机器视觉，opencv基础学习（一）
关于一些基础的opencv图像操纵函数的脑图https://i-blog.csdnimg.cn/direct/be742248bb9349ff9938ddf55b1be61a.png
① 二值化函数简单应用
import cv2
import numpy as np
import matplotlib.pyplot as plt
img = cv2.imread('12.png', cv2.IMREAD_GRAYSCALE)
img1 = cv2.imread('12.png', cv2.IMREAD_GRAYSCALE)
img2 = cv2.imread('12.png', cv2.IMREAD_GRAYSCALE)
ret, img1 = cv2.threshold(img1, 127, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
ret2, img2 = cv2.threshold(img2, 127, 255, cv2.THRESH_BINARY_INV)
cv2.imshow('img', img)
cv2.imshow('img1', img1)
cv2.imshow('img2', img2)
cv2.waitKey(0) https://i-blog.csdnimg.cn/direct/42edee4371b34eda8dbf4de219b83772.png
②自适应二值化函数简单应用
import cv2
img = cv2.imread('1.png', cv2.IMREAD_GRAYSCALE)
img_adaptive_binary = cv2.adaptiveThreshold(img,
255,
cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
cv2.THRESH_BINARY,
37,
5
)
cv2.imshow('img', img)
cv2.imshow('img_adaptive_binary', img_adaptive_binary)
cv2.waitKey(0)
https://i-blog.csdnimg.cn/direct/cd5cc627ac5c4509adb52c8f52d2c3c3.png
③腐蚀函数简单应用
import cv2
img_binary = cv2.imread('2.png')
ret = cv2.getStructuringElement(cv2.MORPH_RECT, (9, 9))
img_erode = cv2.erode(img_binary, ret)
cv2.imshow('img', img_binary)
cv2.imshow('img_erode', img_erode)
cv2.waitKey(0)
https://i-blog.csdnimg.cn/direct/d1a8163833fd4481992f27bf5fa8270c.png
④膨胀函数简单应用
import cv2
# 读取一张彩色图
img = cv2.imread("1.png")
# 转换成灰度图
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# 转换成二值化图
img_binary = cv2.adaptiveThreshold(img_gray,
255,
cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
cv2.THRESH_BINARY_INV,
7,
5)
# 进行腐蚀和膨胀操作
# 1、创建结构化元素 / 核
kernal = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
# 2、调用腐蚀函数
img_erode = cv2.erode(img_binary, kernal)
# 3、调用膨胀函数
img_erode_dilate = cv2.dilate(img_erode, kernal)
cv2.imshow('image_binary', img_binary)
cv2.imshow('image_erode', img_erode)
cv2.imshow('image_erode_dilate', img_erode_dilate)
cv2.waitKey(0) https://i-blog.csdnimg.cn/direct/ea0b34cde2794fa7b0db433cc5a7284b.png
⑤仿射变更函数简单应用
import cv2
img = cv2.imread('5.png')
m = cv2.getRotationMatrix2D((img.shape / 2, img.shape / 2), 45, 0.5)
img_new = cv2.warpAffine(img, m, (img.shape, img.shape), flags=cv2.INTER_LINEAR, borderMode=cv2.BORDER_REFLECT_101)
cv2.imshow('img',img)
cv2.imshow('img_new',img_new)
cv2.waitKey(0)
https://i-blog.csdnimg.cn/direct/f277bb4b3dd84050a87d68cb66ce4cd8.png
⑥透视变更函数简单应用
import cv2
import numpy as np
img = cv2.imread("6.png")
#获取透视变换矩阵
#原图中的4个点
points1 = np.array([, , , ],dtype=np.float32)
#目标中的4个点
points2 = np.array([, , 0], ], , img.shape]],dtype=np.float32)
M = cv2.getPerspectiveTransform(points1, points2)
img_warp=cv2.warpPerspective(img,M,(img.shape,img.shape))
cv2.imshow("img",img)
cv2.imshow('img_warp', img_warp)
cv2.waitKey(0)
原图：
https://i-blog.csdnimg.cn/direct/2be9f40e770b48cca684cd2e63d9c7ef.png
https://i-blog.csdnimg.cn/direct/e9926fa0a7704664961b2fd69e5da9ba.pnghttps://i-blog.csdnimg.cn/direct/5e0fd1d5f59b4b1a97e9accbf5f9ab8f.png
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