2

I need help in the following regard...

this code:

show_picture(x_train[0])
print(x_train.shape)
plt.imshow(x_train,cmap=cm.Greys_r,aspect='equal')

returns the following:

(267, 100, 100, 3)
TypeError                                 Traceback (most recent call last)
<ipython-input-86-649cf879cecf> in <module>()
2 show_picture(x_train[0])
  3 print(x_train.shape)
 ----> 4 plt.imshow(x_train,cmap=cm.Greys_r,aspect='equal')
  5 

5 frames
/usr/local/lib/python3.7/dist-packages/matplotlib/image.py in set_data(self, A)
697                 or self._A.ndim == 3 and self._A.shape[-1] in [3, 4]):
698             raise TypeError("Invalid shape {} for image data"
--> 699                             .format(self._A.shape))
700 
701         if self._A.ndim == 3:

TypeError: Invalid shape (267, 100, 100, 3) for image data

whats the correct procedure to do this

molbdnilo
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gumecf
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  • It looks like you have made yourself a three dimensional image. It's impossible to guess what the correct procedure is without knowing what it's supposed to be. – molbdnilo Mar 04 '21 at 07:29

1 Answers1

1

First of all, it seems like you are working with an array of 267 of 100x100 RGB images here. I am assuming you are using a NumPy array. In order to convert the images to grayscale you can use the method proposed in this answer:

def rgb2gray(rgb):
    return np.dot(rgb[...,:3], [0.2989, 0.5870, 0.1140])

x_train_gray = rgb2gray(x_train)

Note that this works for all images in one pass and the resulting shape should be (267, 100, 100). However, np.imshow only works for one image at a time so to plot an image in grayscale you can do the following:

plt.imshow(x_train_gray[0], cmap=plt.get_cmap('gray'), vmin=0, vmax=1)
plt.show()
Gilles Ottervanger
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