CODEWITHSUNDEEP
pythontensorflowopencv
Clement Ong
Clement Ong

Reputation: 107

Resizing image with cv2

I'm trying resize images retrieved from cifar10 in the original 32x32 to 96x96 for use with MobileNetV2, howevery I'm running into this error. Tried a variety of solutions but nothing seems to work.

My code:

for a in range(len(train_images)):
    train_images[a] = cv2.resize(train_images[a], dsize=(minSize, minSize), interpolation=cv2.INTER_CUBIC)

Error I'm getting:

----> 8     train_images[a] = cv2.resize(train_images[a], dsize=(minSize, minSize), interpolation=cv2.INTER_CUBIC)
ValueError: could not broadcast input array from shape (96,96,3) into shape (32,32,3)

Upvotes: 3

Views: 10919

Answers (3)

Md. Hanif Ali Sohag
Md. Hanif Ali Sohag

Reputation: 59

There are some interpolation algorithms in OpenCV. Such as-

  • INTER_NEAREST – a nearest-neighbor interpolation
  • INTER_LINEAR – a bilinear interpolation (used by default)
  • INTER_AREA – resampling using pixel area relation. It may be a preferred method for image decimation, as it gives moire’-free results. But when the image is zoomed, it is similar to the INTER_NEAREST method.
  • INTER_CUBIC – a bicubic interpolation over 4×4 pixel neighborhood
  • INTER_LANCZOS4 – a Lanczos interpolation over 8×8 pixel neighborhood

Code:

image_scaled=cv2.resize(image,None,fx=.75,fy=.75,interpolation = cv2.INTER_LINEAR)
img_double=cv2.resize(image,None,fx=2,fy=2,interpolation=cv2.INTER_CUBIC)
image_resize=cv2.resize(image,(200,300),interpolation=cv2.INTER_AREA)
image_resize=cv2.resize(image,(500,400),interpolation=cv2.INTER_LANCZOS4)

You can find the details about python implementation here as well: How to resize images in OpenCV python

Upvotes: 0

Novak
Novak

Reputation: 2171

Sometimes you have to convert the image from RGB to grayscale. If that is the problem, the only thing you should do is gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY), resize the image and then again resized_image = cv2.cvtColor(gray_image, cv2.COLOR_GRAY2RGB)

I have never run into this error but if the first option doesn't work, you can try and resize image with pillow like this:

from PIL import Image

im = Image.fromarray(cv2_image)
nx, ny = im.size
im2 = im.resize((nx*2, ny*2), Image.LANCZOS)
cv2_image = cv2.cvtColor(numpy.array(im2), cv2.COLOR_RGB2BGR)

You can make this into a function and call it in the list comprehension. I hope this solves your problem :)

Upvotes: 1

Ary
Ary

Reputation: 424

This is simply because you are reading the 32x32 image from train_images and trying to save the reshaped image (96x96) in the same array which is impossible! Try something like:

train_images_reshaped = np.array((num_images, 96, 96, 3))
for a in range(len(train_images)):
    train_images_reshaped[a] = cv2.resize(train_images[a], dsize=(minSize, minSize), interpolation=cv2.INTER_CUBIC)

Upvotes: 1

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