opencv基礎-影象操作

阿新 • • 發佈：2020-12-13

matplotlib  中是  RGB  順序
opencv      中是  BGR  順序

【例2.1】使用Numpy庫生成一個元素值都是0的二維陣列，用來模擬一幅黑色影象，並對其進行訪問、修改

import numpy as np
import matplotlib.pyplot as plt

img = np.zeros((5,5), dtype=np.uint8)
print('img=\n', img)
plt.subplot(1, 2, 1)
plt.imshow(img, cmap='gray')

img[:,3] = 255
print('img_modifier=\n', img)
plt.subplot(1, 2, 2)
plt.imshow(img, cmap='gray')

img=
 [[0 0 0 0 0]
 [0 0 0 0 0]
 [0 0 0 0 0]
 [0 0 0 0 0]
 [0 0 0 0 0]]
img_modifier=
 [[  0   0   0 255   0]
 [  0   0   0 255   0]
 [  0   0   0 255   0]
 [  0   0   0 255   0]
 [  0   0   0 255   0]]

【例2.2】讀取一個灰度影象，並對其畫素進行訪問、修改。

import cv2 as cv

lenna = cv.imread('../img/Lenna.png', cv.IMREAD_GRAYSCALE)
plt.subplot(121),plt.imshow(lenna, cmap='gray')
lenna[100:200, 80:100] = 255
plt.subplot(122),plt.imshow(lenna, cmap='gray')

【例2.3】使用Numpy生成三維陣列，用來觀察三個通道值的變化情況。

import numpy as np
import matplotlib.pyplot as plt

blue = np.zeros((300, 300, 3), dtype=np.uint8)
blue[:, :, 0] = 255
print('blue:\n', blue)

green =  np.zeros((300, 300, 3), dtype=np.uint8)
green[:, :, 1] = 255
print('green:\n', green)

red = np.zeros((300, 300, 3), dtype=np.uint8)
red[:, :, 2] = 255
print('red:\n', red)

plt.subplot(1, 3, 1), plt.imshow(blue)
plt.subplot(1, 3, 2), plt.imshow(green)
plt.subplot(1, 3, 3), plt.imshow(red)

blue:
 [[[255   0   0]
  [255   0   0]
  [255   0   0]
  ...
  [255   0   0]
  [255   0   0]
  [255   0   0]]

 [[255   0   0]
  [255   0   0]
  [255   0   0]
  ...
  [255   0   0]
  [255   0   0]
  [255   0   0]]

 [[255   0   0]
  [255   0   0]
  [255   0   0]
  ...
  [255   0   0]
  [255   0   0]
  [255   0   0]]

 ...

 [[255   0   0]
  [255   0   0]
  [255   0   0]
  ...
  [255   0   0]
  [255   0   0]
  [255   0   0]]

 [[255   0   0]
  [255   0   0]
  [255   0   0]
  ...
  [255   0   0]
  [255   0   0]
  [255   0   0]]

 [[255   0   0]
  [255   0   0]
  [255   0   0]
  ...
  [255   0   0]
  [255   0   0]
  [255   0   0]]]
green:
 [[[  0 255   0]
  [  0 255   0]
  [  0 255   0]
  ...
  [  0 255   0]
  [  0 255   0]
  [  0 255   0]]

 [[  0 255   0]
  [  0 255   0]
  [  0 255   0]
  ...
  [  0 255   0]
  [  0 255   0]
  [  0 255   0]]

 [[  0 255   0]
  [  0 255   0]
  [  0 255   0]
  ...
  [  0 255   0]
  [  0 255   0]
  [  0 255   0]]

 ...

 [[  0 255   0]
  [  0 255   0]
  [  0 255   0]
  ...
  [  0 255   0]
  [  0 255   0]
  [  0 255   0]]

 [[  0 255   0]
  [  0 255   0]
  [  0 255   0]
  ...
  [  0 255   0]
  [  0 255   0]
  [  0 255   0]]

 [[  0 255   0]
  [  0 255   0]
  [  0 255   0]
  ...
  [  0 255   0]
  [  0 255   0]
  [  0 255   0]]]
red:
 [[[  0   0 255]
  [  0   0 255]
  [  0   0 255]
  ...
  [  0   0 255]
  [  0   0 255]
  [  0   0 255]]

 [[  0   0 255]
  [  0   0 255]
  [  0   0 255]
  ...
  [  0   0 255]
  [  0   0 255]
  [  0   0 255]]

 [[  0   0 255]
  [  0   0 255]
  [  0   0 255]
  ...
  [  0   0 255]
  [  0   0 255]
  [  0   0 255]]

 ...

 [[  0   0 255]
  [  0   0 255]
  [  0   0 255]
  ...
  [  0   0 255]
  [  0   0 255]
  [  0   0 255]]

 [[  0   0 255]
  [  0   0 255]
  [  0   0 255]
  ...
  [  0   0 255]
  [  0   0 255]
  [  0   0 255]]

 [[  0   0 255]
  [  0   0 255]
  [  0   0 255]
  ...
  [  0   0 255]
  [  0   0 255]
  [  0   0 255]]]

【例2.4】使用Numpy生成一個三維陣列，用來觀察三個通道值的變化情況。

import numpy as np
import matplotlib.pyplot as plt

img = np.zeros((300, 300, 3), dtype=np.uint8)
img[:, 0:100, 0] = 255
img[:, 100:200, 1] = 255
img[:, 200:300, 2] = 255
plt.imshow(img)

【例2.5】使用Numpy生成一個三維陣列，用來模擬一幅BGR模式的彩色影象，並對其進行訪問、修改

import numpy as np
import matplotlib.pyplot as plt
import cv2 as cv
img = np.zeros((2, 4, 3), dtype=np.uint8)
print('img:\n',img)

img[0, 3] = 255
img[0, 1] = [66, 67, 88]
img[1, 1, 1] = 255
img[1, 2, 2] = 0
img[0, 2, 0] = 255
print(img)
plt.imshow(img)

img:
 [[[0 0 0]
  [0 0 0]
  [0 0 0]
  [0 0 0]]

 [[0 0 0]
  [0 0 0]
  [0 0 0]
  [0 0 0]]]
[[[  0   0   0]
  [ 66  67  88]
  [255   0   0]
  [255 255 255]]

 [[  0   0   0]
  [  0 255   0]
  [  0   0   0]
  [  0   0   0]]]

【例2.6】讀取一幅彩色影象，並對其畫素進行訪問、修改。

import cv2 as cv
import matplotlib.pyplot as plt
lenna = cv.imread('../img/Lenna.png')
lenna = lenna[:, :, [2, 1, 0]]
lenna[100:300, 100:200] = 255
lenna[300:400, 200:300] = 0
lenna[400:500, 300:400, 1] = 0
plt.imshow(lenna)