Fail to convert List of ndarrays to numpy array

Question

I am reading thousands of images (all three channels), one by one, in form of a numpy ndarray and append them to a list. At the end I want to convert this list into a numpy array:

import numpy as np
from PIL import Image

def read_image_path(path, img_size=227):
    img = Image.open(path)
    img = np.array(img.resize([img_size, img_size]))
    return img

I read each image path from a dictionary that looks like:

{1:{'img_path': 'path-to-image', 'someOtherKeys':'...'}, 2:{...}}

images = []
for key in key:
    img = read_image_path(dataset_dictionary[key]['img_path'])
    images.append(img)

Up to here it's all fine. I have a list of ndarray image matrices of size (227,227,3). But when I try to convert "images" to numpy array and return it from the function, it gives the following error:

return np.array(images)

return np.array(images)

ValueError: could not broadcast input array from shape (227,227,3) into shape (227,227)

I will be grateful to have anyone's idea about this.

Answer 1

Most likely you have a img (or images) which has the shape of (227,227) instead of (227,227,3).

The following code should tell you which image is the offender.

for key in key:
    img = read_image_path(dataset_dictionary[key]['img_path'])
    if img.shape != (227,227,3):
            print(key)