ML/DL tools function library
Project description
Guang
Universal function library of scientific calculation.
Requirements
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
# Before install `guang`, you need to have all the requirements installed.
pip install guang
Nightly Build
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
guang cvt2wav INPUT OUTPUT
Use as function
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)
guang av_speed inputname outputname N --cut_frame=False
-
Fourier visualization
guang fourier
-
Fourier draw anything you want
-
FFT convolution
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:from guang.Utils.toolsFunc import dict_dotable a = {'a':{'b':1}} a = dict_dotable(a) print(a.a.b) >> 1
-
Usehas separated to pyprobarprobar
to display current progressfrom 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.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.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.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 thanleast_time
seconds. Note that this function does not work in the interactive interpreter because it usesmultiprocessing.pool.Pool
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
from guang.Voice.reduce import find_no_silence start, end, arg_start, arg_end = find_no_silence(filename)
-
Download wechat files.
from guang.wechat.Utils.download import downloads downloads(nickName='caloi', fileType='mp3', d_t=60)
-
Plots 3D Scatter:
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:
cd guang/ML/manifold python test_digits.py
python test_s_curve
-
:smiley:
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