Exemplos de createSlicesFromAudio em Python

Exemplo n.º 1

parser.add_argument("mode",
                    help="Trains or tests the CNN",
                    nargs='+',
                    choices=["train", "test", "slice", "identify"])
args = parser.parse_args()

print("--------------------------")
print("| ** Config ** ")
print("| Validation ratio: {}".format(validationRatio))
print("| Test ratio: {}".format(testRatio))
print("| Slices per genre: {}".format(filesPerGenre))
print("| Slice size: {}".format(sliceSize))
print("--------------------------")

if "slice" in args.mode:
    createSlicesFromAudio(trainPath)
    sys.exit()

#List genres
genres = os.listdir(trainPath + slicesPath)
genres = [
    filename for filename in genres
    if os.path.isdir(trainPath + slicesPath + filename)
]
nbClasses = len(genres)

#Create model
model = createModel(nbClasses, sliceSize)

if "train" in args.mode:

Exemplo n.º 2

Arquivo: main.py Projeto: athulkrishnan97/Raga_Classification

parser.add_argument("mode",
                    help="Trains or tests the CNN",
                    nargs='+',
                    choices=["train", "test", "slice", "predict"])
args = parser.parse_args()

print("--------------------------")
print("| ** Config ** ")
print("| Validation ratio: {}".format(validationRatio))
print("| Test ratio: {}".format(testRatio))
print("| Slices per genre: {}".format(filesPerGenre))
print("| Slice size: {}".format(sliceSize))
print("--------------------------")

if "slice" in args.mode:
    createSlicesFromAudio()
    sys.exit()

#List genres
genres = os.listdir(slicesPath)
genres = [
    filename for filename in genres if os.path.isdir(slicesPath + filename)
]
nbClasses = len(genres)

#Create model
model = createModel(nbClasses, sliceSize)

if "train" in args.mode:

    #Create or load new dataset

Exemplo n.º 3

Arquivo: main.py Projeto: withoutend/DeepAudioClassification

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("mode", help="Trains or tests the CNN", nargs='+', choices=["train","test","slice"])
args = parser.parse_args()

print("--------------------------")
print("| ** Config ** ")
print("| Validation ratio: {}".format(validationRatio))
print("| Test ratio: {}".format(testRatio))
print("| Slices per genre: {}".format(filesPerGenre))
print("| Slice size: {}".format(sliceSize))
print("--------------------------")

if "slice" in args.mode:
	createSlicesFromAudio()
	sys.exit()

#List genres
genres = os.listdir(slicesPath)
genres = [filename for filename in genres if os.path.isdir(slicesPath+filename)]
nbClasses = len(genres)

#Create model 
model = createModel(nbClasses, sliceSize)

if "train" in args.mode:

	#Create or load new dataset
	train_X, train_y, validation_X, validation_y = getDataset(filesPerGenre, genres, sliceSize, validationRatio, testRatio, mode="train")