https://github.com/kenyony/guang
Universal Function Library of Scientific Calculation
https://github.com/kenyony/guang
deep-learning machine-learning tts utility-library voice-processing
Last synced: 4 months ago
JSON representation
Universal Function Library of Scientific Calculation
- Host: GitHub
- URL: https://github.com/kenyony/guang
- Owner: KenyonY
- License: gpl-3.0
- Created: 2019-10-26T12:03:04.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2021-05-24T03:47:30.000Z (about 4 years ago)
- Last Synced: 2025-02-08T16:45:59.666Z (4 months ago)
- Topics: deep-learning, machine-learning, tts, utility-library, voice-processing
- Language: Jupyter Notebook
- Homepage: https://beidongjiedeguang.github.io/guang
- Size: 88.4 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Guang
[](https://pypi.org/project/guang)
[](https://www.python.org/)
[](LICENSE)
[](https://github.com/beidongjiedeguang)
Universal function library of scientific calculation.
## Requirements
```python
Python 3
CUDA >= 10.0
PyTorch >= 1.0
Tensorflow >= 1.12.0
opencv-python
pydub
librosa
pyworld
soundfile
pypinyin
pomegranate
python-Levenshtein
streamlit
pyprobar
fire
```
## Installation
```python
# Before install `guang`, you need to have all the requirements installed.
pip install guang
```
*Nightly* Build
```bash
git clone https://github.com/beidongjiedeguang/guang.git
cd guang
python ./night_workflow.py
```
## Examples
- Convert audio in .mp3/ .wav format to (sample rate=16k, single channel) .wav format
**Use in bash/shell**
```bash
guang cvt2wav INPUT OUTPUT
```
**Use as function**
```python
from guang.Voice.convert import cvt2wav
cvt2wav(input_name, output_name, sr=16000)
# Multi-process
from guang.Voice.convert import multi_cvt2wav
multi_cvt2wav(PATH1, PATH2,sr=16000, n_cpu=None)
```
* **Let the video play at N times speed** (install ffmpeg first)
```bash
guang av_speed inputname outputname N --cut_frame=False
```
* **Fourier visualization**
```bash
guang fourier
```
* **Fourier draw anything**
* **FFT convolution**
```python
from guang.sci import fft
A = np.random.rand(100, 100)
B = np.random.rand(100, 100)
fft.fft_conv2d(A, B)
```
* Use `dict_dotable` to convert a dictionary to dot-able dictionary:
```python
from guang.Utils.toolsFunc import dict_dotable
a = {'a':{'b':1}}
a = dict_dotable(a)
print(a.a.b)
>> 1
```
* ~~Use `probar` to display current progress~~ has separated to [pyprobar](https://github.com/beidongjiedeguang/python-progress-bar)
```python
from guang.Utils.bar import bar, probar
for idx, x in probar(range(10)):
time.sleep(0.8)
>> 100.00% |█████████████████████████████| 0'7.2"|0'7.2" ETC: 12-2 23:59:8
N = 1024
a = np.linspace(2, 5, N)
for idx, i in enumerate(a):
time.sleep(0.01)
bar(idx, N)
>> 100.00% |█████████████████████████████| 0:00:00|0:00:10 ETC: 02-19 20:33:34
```
* `@broadcast` broadcast a non-broadcast function.
```python
from guang.Utils.toolsFunc import broadcast
@broadcast
def f(x):
# A function that can map only a single element
if x==1 or x==0:
return x
else:
return f(x-1)+f(x-2)
>> f([2,4,10])
>> array([1, 3, 832040], dtype=object)
```
* `download` download files from google drive.
```python
from guang.Utils.google import download
url = "https://drive.google.com/open?id=1eU57Fkv1DBEOqi-iOs1AebD02FqVDY23"
outname = "filename.zip"
download(url, outname)
```
* `txt2ph` Convert Chinese characters to phoneme.
```python
from guang.Voice.txt2pinyin import txt2ph
txt2ph('你好，我是光')
>> [('n', 'i3'), ('h', 'ao3'), ('sp1',), ('uo3',), ('sh', 'ii4'), ('g', 'uang1')]
```
* `reduce_from_duration` Remove files with duration less than `least_time` seconds.
Note that this function does not work in the interactive interpreter because it uses [`multiprocessing.pool.Pool`](https://docs.python.org/zh-cn/3/library/multiprocessing.html#multiprocessing.pool.Pool)
```python
from guang.Voice.reduce import reduce_from_duration
reduced_list = reduce_from_duration(path_list, least_time=2)
print(len(path_list), len(reduced_list))
>> (6889, 6714)
```
* Find NOT silence part of a sound file: `find_no_silence`
```python
from guang.Voice.reduce import find_no_silence
start, end, arg_start, arg_end = find_no_silence(filename)
```
* Download wechat files.
```python
from guang.wechat.Utils.download import downloads
downloads(nickName='caloi', fileType='mp3', d_t=60)
```
* Plots 3D Scatter:
```python
from guang.Utils.plotly import Scatter3d
from guang.Utils.interesting import Lorenz
trace = Lorenz.Trace()
x,y,z = trace[:,0], trace[:,1], trace[:,2]
fig = Scatter3d()
fig.scatter3d(x,y,z,mode="lines+markers",color_line=z,color_marker=None,marker_size=2)
fig.show()
```
* Data dimension reduction:
```bash
cd guang/ML/manifold
python test_digits.py
```
```bash
python test_s_curve
```
* :smiley: