本节为《OpenCV计算机视觉实战(Python)》版第二讲,图像基本操作,的主要内容以及讲解,按顺序。
import cv2
import matplotlib.pyplot as plt
import numpy as np
img = cv2.imread('cat.jpg')
- cv2读取的格式是BGR
- 输出的Img为三维:(400,500,3)
# 图像的显示,也可以创建多个窗口
cv2.imshow('image',img)
# 等待时间,毫秒级,0表示任意键终止
cv2.waitKey(0)
cv2.destroyAllWindows()
# 图像保存
cv2.imwrite('mycat.png', img)
- cv2.waitKey() 括号中,写0表示按任意键可以终止;写10就代表会停10毫秒,10毫秒后自动终止
img = cv2.imread('cat.jpg', cv2.IMREAD_GRAYSCALE)
# Img图像的尺寸,彩色图一般为(m,n,p)
img.shape
type(img) # 输出numpy.ndarray
img.size
img.dtype # dtype('uint8’)
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:
# 将整体的视频都转为黑白色
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
cv2.imshow('result', gray)
# 展示结果,放缓或者加快速度
if cv2.waitKey(10)& 0xFF == 27: # 27代表的是退出键,也可以写别的
break
vc.release()
cv2.destroyAllWindows()
img = cv2.imread('cat.jpg')
cat = img[0:200, 0:200]
cv2.imshow('cat', cat)
b,g,r = cv2.split(img) # 输出的单通道应该为二维:(400,500)
img = cv2.merge((b,g,r)) # 输出为三维:(400,500,3)
# 只保留R通道
cur_img = img.copy()
cur_img[:,:,0] = 0
cur_img[:,:,1] = 0
cv2.imshow('R', cur_img)
top_size, bottom_size, left_size, right_size = (50,50,50,50)
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, borderType = cv2.BORDER_REFLECT)
reflect101 = cv2.copyMakeBorder(img, top_size, bottom_size, left_size, right_size, borderType = cv2.BORDER_REFLECT_101)
wrap = cv2.copyMakeBorder(img, top_size, bottom_size, left_size, right_size, borderType = cv2.BORDER_WRAP)
constant = cv2.copyMakeBorder(img, top_size, bottom_size, left_size, right_size, borderType = cv2.BORDER_CONSTANT, value = 0)
import matplotlib.pyplot as plt
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')
BORDER_REPLICATE: 复制法,也就是复制最边缘像素
BORDER_REFLECT: 反射法,对感兴趣的图像中的像素在两边进行复制,例如:fedcba | abcdefg | hgfedcb
BORDER_REFLECT_101: 反射法,以最边缘像素为轴,对称,gfedcb | abcdefgh | gfedcba
BORDER_WRAP: 外包装法,cdefgh | abcdefgh | abcdefg
BORDER_CONSTANT: 常量法,用常数值填充
img_cat = cv2.imread('cat.jpg')
img_dog = cv2.imread('dog.jpg')
img_cat2 = img_cat + 10
cv2.add(img_cat, img_cat2)
- 直接相加的话,在Uint8范围内,会自动对256求余
- 如果用cv2.add()函数,如果数值超过255,输出矩阵均为255
img_dog = cv2.resize(img_dog, (500,414))
img_dog = cv2.resize(img_dog, (0,0), fx=3, fy=1) # x轴放大3倍,y轴放大1倍
#加权重,0.4*猫的图像 + 0.6*狗的图像 + 偏置0
res = cv2.addWeighted(img_cat, 0.4, img_dog, 0.6, 0)
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