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.
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
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
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()
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")
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.
