CODEWITHSUNDEEP
pythondeep-learning
Adesh Vaidya
Adesh Vaidya

Reputation: 21

cannot reshape array of size 2352 into shape (1,28,28,1)

During the classification of MNIST data, I am not able to upload the custom image from myself and gives ValueError cannot reshape array of size 2352 into shape (1,28,28,1)

import numpy as np
from google.colab import files
from tensorflow.keras.preprocessing import image
import matplotlib.pyplot as plt

uploaded = files.upload()

for fn in uploaded.keys():
   path = '/content/' + fn
   img = image.load_img(path, target_size =(28, 28))
   x = image.img_to_array(img)
   x = np.expand_dims(x, axis = 0)
   images = np.vstack([x])
   print(images.shape)
   images = images.reshape(1, 28, 28, 1)
   print(images.shape)
   classes = model.predict(images, batch_size = 10)



Capture.PNG(image/png) - 8252 bytes, last modified: 1/26/2020 - 100% done
Saving Capture.PNG to Capture (1).PNG
(1, 28, 28, 3)
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-156-810149b1d6fd> in <module>()
     13   images = np.vstack([x])
     14   print(images.shape)
---> 15   images = images.reshape(1, 28, 28, 1)
     16   print(images.shape)
     17   classes = model.predict(images, batch_size = 10)

 ValueError: cannot reshape array of size 2352 into shape (1,28,28,1)

Upvotes: 1

Views: 8014

Answers (1)

Kalpit
Kalpit

Reputation: 1081

You probably are trying to predict on an RGB image, while the model requires a grayscale image. What would work is if you do

img = img[:,:,0]

right after you load the image and then do the remaining process as it is.

Upvotes: 4

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