Augmentation

adding_noise.py

#standard deviation for noise to be added in the image
sigma=0.155
#add random noise to the image
noisyRandom = random_noise(image,var=sigma**2)

plt.imshow(noisyRandom)
plt.title('Random Noise')

blurring.py

#blur the image
blurred = gaussian(image,sigma=1,multichannel=True)

plt.imshow(blurred)
plt.title('Blurred Image')

flip_1.py

#flip image left-to-right
flipLR = np.fliplr(image)

plt.imshow(flipLR)
plt.title('Left to Right Flipped')

flip_2.py

#flip image up-to-down
flipUD = np.flipud(image)

plt.imshow(flipUD)
plt.title('Up Down Flipped')

image_rotation.py

print('Rotated Image')
#rotating the image by 45 degrees
rotated = rotate(image, angle=45, mode = 'wrap')
#plot the rotated image
io.imshow(rotated)

image_shift.py

#apply shift operation
transform = AffineTransform(translation=(25,25))
wrapShift = warp(image,transform,mode='wrap')
plt.imshow(wrapShift)
plt.title('Wrap Shift')

library.py

# importing all the required libraries
import warnings
warnings.filterwarnings('ignore')
import numpy as np
import skimage.io as io
from skimage.transform import rotate, AffineTransform, warp
from skimage.util import random_noise
from skimage.filters import gaussian
import matplotlib.pyplot as plt
% matplotlib inline

reading_image.py

# reading the image using its path
image = io.imread('emergency_vs_non-emergency_dataset/images/0.jpg')

# shape of the image
print(image.shape)

# displaying the image
io.imshow(image)