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pythontensorflowkerasdeep-learningneural-network

How Do I separate labels and images?

I am loading a dataset of handwritten images

import numpy as np
import matplotlib.pyplot as plt
from tensorflow import keras
from tensorflow.keras import layers 

train_data= np.loadtxt('train.txt')
print('train:',train_data.shape)      ##train (7291, 257)

The first digit of each row is a digit from 0-9(labels), and the rest 256 are images. How can I separate these labels from the images? What I am thinking is to make a new tensor with every first digit of each row, and another one with the rest of the digits. Since I am a beginner I am not sure how to do it or if my approach is correct.

Solution

  • You need to learn numpy indexing: https://numpy.org.cn/en/user/basics/indexing.html

    In your case, just do

    labels = train_data[:, 0]
images = train_data[:, 1:]