1 计算机中的图像

# 图像基本操作
import cv2
import matplotlib.pyplot as plt
import numpy as np

# cv2.IMREAD_COLOR 彩色图像，cv2.IMREAD_GRAYSCALE 灰度图像
img = cv2.imread('img.png')  # opencv默认读取的是BGR
cv2.imshow('image', img)  # 图像的显示，也可以创建多个窗口
cv2.waitKey(0)  # 等待时间，毫秒级，0表示任意键终止
cv2.destroyAllWindows()
cv2.imwrite('myimg.jpg', img)

2 视频的读取和处理

# 图像基本操作
import cv2
import matplotlib.pyplot as plt
import numpy as np

# 可以捕获摄像头，用数字来控制不同的设备，如果是视频文件，直接指定路径
vc = cv2.VideoCapture('test.mp4')
# 检查是否打开正确
if vc.isOpened():
    open, frame = vc.read()
else:
    open = False
while open:
    ret, frame = vc.read()
    if frame is None:
        break
    if ret == True:
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        cv2.imshow('result', gray)
        if cv2.waitKey(10) & 0xFF == 27:
            break
vc.release()
cv2.destroyAllWindows()

3 ROI区域

# 图像基本操作
import cv2
import matplotlib.pyplot as plt
import numpy as np

# 截取部分图像数据
img = cv2.imread('img.png')
img = img[0:500, 0:500]
cv2.imshow('img', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

# 颜色通道提取
b, g, r = cv2.split(img)
img = cv2.merge((b, g, r))

4 边界填充

import cv2
import matplotlib.pyplot as plt
import numpy as np

# 边界填充
img = cv2.imread('test.jpg')
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
top_size, bottom_size, left_size, right_size = (100, 100, 100, 100)
replicate = cv2.copyMakeBorder(src=img, top=top_size, bottom=bottom_size, left=left_size, right=right_size,
                               borderType=cv2.BORDER_REPLICATE)
reflect = cv2.copyMakeBorder(src=img, top=top_size, bottom=bottom_size, left=left_size, right=right_size,
                             borderType=cv2.BORDER_REFLECT)
reflect101 = cv2.copyMakeBorder(src=img, top=top_size, bottom=bottom_size, left=left_size, right=right_size,
                                borderType=cv2.BORDER_REFLECT_101)
wrap = cv2.copyMakeBorder(src=img, top=top_size, bottom=bottom_size, left=left_size, right=right_size,
                          borderType=cv2.BORDER_WRAP)
constant = cv2.copyMakeBorder(src=img, top=top_size, bottom=bottom_size, left=left_size, right=right_size,
                              borderType=cv2.BORDER_CONSTANT, value=0)

plt.subplot(2, 3, 1), plt.imshow(img, ), plt.title('original')
plt.subplot(2, 3, 2), plt.imshow(replicate, ), plt.title('replicate')
plt.subplot(2, 3, 3), plt.imshow(reflect, ), plt.title('reflect')
plt.subplot(2, 3, 4), plt.imshow(reflect101, ), plt.title('reflect101')
plt.subplot(2, 3, 5), plt.imshow(wrap, ), plt.title('wrap')
plt.subplot(2, 3, 6), plt.imshow(constant, ), plt.title('constant')

plt.show()

5 图像融合

import cv2
import matplotlib.pyplot as plt
import numpy as np

# 边界填充
img1 = cv2.imread('data/lena.png')
img2 = cv2.imread('data/dog.jpg')
print(img1.shape)  # (998, 998, 3)
print(img2.shape)  # (1298, 1298, 3)
img2 = cv2.resize(img2, img1.shape[:2])
res = cv2.addWeighted(img1, 0.4, img2, 0.6, 0)
cv2.imwrite('res.jpg', res)