CODEWITHSUNDEEP
pythonnumpymatplotlibimshow
LearnToGrow
LearnToGrow

Reputation: 1750

Replace pixel values in a Numpy image

I have a zeros image with dimension 720*1280 and I have a list of pixels' coordinates to change:

x = [623, 623, 583, 526, 571, 669, 686, 697, 600, 594, 606, 657, 657, 657, 617, 646, 611, 657, 674, 571, 693, 688, 698, 700, 686, 687, 687, 693, 690, 686, 694]

y = [231, 281, 270, 270, 202, 287, 366, 428, 422, 517, 608, 422, 518, 608, 208, 214, 208, 231, 653, 652, 436, 441, 457, 457, 453, 461, 467, 469, 475, 477, 467]

here is the scatter plot :

yy= [720 -x for x in y]
plt.scatter(x, yy, s = 25, c = "r")
plt.xlabel('x')
plt.ylabel('y')
plt.xlim(0, 1280)
plt.ylim(0, 720)
plt.show()

enter image description here

here is the code to generate binary image by set the pixel value to 255

image_zeros = np.zeros((720, 1280), dtype=np.uint8)
    for i ,j in zip (x, y):
            image_zeros[i, j] = 255

    plt.imshow(image_zeros, cmap='gray')
    plt.show()

here is the result : What is the problem!!

enter image description here

Upvotes: 1

Views: 2713

Answers (1)

unutbu
unutbu

Reputation: 879501

As Goyo pointed out, the resolution of the image is the problem. The default figure size is 6.4 inches by 4.8 inches, and the default resolution is 100 dpi (at least for the current version of matplotlib). So the default image size is 640 x 480. The figure includes not only the imshow image, but also the tickmarks, ticklabels and the x and y axis and a white border. So there are are even fewer than 640 x 480 pixels available for the imshow image by default.

Your image_zeros has shape (720, 1280). The array is too large to be fully rendered in an image of 640 x 480 pixels.

Thus, to generate white dots using imshow, set the figsize and dpi so that the number of pixels available for the imshow image is bigger than (1280, 720):

import numpy as np
import matplotlib.pyplot as plt

x = np.array([623, 623, 583, 526, 571, 669, 686, 697, 600, 594, 606, 657, 657, 657, 617, 646, 611, 657, 674, 571, 693, 688, 698, 700, 686, 687, 687, 693, 690, 686, 694])
y = np.array([231, 281, 270, 270, 202, 287, 366, 428, 422, 517, 608, 422, 518, 608, 208, 214, 208, 231, 653, 652, 436, 441, 457, 457, 453, 461, 467, 469, 475, 477, 467])

image_zeros = np.zeros((720, 1280), dtype=np.uint8)
image_zeros[y, x] = 255

fig, ax = plt.subplots(figsize=(26, 16), dpi=100)
ax.imshow(image_zeros, cmap='gray', origin='lower')
fig.savefig('/tmp/out.png')

Here is a closeup showing some of the white dots:

enter image description here

To make the white dots easier to see, you may wish to use scatter instead of imshow:

import numpy as np
import matplotlib.pyplot as plt

x = np.array([623, 623, 583, 526, 571, 669, 686, 697, 600, 594, 606, 657, 657, 657, 617, 646, 611, 657, 674, 571, 693, 688, 698, 700, 686, 687, 687, 693, 690, 686, 694])
y = np.array([231, 281, 270, 270, 202, 287, 366, 428, 422, 517, 608, 422, 518, 608, 208, 214, 208, 231, 653, 652, 436, 441, 457, 457, 453, 461, 467, 469, 475, 477, 467])
yy = 720 - y

fig, ax = plt.subplots()

ax.patch.set_facecolor('black')
ax.scatter(x, yy, s=25, c='white')
ax.set_xlabel('x')
ax.set_ylabel('y')
ax.set_xlim(0, 1280)
ax.set_ylim(0, 720)
fig.savefig('/tmp/out-scatter.png')

enter image description here

Upvotes: 1

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