What is train_y and val_y in dataset? about eye-tracker HOT 6 CLOSED

@IvanKwokKC It's because the input data has been normalized. You may want to check out the official release of the code here.

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I find the normalization function in the code:

def normalize(data):
    shape = data.shape
    data = np.reshape(data, (shape[0], -1))
    data = data.astype('float32') / 255. # scaling
    data = data - np.mean(data, axis=0) # normalizing
return np.reshape(data, shape)

I am not good in statistics. I think this is zero mean normalization.
data = data - np.mean(data, axis=0) # normalizing

Does it possible convert normalized data back to original one?
I have no idea.

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@IvanKwokKC I think you can just keep the original data.

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I think the output is strange. The input has been normalized using a zero-mean function. However, the output always stay a small or negative number.

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train_y and val_y is actually the xy offset from your mobile phones camera. According to this dataset, the offset ranges from 0~20 centimeters. You normalize the input data but your did not normalize the output of the network. The problem is not the normalization.

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@Vampire-Vx Thank you for providing additional information. I wondered if the output has already been normalized by the original authors when releasing the dataset. The dataset I was using was a small sampling from the whole dataset. Please refer to #4 for more about this dataset. You may want to contact the original authors to get the raw output.

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