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Functions289 in github.com/MTG/DeepConvSep

⨍ Functions 289◇ Types & classes 21
↓ 23 callersMethodcompute_transform
Compute the features for a given set of audio signals. The audio signal \"audio\" is a numpy array with the shape (t,i) - t is ti
transform.py:80
↓ 23 callersMethodloadTensor
Loads a binary .data file
dataset.py:680
↓ 17 callersMethodcompute_inverse
(self, mag, phase)
transform.py:156
↓ 16 callersMethodcompute_file
(self,audio, phase=False)
transform.py:153
↓ 14 callersMethodgetMax
(self,inputs=True)
dataset.py:581
↓ 14 callersMethodgetMean
(self,inputs=True)
dataset.py:567
↓ 14 callersMethodgetStd
(self,inputs=True)
dataset.py:574
↓ 13 callersFunctionfun
(f,q_in,q_out)
dataset.py:40
↓ 11 callersMethodloadTensor
Loads a binary .data file
dataset_old.py:635
↓ 10 callersMethodsaveTensor
Saves a numpy array as a binary file
dataset.py:707
↓ 8 callersFunction_parser
()
climate/flags.py:55
↓ 5 callersMethod__init__
(self, path_transform_in=None, path_transform_out=None, sampleRate=44100, exclude_list=[], nsamples=0,
dataset.py:112
↓ 5 callersMethodfilterSpec
(self,mag,notes,start,stop)
dataset.py:759
↓ 5 callersMethodsaveTensor
Saves a numpy array as a binary file
dataset_old.py:661
↓ 4 callersMethodbuildPitch
(self,mag,notes,start,stop)
dataset.py:796
↓ 4 callersMethodgetMin
(self,inputs=True)
dataset.py:588
↓ 4 callersMethoditerate
This is called whenever you need to return a batch, e.g. the callable that generates numpy arrays
dataset_old.py:173
↓ 4 callersMethoditerate
This is called whenever you need to return a batch, e.g. the callable that generates numpy arrays
dataset.py:181
↓ 3 callersMethodinitOutput
Allocate memory for read data, where \"size\" is the number of examples of size \"time_context\"
dataset_old.py:480
↓ 3 callersMethodloadBatches
Loads more batches from the disk, if the batches from the memory are exhausted
dataset.py:233
↓ 3 callersMethodloadFile
reads a .data file and splits into batches
dataset_old.py:356
↓ 3 callersMethodloadFile
reads a .data file and splits into batches
dataset.py:383
↓ 3 callersFunctionload_model
(filename)
examples/dsd100_2ch_ILD/trainCNN_ILD_DSD100_3stages.py:52
↓ 3 callersMethodsaveTensor
Saves a numpy array as a binary file
transform.py:159
↓ 3 callersFunctionsave_model
(filename, model)
examples/dsd100_2ch_ILD/trainCNN_ILD_DSD100_3stages.py:58
↓ 3 callersFunctionstr2midi
Given a note string name (e.g. "Bb4"), returns its MIDI pitch number.
util.py:581
↓ 2 callersMethod__init__
(self, path_transform_in=None, path_transform_out=None, sampleRate=44100, exclude_list=[], nsamples=0,
dataset_old.py:112
↓ 2 callersFunctioncompute_inverse
(mag, phase, frameSize=1024, hopSize=512, sampleRate=44100, window=np.hanning)
examples/ikala/separate_ikala.py:36
↓ 2 callersMethodfilterSpec
(self,mag,notes,start,stop)
dataset_old.py:713
↓ 2 callersMethodgenBatches
This function is called by \"loadBatches\" to generate batches from the disk
dataset_old.py:241
↓ 2 callersMethodgenBatches
This function is called by \"loadBatches\" to generate batches from the disk
dataset.py:260
↓ 2 callersMethodgetAudio
(self,max_duration=0,sampleRate=44100)
rwc.py:154
↓ 2 callersMethodgetNote
(self,nr,dynamics='F',style='NO',case=1)
rwc.py:103
↓ 2 callersMethodgetNum
For a single .data file computes the number of examples of size \"time_context\" that can be created
dataset.py:596
↓ 2 callersFunctionget_logger
Get or create a logger.
