Nsryjdtyk

I have a mask image which is technically a matrix full of True/False values. I would like to view this as an image. First, I converted it into a binary array with (astype(np.uint8))

print('Part Mask', p['masks'][class_id].astype(np.uint8))

but I still can't view it as an image under Python notebook. OpenCV goes crazy and crashes the kernel.

Does anyone know how to view such a structure as an image on Python notebook without crashing the kernel?

    [[0 0 0 ... 0 0 0]

     [0 0 0 ... 0 0 0]

     [0 0 0 ... 0 0 0]

     ...

     [0 0 0 ... 0 0 0]

     [0 0 0 ... 0 0 0]

     [0 0 0 ... 0 0 0]]

or this would work as well ():

[[False False False ... False False False]

 [False False False ... False False False]

 [False False False ... False False False]

 ...

 [False False False ... False False False]

 [False False False ... False False False]

 [False False False ... False False False]]

Thanks in advance.

EDIT: I cannot copy paste the whole code here but basically I have a prediction tensor p, and p[masks][class_id] is what I want to visualize (showing the mask of each class).

enumerator = 0

# run through the instances

for class_id in p['class_ids']:

    #print('Image:', image) # the original input image

    #print('Mask:', merged_mask) # whole masked image

    print('ID: ', class_names[class_id] + str(enumerator))

    #print('Outline Poses: ', ) # mask boundary coordinates

    #print('Pose:',) # mask center coordinates

    print('Part Mask', p['masks'][class_id].astype(np.uint8)) # how to visualize this as an image?

    print('Confidence: ', p['scores'][class_id])

    print('BB: ', p['rois'][class_id]) # get the BB

    print('--------------------------')

    enumerator = enumerator + 1

P.S: Matplotlib does not work either. This is the kind of image I get when I try to print:

Matplotlib should work for you:

import numpy as np

from matplotlib import pyplot as plt





image = np.eye(10)

binary = image > 0

plt.imshow(binary)

plt.show()

With result:

Edit:

Your image is of shape (510,7), what you got above is exactly what you should expect:

import numpy as np

from matplotlib import pyplot as plt





image = np.eye(510)[:,:7]

binary = image > 0

plt.imshow(binary)

plt.show()

Results:

Maybe you may use PIL

from PIL import Image



data = [...]



width = len(data[0])

height = len(data)



output_image = Image.new(mode='1', size=(width, height))



for x in range(height):

    for y in range(width):

        pixel_value = data[x][y]

        output_image.putpixel((x,y), pixel_value)





output_image

with data = [[0,0,0,0], [0,0,1,1], [1,1,1,0], [0,1,1,0]]

i have such image ->