I\'m trying to reshape a numpy array as:
data3 = data3.reshape((data3.shape[0], 28, 28))
where data3
is:
[[54
You can reshape the numpy matrix arrays such that before(a x b x c..n) = after(a x b x c..n). i.e the total elements in the matrix should be same as before, In your case, you can transform it such that transformed data3 has shape (156, 28, 28) or simply :-
import numpy as np
data3 = np.arange(122304).reshape(52, 2352 )
data3 = data3.reshape((data3.shape[0]*3, 28, 28))
print(data3.shape)
Output is of the form
[[[ 0 1 2 ..., 25 26 27]
[ 28 29 30 ..., 53 54 55]
[ 56 57 58 ..., 81 82 83]
...,
[ 700 701 702 ..., 725 726 727]
[ 728 729 730 ..., 753 754 755]
[ 756 757 758 ..., 781 782 783]]
...,
[122248 122249 122250 ..., 122273 122274 122275]
[122276 122277 122278 ..., 122301 122302 122303]]]
First, your input image's number of elements should match the number of elements in the desired feature vector.
Assuming the above is satisfied, the below should work:
# Reading all the images to a one numpy array. Paths of the images are in the imagePaths
data = np.array([np.array(cv2.imread(imagePaths[i])) for i in range(len(imagePaths))])
# This will contain the an array of feature vectors of the images
features = data.flatten().reshape(1, 784)