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I'm following a tutorial on YouTube (https://www.youtube.com/watch?v=y1ZrOs9s2QA&feature=youtu.be), the code can be found here: https://github.com/murtazahassan/Digits-Classification/blob/master/OCR_CNN_Trainning.py

But when I try to run the code below, I get the error: TypeError: only integer scalar arrays can be converted to a scalar index.

x_train = np.array(list(map(preprocess, x_train)))
x_test = np.array(list(map(preprocess, x_test)))
x_validation = np.array(list(map(preprocess, x_validation)))

x_train = x_train.reshape(x_train[0], x_train[1], x_train[2], 1)
x_test = x_test.reshape(x_test[0], x_test[1], x_test[2], 1)
x_validation = x_validation.reshape(x_validation[0], x_validation[1], x_validation[2], 1)

I found this (TypeError: only integer scalar arrays can be converted to a scalar index , while trying kfold cv) and this (TypeError when indexing a list with a NumPy array: only integer scalar arrays can be converted to a scalar index), but it did not help me. What am I doing wrong?

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  • With numpy, what do you get if you do name.dtype for all the arrays? Commented Apr 24, 2020 at 13:54
  • @duckboycool I get float64 Commented Apr 24, 2020 at 14:03

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You are passing values to reshape that are not of type int: 

x_train = x_train.reshape(x_train[0], x_train[1], x_train[2], 1)

Here, for example, x_train[0] need to be of type int (and so the rest). If you meant to use their shape instead of their values, use: 

x_train = x_train.reshape(x_train.shape[0], x_train.shape[1], x_train.shape[2], 1)

Otherwise, you have two options:

  1. If you know values in x_train, x_test and x_validation are integers, set their dtype to int (and make sure it remains the same during ML operations: 

    x_train = np.array(list(map(preprocess, x_train)), dtype=np.int)
x_test = np.array(list(map(preprocess, x_test)), dtype=np.int)
x_validation = np.array(list(map(preprocess, x_validation)), dtype=np.int)

  2. If you need them to be float but want to call them as int, use: 

    x_train = x_train.reshape(int(x_train[0]), int(x_train[1]), int(x_train[2]), 1)
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