climate/log.py:57
↓ 2 callersMethodget_shape
Reads a .shape file
dataset_old.py:649
↓ 2 callersMethodget_shape
Reads a .shape file
dataset.py:695
↓ 2 callersFunctiongetfreqs
(midinote,interval=30,tuning_freq=440,nharmonics=20,ismidi=True)
util.py:183
↓ 2 callersMethodinitBatches
Allocates memory for the output
dataset_old.py:605
↓ 2 callersMethodinitBatches
Allocates memory for the output
dataset.py:650
↓ 2 callersMethodinitFeatures
(self,size)
dataset.py:526
↓ 2 callersMethodloadBatches
Loads more batches from the disk, if the batches from the memory are exhausted
dataset_old.py:214
↓ 2 callersFunctionload_model
(filename)
examples/bach10_scoreinformed/trainCNNrwc.py:53
↓ 2 callersFunctionload_model
(filename)
examples/dsd100_2ch_ILD/trainCNN_ILD_DSD100.py:52
↓ 2 callersFunctionmain
(argv)
examples/dsd100/separate_dsd.py:316
↓ 2 callersFunctionremove_overlap
(ranges)
util.py:140
↓ 2 callersFunctionsave_model
(filename, model)
examples/dsd100_2ch_ILD/trainCNN_ILD_DSD100.py:58
↓ 2 callersMethodshuffleBatches
Shuffle batches
dataset_old.py:462
↓ 2 callersMethodshuffleBatches
Shuffle batches
dataset.py:491
↓ 2 callersFunctionsinebell
window = sinebell(lengthWindow) Computes a \"sinebell\" window function of length L=lengthWindow The formula is: .. math::
transform.py:35
↓ 2 callersFunctionsinebell
(lengthWindow)
examples/ikala/separate_ikala.py:44
↓ 2 callersFunctionsinebell
(lengthWindow)
examples/dsd100/separate_dsd.py:44
↓ 2 callersFunctionsinebell
(lengthWindow)
examples/bach10/separate_bach10.py:44
↓ 2 callersFunctionsinebell
(lengthWindow)
examples/bach10_scoreinformed/separate_bach10.py:44
↓ 2 callersFunctionsinebell
(lengthWindow)
examples/hiphopss/separate_hhds.py:44
↓ 2 callersFunctionslicefft_slices
(pitch,size,interval=30,tuning_freq=440,nharmonics=20,fmin=25,fmax=18000,iscale = 'lin',sampleRate=44100)
util.py:171
↓ 1 callersMethod__init__
(self, ttype='fft', bins=48, frameSize=1024, hopSize=256, tffmin=25, tffmax=18000, iscale = 'lin', suffix='',
transform.py:68
↓ 1 callersFunctionbuild_ca
(input_var=None, batch_size=32,time_context=30,feat_size=1025)
examples/ikala/separate_ikala.py:172
↓ 1 callersFunctionbuild_ca
Builds a network with lasagne Parameters ---------- input_var : Theano tensor The input for the network batch_size :
examples/dsd100/separate_dsd.py:172
↓ 1 callersFunctionbuild_ca
Builds a network with lasagne Parameters ---------- input_var : Theano tensor The input for the network batch_size : int
examples/bach10/separate_bach10.py:172
↓ 1 callersFunctionbuild_ca
Builds a network with lasagne Parameters ---------- input_var : Theano tensor The input for the network batch_size : int
examples/bach10_scoreinformed/separate_bach10.py:388
↓ 1 callersFunctionbuild_ca
Builds a network with lasagne Parameters ---------- input_var : Theano tensor The input for the network batch_size :
examples/hiphopss/separate_hhds.py:171
↓ 1 callersFunctioncompute_file
(audio, phase=False, frameSize=1024, hopSize=512, sampleRate=44100, window=np.hanning)
examples/ikala/separate_ikala.py:24
↓ 1 callersFunctioncompute_file
(audio, phase=False, frameSize=1024, hopSize=512, sampleRate=44100, window=np.hanning)
examples/dsd100/separate_dsd.py:24
↓ 1 callersFunctioncompute_file
(audio, phase=False, frameSize=1024, hopSize=512, sampleRate=44100, window=np.hanning)
examples/bach10/separate_bach10.py:24
↓ 1 callersFunctioncompute_file
(audio, phase=False, frameSize=1024, hopSize=512, sampleRate=44100, window=np.hanning)
examples/bach10_scoreinformed/separate_bach10.py:24
↓ 1 callersFunctioncompute_file
(audio, phase=False, frameSize=1024, hopSize=512, sampleRate=44100, window=np.hanning)
examples/hiphopss/separate_hhds.py:24
↓ 1 callersFunctioncompute_inverse
(mag, phase, frameSize=1024, hopSize=512, sampleRate=44100, window=np.hanning)
