You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
74 lines
2.0 KiB
74 lines
2.0 KiB
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the
|
|
import base64
|
|
import math
|
|
|
|
|
|
def wav2base64(wav_file: str):
|
|
"""
|
|
read wave file and covert to base64 string
|
|
"""
|
|
with open(wav_file, 'rb') as f:
|
|
base64_bytes = base64.b64encode(f.read())
|
|
base64_string = base64_bytes.decode('utf-8')
|
|
return base64_string
|
|
|
|
|
|
def base64towav(base64_string: str):
|
|
pass
|
|
|
|
|
|
def self_check():
|
|
""" self check resource
|
|
"""
|
|
return True
|
|
|
|
|
|
def denorm(data, mean, std):
|
|
"""stream am model need to denorm
|
|
"""
|
|
return data * std + mean
|
|
|
|
|
|
def get_chunks(data, block_size, pad_size, step):
|
|
"""Divide data into multiple chunks
|
|
|
|
Args:
|
|
data (tensor): data
|
|
block_size (int): [description]
|
|
pad_size (int): [description]
|
|
step (str): set "am" or "voc", generate chunk for step am or vocoder(voc)
|
|
|
|
Returns:
|
|
list: chunks list
|
|
"""
|
|
if step == "am":
|
|
data_len = data.shape[1]
|
|
elif step == "voc":
|
|
data_len = data.shape[0]
|
|
else:
|
|
print("Please set correct type to get chunks, am or voc")
|
|
|
|
chunks = []
|
|
n = math.ceil(data_len / block_size)
|
|
for i in range(n):
|
|
start = max(0, i * block_size - pad_size)
|
|
end = min((i + 1) * block_size + pad_size, data_len)
|
|
if step == "am":
|
|
chunks.append(data[:, start:end, :])
|
|
elif step == "voc":
|
|
chunks.append(data[start:end, :])
|
|
else:
|
|
print("Please set correct type to get chunks, am or voc")
|
|
return chunks
|