图像基本操作

图片的读取

import cv2

img = cv2.imread('geeks.png', cv2.IMREAD_GRAYSCALE)     # 读取灰度图片
cv2.imshow('my test', img)
cv2.waitKey(0)      # 等待，0表示按下任意键终止
cv2.destroyAllWindows()
print(img.shape)
print(img.size)     # 查看像素点个数

 

视频的读取

import cv2

vc = cv2.VideoCapture('psychological.mp4')
# 先判断是否能打开，如果能则循环读取每一帧数据，之后对每一张图片进行一些处理
if vc.isOpened():
    open, frame = vc.read()
else:
    open = False
while open:
    ret, frame = vc.read()
    if frame is None:
        break
    if ret:
        # 如果用一些老的训练好的模型，建议使用兼容老模型的bgr
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        cv2.imshow('result', gray)
        if cv2.waitKey(100) % 0xFF == 27:
            break
vc.release()
cv2.destroyAllWindows()

 

读取感兴趣的窗口

import cv2

img = cv2.imread('geeks.png')
img2 = img[20:200, 20:200]      # 截取Y、X轴的范围
cv2.imshow('test', img2)
cv2.waitKey(0)
cv2.destroyAllWindows()

 

通道分离与合并

import cv2
img = cv2.imread('geeks.png')
b, g, r = cv2.split(img)    # 通道分开
img1 = cv2.merge((b, g, r))     # 通道合并
cv2.imshow('test1', img1)
cop_img = img1.copy()
cop_img[:, :, [0, 1]] = 0   # 只留下红色通道
cv2.imshow('test1_only_r', cop_img)
cv2.waitKey(0)
cv2.destroyAllWindows()

 

边界填充

import cv2
import matplotlib.pyplot as plt

top_size, bottom_size, left_size, right_size = (50, 50, 50, 50)
img = cv2.imread('geeks.png')
replicate = cv2.copyMakeBorder(img, top_size, bottom_size, left_size, right_size, borderType=cv2.BORDER_REPLICATE)
reflect = cv2.copyMakeBorder(img, top_size, bottom_size, left_size, right_size, cv2.BORDER_REFLECT)
reflect101 = cv2.copyMakeBorder(img, top_size, bottom_size, left_size, right_size, cv2.BORDER_REFLECT_101)
wrap = cv2.copyMakeBorder(img, top_size, bottom_size, left_size, right_size, cv2.BORDER_WRAP)
constant = cv2.copyMakeBorder(img, top_size, bottom_size, left_size, right_size, cv2.BORDER_CONSTANT, value=0)

plt.subplot(231), plt.imshow(img, 'gray'), plt.title('ORIGINAL')
plt.subplot(232), plt.imshow(replicate, 'gray'), plt.title('REPLICATE')
plt.subplot(233), plt.imshow(reflect, 'gray'), plt.title('REFLECT')
plt.subplot(234), plt.imshow(reflect101, 'gray'), plt.title('REFLECT_101')
plt.subplot(235), plt.imshow(wrap, 'gray'), plt.title('WRAP')
plt.subplot(236), plt.imshow(constant, 'gray'), plt.title('CONSTANT')
plt.show()

 

图像数值计算与融合

import cv2

# 对图像的像素点直接进行相加减
# img = cv2.imread('default.png')
# img_add = img + 10
# cv2.imshow('test', img)
# cv2.waitKey(0)
# cv2.destroyAllWindows()

img_geeks = cv2.imread('geeks.png')
img_default = cv2.imread('default.png')
print('img_geeks_size', img_geeks.shape)
print('img_default_size', img_default.shape)
img_geeks_resize = cv2.resize(img_geeks, (382, 420))
print('img_geeks_resize', img_geeks_resize.shape)
# 将两张相同大小且类型相同的图像融合，第一张图淡化到30%，第二张图90%，注意两图大小保持一致
res = cv2.addWeighted(img_geeks_resize, 0.3, img_default, 0.9, 0)
cv2.imshow('420*382', res)
cv2.waitKey(0)
cv2.destroyAllWindows()