from web.api import api_blueprint from pathlib import Path from gevent import pywsgi as wsgi from flask import Flask, Response, request, render_template from synthesizer.inference import Synthesizer from encoder import inference as encoder from vocoder.hifigan import inference as gan_vocoder from vocoder.wavernn import inference as rnn_vocoder import numpy as np import re from scipy.io.wavfile import write import io import base64 from flask_cors import CORS from flask_wtf import CSRFProtect def webApp(): # Init and load config app = Flask(__name__, instance_relative_config=True) app.config.from_object("web.config.default") app.config['RESTPLUS_MASK_SWAGGER'] = False app.register_blueprint(api_blueprint) # CORS(app) #允许跨域,注释掉此行则禁止跨域请求 csrf = CSRFProtect(app) csrf.init_app(app) syn_models_dirt = "synthesizer/saved_models" synthesizers = list(Path(syn_models_dirt).glob("**/*.pt")) synthesizers_cache = {} encoder.load_model(Path("encoder/saved_models/pretrained.pt")) gan_vocoder.load_model(Path("vocoder/saved_models/pretrained/g_hifigan.pt")) def pcm2float(sig, dtype='float32'): """Convert PCM signal to floating point with a range from -1 to 1. Use dtype='float32' for single precision. Parameters ---------- sig : array_like Input array, must have integral type. dtype : data type, optional Desired (floating point) data type. Returns ------- numpy.ndarray Normalized floating point data. See Also -------- float2pcm, dtype """ sig = np.asarray(sig) if sig.dtype.kind not in 'iu': raise TypeError("'sig' must be an array of integers") dtype = np.dtype(dtype) if dtype.kind != 'f': raise TypeError("'dtype' must be a floating point type") i = np.iinfo(sig.dtype) abs_max = 2 ** (i.bits - 1) offset = i.min + abs_max return (sig.astype(dtype) - offset) / abs_max # Cache for synthesizer @csrf.exempt @app.route("/api/synthesize", methods=["POST"]) def synthesize(): # TODO Implementation with json to support more platform # Load synthesizer if "synt_path" in request.form: synt_path = request.form["synt_path"] else: synt_path = synthesizers[0] print("NO synthsizer is specified, try default first one.") if synthesizers_cache.get(synt_path) is None: current_synt = Synthesizer(Path(synt_path)) synthesizers_cache[synt_path] = current_synt else: current_synt = synthesizers_cache[synt_path] print("using synthesizer model: " + str(synt_path)) # Load input wav wav_base64 = request.form["upfile_b64"] wav = base64.b64decode(bytes(wav_base64, 'utf-8')) wav = pcm2float(np.frombuffer(wav, dtype=np.int16), dtype=np.float32) encoder_wav = encoder.preprocess_wav(wav, 16000) embed, _, _ = encoder.embed_utterance(encoder_wav, return_partials=True) # Load input text texts = request.form["text"].split("\n") punctuation = '!,。、,' # punctuate and split/clean text processed_texts = [] for text in texts: for processed_text in re.sub(r'[{}]+'.format(punctuation), '\n', text).split('\n'): if processed_text: processed_texts.append(processed_text.strip()) texts = processed_texts # synthesize and vocode embeds = [embed] * len(texts) specs = current_synt.synthesize_spectrograms(texts, embeds) spec = np.concatenate(specs, axis=1) wav = gan_vocoder.infer_waveform(spec) # Return cooked wav out = io.BytesIO() write(out, Synthesizer.sample_rate, wav) return Response(out, mimetype="audio/wav") @app.route('/', methods=['GET']) def index(): return render_template("index.html") host = app.config.get("HOST") port = app.config.get("PORT") print(f"Web server: http://{host}:{port}") server = wsgi.WSGIServer((host, port), app) server.serve_forever() return app if __name__ == "__main__": webApp()