Comments (4)
Check if you have images in the directory you have used for DataGenerator
from music-genre-classification.
directory = "/content/drive/MyDrive/spectrograms3sec/train/"
for g in genre:
filenames = os.listdir(os.path.join(directory,f"{g}"))
random.shuffle(filenames)
test_files = filenames[0:100]
for f in test_files:
shutil.move(directory + f"{g}"+ "/" + f,"/content/drive/MyDrive/spectrograms3sec/test/" + f"{g}")
when i run this code there was neither any output nor any error .
from music-genre-classification.
i thought above code will automatically put the data inside the train directory
from music-genre-classification.
i need ur help. also the method u have used is exactly what i had thought (input as mel spetrogram to train the model). that's why i followed ur code.
from music-genre-classification.
Related Issues (4)
- Epoch 1/70 12/22 [===============>..............] - ETA: 8s - loss: 0.4481 - accuracy: 0.8300 - get_f1: 0.8416 --------------------------------------------------------------------------- UnidentifiedImageError Traceback (most recent call last) <ipython-input-39-b2a011903e5a> in <module>() ----> 1 model.fit_generator(train_generator,epochs=70,validation_data=vali_generator) 12 frames /usr/local/lib/python3.6/dist-packages/PIL/Image.py in open(fp, mode) 2860 warnings.warn(message) 2861 raise UnidentifiedImageError( -> 2862 "cannot identify image file %r" % (filename if filename else fp) 2863 ) 2864 UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x7ff9217a4af0> HOT 2
- NameError: name 'X_test' is not defined HOT 8
- Music Genre classification using cnn
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from music-genre-classification.