs/style_vector' + _dir + VOICE.replace(
# '/', '_').replace(
# '#', '_').replace(
# 'cmu-arctic', 'cmu_arctic').replace(
# '_low', '') + '.wav')
# print('\n STYLE VECTOR \n', precomputed_style_vector.shape)
# ==== STYLE VECTOR
CACHE_DIR = 'flask_cache/'
Path(CACHE_DIR).mkdir(parents=True, exist_ok=True)
def tts_multi_sentence(scene=None):
if scene is not None:
sound_background = sound_generator.generate([scene])[0]
sound_background = audio_write(None,
sound_background.cpu(),
24000, # Same as styleTTs sample_rate,
strategy="loudness",
loudness_compressor=True).detach().cpu().numpy()[0, :]
else:
sound_background = None
# # StyleTTS2
# if ('en_US/' in voice) or ('en_UK/' in voice) or (voice is None):
# assert precomputed_style_vector is not None, 'For affective TTS, style vector is needed.'
# x = []
# for _sentence in text:
# x.append(msinference.inference(_sentence,
# precomputed_style_vector,
# alpha=0.3,
# beta=0.7,
# diffusion_steps=7,
# embedding_scale=1))
# x = np.concatenate(x)
# return overlay(x, sound_background)
return sound_background
app = Flask(__name__)
cors = CORS(app)
@app.route("/")
def index():
with open('README.md', 'r') as f:
return markdown.markdown(f.read())
@app.route("/", methods=['GET', 'POST', 'PUT'])
def serve_wav():
# https://stackoverflow.com/questions/13522137/in-flask-convert-form-post-
# object-into-a-representation-suitable-for-mongodb
r = request.form.to_dict(flat=False)
args = SimpleNamespace(
text=None if r.get('text') is None else r.get('text'), # string not file?
scene=r.get('scene')[0]
)
# print('\n==RECOMPOSED as \n',request.data,request.form,'\n==')
x = tts_multi_sentence(args.scene)
# print('\n\n\n\n Obtai TTS output shape', x.shape)
OUT_FILE = 'tmp.wav'
soundfile.write(CACHE_DIR + OUT_FILE, x, 24000)
# send server's output as default file -> srv_result.xx
print(f'\n=SERVER saved as {OUT_FILE=}\n')
response = send_from_directory(CACHE_DIR, path=OUT_FILE)
response.headers['suffix-file-type'] = OUT_FILE
return response
if __name__ == "__main__":
app.run(host="0.0.0.0")
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