ValueError: cannot reshape array of size 15525000 into shape (260,260) in Python?

Question

I have a problem about reshaping dataframe for implementing CNN.

My dataframe shape : train.shape -> (230, 67502).

Then I wrote a code shown below.

Y_train = train["Label"]
X_train = train.drop(labels = ["Label"],axis = 1) 

When I run this code below for plotting some images by iloc, It throws an error

img = X_train.iloc[0].to_numpy()
img = np.pad(img, (0, (67600-img.shape[0])), 'constant').reshape((260, 260))
plt.imshow(img,cmap='gray')
plt.title(train.iloc[0,0])
plt.axis("off")
plt.show()

Then I normalize X_train

X_train = X_train / 255.0
print("x_train shape: ",X_train.shape)

When I reshape X_train , it throws an error

X_train = X_train.values.reshape(-1, 260, 260)
print("x_train shape: ",X_train.shape)

ValueError: cannot reshape array of size 15525000 into shape (260,260)

How can I fix the issue?

Answer 1

Are you absolutely sure you need a 260 * 260 image? As 67500 == 270 * 250, you can try that and see how it looks! Otherwise you would need to PAD - how exactly would depend upon your image.

But, one of the simplest might be to add 100 more 0's at the end to make it 67600 - hence 260 * 260

Answer 2

Well, 260*260 is 67600 and not 67500. So you can't cast your array into those dimensions.

To actually cast it into those dimensions you would need to pad or normalize the source image arrays. For example, check the Keras pad_sequences functionality documentation on dealing with this kind of issues.

Answer 3

Solution :

X_train = np.pad(X_train, ((0,0), (0, (67600-X_train.shape[1]))), 'constant').reshape(-1, 260, 260)