examples/dsd100/separate_dsd.py:36
↓ 1 callersFunctioncompute_inverse
(mag, phase, frameSize=1024, hopSize=512, sampleRate=44100, window=np.hanning)
examples/bach10/separate_bach10.py:36
↓ 1 callersFunctioncompute_inverse
(mag, phase, frameSize=1024, hopSize=512, sampleRate=44100, window=np.hanning)
examples/bach10_scoreinformed/separate_bach10.py:36
↓ 1 callersFunctioncompute_inverse
(mag, phase, frameSize=1024, hopSize=512, sampleRate=44100, window=np.hanning)
examples/hiphopss/separate_hhds.py:36
↓ 1 callersFunctionenable_default_logging
Set up logging in the typical way. Parameters ---------- default_level : str, optional Logging level. Defaults to INFO. strea
climate/log.py:89
↓ 1 callersFunctionexpandMidi
(instrument,FilePath,beginTime,finishTime,interval,tuning_freq,nharmonics,samplerate,hop,window,timeSpan_on,ti
examples/bach10_scoreinformed/separate_bach10.py:203
↓ 1 callersFunctionfilterSpec
(mag,notes,ninst,start,stop,timbre_model_path=None)
examples/bach10_scoreinformed/separate_bach10.py:172
↓ 1 callersMethodfilterSpec
(self,mag,notes,start,stop)
dataset.py:839
↓ 1 callersFunctiongenerate_overlapadd
(allmix,input_size=513,time_context=30, overlap=10,batch_size=32,sampleRate=44100)
examples/ikala/separate_ikala.py:114
↓ 1 callersFunctiongenerate_overlapadd
(allmix,input_size=513,time_context=30, overlap=10,batch_size=32,sampleRate=44100)
examples/dsd100/separate_dsd.py:114
↓ 1 callersFunctiongenerate_overlapadd
(allmix,input_size=513,time_context=30, overlap=10,batch_size=32,sampleRate=44100)
examples/bach10/separate_bach10.py:114
↓ 1 callersFunctiongenerate_overlapadd
(allmix,input_size=513,time_context=30, overlap=10,batch_size=32,sampleRate=44100)
examples/hiphopss/separate_hhds.py:114
↓ 1 callersMethodgetCombos
(self)
examples/bach10/compute_features_bach10rwc.py:89
↓ 1 callersMethodgetCombos
(self)
examples/bach10_scoreinformed/compute_features_bach10rwc.py:93
↓ 1 callersMethodgetFeatureSize
Returns the feature size of the input and of the output to the neural network
dataset_old.py:515
↓ 1 callersMethodgetFeatureSize
Returns the feature size of the input and of the output to the neural network
dataset.py:543
↓ 1 callersMethodgetFeatureSize
Returns the feature size of the input and of the output to the neural network
dataset.py:1048
↓ 1 callersMethodgetInfo
(self)
rwc.py:140
↓ 1 callersFunctiongetMidiNum
(instrument,FilePath,beginTime,finishTime)
examples/bach10_scoreinformed/separate_bach10.py:306
↓ 1 callersMethodgetNextIndex
Returns how many batches/sequences to load from each .data file
dataset_old.py:320
↓ 1 callersMethodgetNextIndex
Returns how many batches/sequences to load from each .data file
dataset.py:344
↓ 1 callersMethodgetNum
For a single .data file computes the number of examples of size \"time_context\" that can be created
dataset_old.py:551
↓ 1 callersMethodgetWavs
(self)
rwc.py:66
↓ 1 callersMethodget_shape
Reads a .shape file
transform.py:187
↓ 1 callersMethodinitBatches
Allocates memory for the output
dataset.py:1122
↓ 1 callersMethodinitFeatures
(self,size)
dataset_old.py:498
↓ 1 callersMethodinitMasks
(self,size)
dataset.py:522
↓ 1 callersMethodinitMasks
(self,size)
dataset.py:1044
↓ 1 callersMethodinitOutput
Allocate memory for read data, where \"size\" is the number of examples of size \"time_context\"
dataset.py:509
↓ 1 callersMethodinitOutput
Allocate memory for read data, where \"size\" is the number of examples of size \"time_context\"
dataset.py:1031
↓ 1 callersMethodinitPitches
(self,size)
dataset.py:518
↓ 1 callersMethodinitPitches
(self,size)
dataset.py:1040
↓ 1 callersFunctionistft_norm
data = istft_norm(X,window=sinebell(2048),hopsize=1024.0,nfft=2048.0,fs=44100) Computes an inverse of the short time Fourier transform (STFT
transform.py:337
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