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November 14, 2023 17:50
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Preprocessing Techniques
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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() |
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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() |
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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() |
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from skimage.io import imread, imshow | |
from skimage import data | |
image = data.astronaut() | |
imshow(image) |
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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() |
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image_gray = imread('images.jpeg', as_gray=True) | |
print(image_gray.shape) | |
print(image_gray) |
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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) |
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from skimage.io import imread, imshow | |
import matplotlib.pyplot as plt | |
%matplotlib inline | |
image_gray = imread('images.jpeg', as_gray=True) | |
imshow(image_gray) |
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red_channel = image_color*[1,0,0] | |
imshow(red_channel) |
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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() |
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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() |
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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() |
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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() |
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from skimage.transform import rotate | |
image = imread('tilt_image.png') | |
image_rotated = rotate(image, angle=45) | |
imshow(image_rotated) |
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from skimage.transform import rotate | |
image = imread('tilt_image.png') | |
image_rotated = rotate(image, angle=45, resize=True) | |
imshow(image_rotated) |
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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)):
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 toimg_rescaled = rescale(img, 0.5)
, it worksplt.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 ??????????????
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Helpful. Thank YOU