These are the 9600 images in my folder + their properties: enter image description here
I tried resizing them with this code below, but then this gave me an image shape of (9600, 224, 672). I mainly used this code because it helped me get my images into the correct array/ I had used this code earlier for a kmeans thing. I need a smaller image shape for the DCGAN code (something closer to 9600,64,128)-- see below for why.
import numpy as np
from numpy import save
import tensorflow as tf
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans
from sklearn.metrics import silhouette_score
import cv2
import os, glob, shutil
input_dir = '/Users/User/Documents/MATLAB/attempt6images/'
glob_dir = input_dir + '/*.jpg'
img = [cv2.resize(cv2.imread(file), (224, 224)) for file in glob.glob(glob_dir)]
#save('SV_images.npy', images)
paths = [file for file in glob.glob(glob_dir)]
img = np.array(np.float32(img).reshape(len(img), -1)/255)
save('SV_images.npy', img)
I'm trying to run them through a DCGAN code which was originally created for an image with shape (9600, 64, 128). When I use the image shape 224,672, my kernel dies. So I'm assuming my image size might be too big in comparison to the original images. By the way I changed the 25624 part to 256721 to match my image shape + changed all the other numbers besides the 256 column). Below is a part of that original code for the 64x128. Any idea how to reshape my image size so that my kernel doesnt die? enter image description here