Visualize MNIST dataset using OpenCV or Matplotlib

问题:

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 pyplot or opencv in the 28*28 image format. I am trying directly using :

plt.imshow(X[2:],cmap =plt.cm.gray_r, interpolation = "nearest") 

but i its not working? any ideas on how should i approach this.

回答1:

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()

回答2:

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.

回答3:

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")