resize numpy array referencing another array

Question

mypath='/Users/sachal/Desktop/data_raw/normal_1/images'
onlyfiles = [ f for f in listdir(mypath) if isfile(join(mypath,f)) ]
images = np.asarray(np.empty(len(onlyfiles), dtype=object))

for n in range(0, len(onlyfiles)):
  images[n] = cv2.imread( join(mypath,onlyfiles[n]) )
#--------------------------------------------------------------------------------
resized = np.asarray(np.empty(len(onlyfiles), dtype=object))
img_f = np.asarray(np.empty(len(onlyfiles), dtype=object))


for n in range(0, len(onlyfiles)):
  resized[n] = cv2.resize(images[n],(101,101))
  img_f[n] = cv2.cvtColor(resized[n], cv2.COLOR_BGR2YUV)

train_img =  np.asarray(img_f)
#--------------------------------------------------------------------------------

In the above code first I am loading images using opencv then I am resizing and changing their colour space in the second block.

My batch size is 6408 and dimensions of images are 101*101*3 When i do train_img.shape i get(6408,) and upon train_img[i].shape i get 101*101*3 and I am unable to train my neural network model because of this and the dimensions i want are 6408*101*101*3

I tried reshaping with this train_img.resize(6408,101,101,3) i got this ValueError: cannot resize an array that references or is referenced by another array in this way. Use the resize function

and while fitting my model with i got this error Error when checking input: expected conv2d_3_input to have 4 dimensions, but got array with shape (6408, 1)

I want to know if i can change the dimensions of my input with the current method i am using to load my images.

Please try to provide a working example without local links to your data. Embedd a small matrix with values to show what you mean. — Joe
– Joe, Commented Aug 15, 2018 at 12:29
what I want is [1 1 1 1] this type of matrix but what i am getting is first a list of 6408 elements then each element is [1 1 1] — user9369143
– user9369143, Commented Aug 15, 2018 at 12:38

Sunreef · Accepted Answer · 2018-08-15 13:50:50Z

1

You shouldn't use the dtype=object here. OpenCV creates ndarray images anyway.

Here is a corrected version of your code:

mypath='/Users/sachal/Desktop/data_raw/normal_1/images'
onlyfiles = [ f for f in os.listdir(mypath) if os.path.isfile(join(mypath,f)) ]
images = []

for file in onlyfiles:
   img = cv2.imread(os.path.join(mypath,file))
   resized_img = cv2.resize(img, (101, 101)) 
   yuv_img = cv2.cvtColor(resized_img, cv2.COLOR_BGR2YUV)
   images.append(yuv_img.reshape(1, 101, 101, 3))

train_img = np.concatenate(images, axis=0)
print(train_img.shape)

In the loop, you load each image, resize it, convert it to YUV then put it in a list. At the end of the loop, your list contains all your training images. You can pass it to np.concatenate to create an ndarray.

edited Aug 15, 2018 at 13:50

answered Aug 15, 2018 at 13:45

Sunreef

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