當需要對圖片進行處理時贪薪，除了PS外查辩，還可以考慮用python胖笛。尤其是大批量處理圖片時，python的優(yōu)勢就體現出來了宜岛。此次介紹skimage包的基本用法匀钧。
1.網上下載的一張原始圖片cat.jpg
cat.jpg
2.代碼
a.讀取RGB和灰度圖像
from skimage.io import imread, imshow
import matplotlib.pyplot as plt
image_color = imread('cat.jpg') # 讀取RGB圖像
image_gray = imread('cat.jpg', as_gray=True) # 讀取灰度圖像
plt.subplot(121), imshow(image_color); plt.title('RGB Format')
plt.subplot(122), imshow(image_gray); plt.title('Gray Format')
plt.show()
b.將RGB圖像轉化為灰度和HSV圖像
from skimage.io import imread, imshow
from skimage.color import rgb2gray
from skimage.color import rgb2hsv
import matplotlib.pyplot as plt
img_rgb = imread('cat.jpg')
img_gray = rgb2gray(img_rgb)
img_hsv = rgb2hsv(img_rgb)
plt.subplot(131), imshow(img_rgb); plt.title('RGB Format')
plt.subplot(132), imshow(img_gray); plt.title('Gray Format')
plt.subplot(133), imshow(img_hsv); plt.title('HSV Format')
plt.show()
c.對圖像按固定像素進行放縮
from skimage.io import imread, imsave
from skimage.transform import resize
import numpy as np
img = imread('cat.jpg')
img_resized = resize(img, (100, 100)) # 圖像的尺寸轉化為100 x 100。返回float類型谬返。
img_unit8 = (img_resized * 255).astype(np.uint8) # 轉化為uint8類型。ima_unit8/255轉化為float類型
imsave('cat_resize.jpg', img_unit8)
cat_resize.jpg
d.對圖像按比例進行放縮
from skimage.io import imread, imsave
from skimage.transform import rescale
import numpy as np
img = imread('cat.jpg')
img_rescaled = rescale(img, scale=(0.5, 0.5, 1)) # 第一二個維度(height, width)縮放為原來的一半日杈，第三個維度(RGB)不變
img_unit8 = (img_rescaled * 255).astype(np.uint8)
imsave('cat_rescale.jpg', img_unit8)
cat_rescale.jpg
e.將圖像旋轉一定角度
from skimage.io import imread, imshow
from skimage.transform import rotate
image = imread('cat.jpg')
image_rotated = rotate(image, angle=45, resize=True) # 逆時針旋轉45度遣铝，改變大小以不丟失任何信息
imshow(image_rotated)
f. 圖像左右佑刷、上下翻轉
from skimage.io import imread, imshow
from numpy import fliplr, flipud
import matplotlib.pyplot as plt
cat = imread('cat.jpg')
cat_flipr = fliplr(cat) # 矩陣左右翻轉
cat_flipud = flipud(cat) # 矩陣上下翻轉
plt.subplot(131), imshow(cat)
plt.subplot(132), imshow(cat_flipr)
plt.subplot(133), imshow(cat_flipud)
plt.show()
g. 裁剪圖像
from skimage.io import imread, imshow
image = imread('cat.jpg')
cropped = image[100:(image.shape[0]-100),100:(image.shape[1]-100)] # 上下左右各減去100像素
imshow(cropped)
h. 調節(jié)亮度
from skimage.io import imread, imshow
from skimage import exposure
import matplotlib.pyplot as plt
image = imread('cat.jpg')
image_bright = exposure.adjust_gamma(image, gamma=0.5, gain=1) # 變亮
image_dark = exposure.adjust_gamma(image, gamma=1.5, gain=1) # 變暗
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()
i. 濾鏡
from skimage.io import imread, imshow
from skimage.filters import median
from skimage.filters import sobel_h
import matplotlib.pyplot as plt
image = imread('cat.jpg', as_gray=True)
image_median = median(image) # 中值濾鏡(像素值被替換為相鄰像素的中值)。平滑畫面酿炸，保持畫面清晰地同時瘫絮，減小畫面上微小的噪點。
image_sobelh = sobel_h(image) # sobel濾鏡填硕。突出顯示圖像的邊緣麦萤。
plt.subplot(131), imshow(image)
plt.title('Original Image')
plt.subplot(132),imshow(image_median)
plt.title('Smooth Image')
plt.subplot(133),imshow(image_sobelh, cmap='Greys_r')
plt.title('Horizontal Edge')
plt.show()
