Visualize MNIST dataset using OpenCV or Matplotlib/Pyplot

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i have MNIST dataset and i am trying to visualise it using pyplot. The dataset is in cvs format where each row is one image of 784 pixels. i want to visualise it in

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  • 2021-02-19 13:42

    Assuming you have a CSV file with this format, which is a format the MNIST dataset is available in

    label, pixel_1_1, pixel_1_2, ...
    

    Here's how you can visulize it in Python with Matplotlib and then OpenCV

    Matplotlib / Pyplot

    import numpy as np
    import csv
    import matplotlib.pyplot as plt
    
    with open('mnist_test_10.csv', 'r') as csv_file:
        for data in csv.reader(csv_file):
            # The first column is the label
            label = data[0]
    
            # The rest of columns are pixels
            pixels = data[1:]
    
            # Make those columns into a array of 8-bits pixels
            # This array will be of 1D with length 784
            # The pixel intensity values are integers from 0 to 255
            pixels = np.array(pixels, dtype='uint8')
    
            # Reshape the array into 28 x 28 array (2-dimensional array)
            pixels = pixels.reshape((28, 28))
    
            # Plot
            plt.title('Label is {label}'.format(label=label))
            plt.imshow(pixels, cmap='gray')
            plt.show()
    
            break # This stops the loop, I just want to see one
    

    OpenCV

    You can take the pixels numpy array from above which is of dtype='uint8' (unsigned 8-bits integer) and shape 28 x 28 , and plot with cv2.imshow()

        title = 'Label is {label}'.format(label=label)
    
        cv2.imshow(title, pixels)
        cv2.waitKey(0)
        cv2.destroyAllWindows()
    
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  • 2021-02-19 13:47

    Importing necessary packages

    import pandas as pd
    import matplotlib.pyplot as plt
    import numpy as np
    

    Reading mnist train dataset ( which is csv formatted ) as a pandas dataframe

    s = pd.read_csv("mnist_train.csv")
    

    Converting the pandas dataframe to a numpy matrix

    data = np.matrix(s)
    

    The first column contains the label, so store it in a separate array

    output = data[:, 0]
    

    And delete the first column from the data matrix

    data = np.delete(data, 0, 1)
    

    The first row represents the first image, it is 28X28 image (stored as 784 pixels)

    img = data[0].reshape(28,28)
    
    # And displaying the image
    plt.imshow(img, cmap="gray")
    

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  • 2021-02-19 14:02

    For all like me who want a quick and dirty solution, simply to get a rough idea what a given input is about, in-console and without fancy libraries:

    def print_greyscale(pixels, width=28, height=28):
        def get_single_greyscale(pixel):
            val = 232 + round(pixel * 23)
            return '\x1b[48;5;{}m \x1b[0m'.format(int(val))
    
        for l in range(height):
            line_pixels = pixels[l * width:(l+1) * width]
            print(''.join(get_single_greyscale(p) for p in line_pixels))
    

    (expects the input to be shaped like [784] and with float values from 0 to 1. If either is not the case, you can easily convert (e.g. pixels = pixels.reshape((784,)) or pixels \= 255)

    The output is a bit distorted but you get the idea.

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