Preprocessing Techniques

adjust_gamma.py

from skimage import exposure

#adjusting brightness
image = imread('images.jpeg')
image_bright = exposure.adjust_gamma(image, gamma=0.5,gain=1)
image_dark = exposure.adjust_gamma(image, gamma=1.5,gain=1)

# plotting images
plt.subplot(131), imshow(image)
plt.title('Original Image')

plt.subplot(132),imshow(image_bright)
plt.title('Bright Image')

plt.subplot(133),imshow(image_dark)
plt.title('Dark Image')

plt.show()

crop_image.py

image = imread('warriors.jpg')

# selecting part of the image only 
cropped = image[100:(img.shape[0]-100),100:(img.shape[1]-100)]

plt.subplot(121), imshow(image)
plt.title('Original Image')
plt.subplot(122),imshow(cropped)
plt.title('Cropped Image')

plt.show()

flip_lr.py

from numpy import fliplr, flipud
dog = imread('Puppy.jpg')
cat = imread('whiskers.jpg')

dog_flip = fliplr(dog)
cat_flip = fliplr(cat)

plt.subplot(141), imshow(dog)
plt.subplot(142), imshow(dog_flip)
plt.subplot(143), imshow(cat)
plt.subplot(144), imshow(cat_flip)
plt.show()

loading_image.py

from skimage.io import imread, imshow
from skimage import data

image = data.astronaut()
imshow(image)

median_filter.py

from skimage.filters import median

image = imread('images.jpeg', as_gray=True)
image_median = median(image)

# plotting images
plt.subplot(121), imshow(image)
plt.title('Original Image')

plt.subplot(122),imshow(image_median)
plt.title('Smooth Image')

plt.show()

printing_gray.py

image_gray = imread('images.jpeg', as_gray=True)
print(image_gray.shape)
print(image_gray)

reading_color.py

from skimage.io import imread, imshow
import matplotlib.pyplot as plt
%matplotlib inline

image_color = imread('images.jpeg', as_gray=False)
print(image_color.shape)
imshow(image_color)

reading_gray.py

from skimage.io import imread, imshow
import matplotlib.pyplot as plt
%matplotlib inline

image_gray = imread('images.jpeg', as_gray=True)
imshow(image_gray)

red_channel.py

red_channel = image_color*[1,0,0]
imshow(red_channel)

rescale_image.py

from skimage.transform import rescale
img = imread('images.jpeg')
img_rescaled = rescale(img, scale=(0.5, 0.5))


plt.subplot(121), imshow(img)
plt.title('Original Image')

plt.subplot(122), imshow(img_rescaled)
plt.title('Rescaled Image')

plt.show()

resize_image.py

from skimage.transform import resize
img = imread('images.jpeg')
#resize image
img_resized = resize(img, (300, 300))

#plot images
plt.subplot(121), imshow(img)
plt.title('Original Image')
plt.subplot(122), imshow(img_resized)
plt.title('Resized Image')
plt.show()

rgb_gray.py

from skimage.color import rgb2gray
img = imread('images.jpeg')
img_new = rgb2gray(img)

plt.subplot(121), imshow(img)
plt.title('RGB Format') 

plt.subplot(122), imshow(img_new)
plt.title('Grayscale Format') 

plt.show()

rgb_hsv.py

from skimage.color import rgb2hsv
img = imread('images.jpeg')
img_new = rgb2hsv(img)

plt.subplot(121), imshow(img)
plt.title('RGB Format') 

plt.subplot(122), imshow(img_new)
plt.title('HSV Format') 

plt.show()

rotate_image.py

from skimage.transform import rotate
image = imread('tilt_image.png')

image_rotated = rotate(image, angle=45)
imshow(image_rotated)

rotate_image_resize.py

from skimage.transform import rotate
image = imread('tilt_image.png')

image_rotated = rotate(image, angle=45, resize=True)
imshow(image_rotated)

sobel_h.py

from skimage.filters import sobel_h

image = imread('images.jpeg', as_gray=True)
image_sobelh = sobel_h(image)

# plotting images
plt.subplot(121), imshow(image)
plt.title('Original Image')

plt.subplot(122),imshow(image_sobelh, cmap = True)
plt.title('Horizontal Edge')

plt.show()

Thanks

'rescale_image.py' is very problematic (at least for me (Python 3.7, scikit-image 0.18.3)):

1. img_rescaled = rescale(img, scale=(0.5, 0.5)) produces "ValueError: Supply a single scale, or one value per spatial axis" !!
   If I change it to img_rescaled = rescale(img, 0.5), it works
2. plt.subplot(122), imshow(img_rescaled) produces "TypeError: Invalid shape (140, 114, 2) for image data" !!

Come on, this is too much guys!

Where are the images used in the code stored ??????????????