Added DATA_DIR hyperparameter
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@ -26,6 +26,8 @@ EPOCHS_PER_SAMPLE = 2
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BATCH_SIZE = 16
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BATCH_SIZE = 16
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Fs = 16000
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Fs = 16000
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DATA_DIR = r"D:\ML_Datasets\mancini_piano\piano\train"
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# Define class that contains GAN infrastructure
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# Define class that contains GAN infrastructure
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class GAN:
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class GAN:
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def __init__(self, model_dims=MODEL_DIMS, num_samples=NUM_SAMPLES,
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def __init__(self, model_dims=MODEL_DIMS, num_samples=NUM_SAMPLES,
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@ -132,8 +134,8 @@ gan = GAN()
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# Create training data
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# Create training data
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X_train = []
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X_train = []
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for file in os.listdir(r"D:\ML_Datasets\mancini_piano\piano\train"):
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for file in os.listdir(DATA_DIR): ### Modify for your data directory
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with open(r"D:\ML_Datasets\mancini_piano\piano\train" + fr"\{file}", "rb") as f:
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with open(DATA_DIR + fr"\{file}", "rb") as f:
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samples, _ = librosa.load(f, Fs)
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samples, _ = librosa.load(f, Fs)
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# Pad short audio files to NUM_SAMPLES duration
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# Pad short audio files to NUM_SAMPLES duration
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if len(samples) < NUM_SAMPLES:
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if len(samples) < NUM_SAMPLES:
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