I cant understand what is the effect of shear parameter in ImageDataGenerator of keras
I had tried to use an image to apply the shear by apply_transform member function in ImageDataGenerator. I can see the image seems to be rotated and stretched out after apply this function. But I cant understand what exactly it did.
from keras.preprocessing.image import ImageDataGenerator
import matplotlib.pyplot as plt
import numpy as np
(train_x, train_y) , (test_x,test_Y) = cifar10.load_data()
img = train_x[0]
img_gen = ImageDataGenerator()
shear_intensity = np.arange(0,110,10, dtype = int)
nrow = 4
ncol = 3
plt.figure(figsize = (14,14))
for i,shear in enumerate(shear_intensity):
plt.title(f'shear intensity : {shear}')
plt.subplot(nrow, ncol, i+1)
plt.imshow(img_gen.apply_transform(img, {'shear' : shear}))
plt.show()
The image does have some change, but I cant understand the effect.