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Use preproccess.py to load a mp3 or .au etc.. to mfcc or mel-spec data, then start a tensorflow session, put some code like this: saver.restore(sess, "../output/model.final") xs, ys = /* your preproccessed data */ acc = sess.run(accuracy, feed_dict={x: xs, y: ys, keep_prob: 1.}) loss = sess.run(cost, feed_dict={x: xs, y: ys, keep_prob: 1.}) print("Minibatch Loss= " + \"{:.6f}".format(loss) + ", Accuracy= " + "{:.5f}".format(acc))
when accuracy is 1 then model prediction is right, otherwise accuracy is zero.
I'm sorry to disturb you. Since the link of the data set of this project in the current year is invalid and the author cannot be contacted, I can only ask you in this way. If you still have the data set of this project, could you please send it to me zjq2048@qq.com
If I download a new song that is not in the Dataset, how could I see what genre it is using the Model.final output file?
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