（自己编写函数）Python + Opencv 图像几何变换(缩小、放大、内凹，外凸，梯形变形、三角型变形、S型变形、图片旋转、图片平移)
因为之前写这个实验的时候，组织上有很多事情，所以当时，随便网上找了个 C++ 的上交了，昨天就补写了一下。这里写的缩小和方法都是等比例进行的，不是等比例的改也比较简单，这里就不改了，有兴趣的朋友可以自己尝试着改改，另外这里用的是灰度图，彩色图稍微改改就行了
比例缩小
ratio 是缩小比例，大致思路是：
1、先根据你输入的缩放比例生成一个与原图 * 缩放比例相同大小的灰度级矩阵。
2、根据书中说的首先根据缩小的倍率去算出，在原图中要隔多少个点采集一次生成新的图像，这就是我里面写的步长。比如：4*4 的 图像要缩小0.5倍，那么步长就是2 除了第一个点之外，其他每个点都要每隔两个点 取一次。
#按比例缩小
def DOWNRESIZE(gray , ratio=0.8) :
height , width = gray.shape[0] , gray.shape[1]
resize_width , resize_height = int(width * ratio) , int(height * ratio)
resize_gray = np.zeros([resize_height,resize_width],np.uint8) #创建一个和原图像 *缩小比例相同像素的空图
stepsize = 1.0/ratio #原图像的采集步长
for i in range (0,resize_height) :
for j in range (0,resize_width) :
if i == 0 and j == 0 : #缩小图(0,0)地方的像素用原图(1,1)的地方代替
resize_gray[i][j] = gray[1][1]
else : #缩小图其他地方的像素用此时原图对应的坐标-1的地方代替
resize_gray[i][j] = gray[int(i*stepsize)-1][int(j*stepsize)-1]
cv2.imshow("old",gray)
cv2.imshow("Downresize",resize_gray)
cv2.waitKey(0)
比例放大
比例方法，这里使用了两种方法：①最邻近插值法；②双线性插值。完全是根据概念，写的算法，概念就不重复了，可以百度，网上很多。
#按比例放大
def UPSIZE(gray , ratio=1.2) :
height , width = gray.shape[0] , gray.shape[1]
resize_width , resize_height = int(width * ratio) , int(height * ratio)
resize_gray = np.zeros([resize_height,resize_width],np.uint8)
"""
#最邻近插值法
for i in range (0,resize_height) :
for j in range (0,resize_width) :
if i == 0 and j == 0 :
resize_gray[i][j] = gray[int(i/ratio)+1][int(j/ratio)+1]
else :
resize_gray[i][j] = gray[int(i/ratio)-1][int(j/ratio)-1]
"""
#双线性插值
for i in range (0,resize_height) :
for j in range (0,resize_width) :
x = i/ratio
y = j/ratio
p=(i+0.0)/ratio-x
q=(j+0.0)/ratio-y
x=int(x)-1
y=int(y)-1
if x+1<i and y+1<j:
resize_gray[i,j]=int(gray[x,y]*(1-p)*(1-q)+gray[x,y+1]*q*(1-p)+gray[x+1,y]*(1-q)*p+gray[x+1,y+1]*p*q)
cv2.imshow("old",gray)
cv2.imshow("Upresize",resize_gray)
cv2.waitKey(0)
水平内凹
内凹与外凸还有S型都差不多，大致思路，生成正弦波的波形，然后，从这个正弦波去确定那些地方是黑色的，最后根据每行中不是黑色的部分和原来的比重，根据之前的缩小的步长去进行每行的缩放即可。
#水平内凹
def CONCAVE(gray) :
RANGE = 400
height, width = gray.shape[0], gray.shape[1]
resize_gray = np.zeros([height, width], np.uint8)
for i in range(height):
# 得到正弦波的波形，即j对应的起点
temp = float((width- RANGE) * math.sin(((2 * math.pi * i) / height) / 2))
for j in range (int(temp+0.5),int(width-temp)) :
#每行非黑色区域的长度
distance = int(width-temp) - int(temp+0.5)
#缩小的倍率
ratio = distance / width
#取点的步长
stepsize = 1.0/ratio
#将同意行缩小相同倍率
resize_gray[i][j] = gray[i][int((j-temp)*stepsize)]
cv2.imshow("old", gray)
cv2.imshow("Concave", resize_gray)
cv2.waitKey(0)
水平外凸
#水平外凸
def CONVEX(gray) :
RANGE = 400
height, width = gray.shape[0], gray.shape[1]
resize_gray = np.zeros([height, width], np.uint8)
temp1 = []
for i in range(height):
# 得到正弦波的波形，即j对应的起点
temp = float((width- RANGE) * math.sin(((2 * math.pi * i) / height) / 2))
temp = 200 - temp
for j in range (int(temp+0.5),int(width-temp)) :
#每行非黑色区域的长度
distance = int(width-temp) - int(temp+0.5)
#缩小的倍率
ratio = distance / width
#取点的步长
stepsize = 1.0/ratio
#将同意行缩小相同倍率
resize_gray[i][j] = gray[i][int((j-temp)*stepsize)]
cv2.imshow("old", gray)
cv2.imshow("Convex", resize_gray)
cv2.waitKey(0)
梯形形变
#梯形形变
def TRAPEZOID(gray,k=0.3) :
height, width = gray.shape[0], gray.shape[1]
value = k*height
resize_gray = np.zeros([height, width], np.uint8)
for i in range (height) :
temp = int( value - k * i )
for j in range (temp,width-temp) :
#每行非黑色区域的长度
distance = int(width-temp) - int(temp+0.5)
#缩小的倍率
ratio = distance / width
#取点的步长
stepsize = 1.0/ratio
#将同意行缩小相同倍率
resize_gray[i][j] = gray[i][int((j-temp)*stepsize)]
cv2.imshow("old", gray)
cv2.imshow("Trapezoid", resize_gray)
cv2.waitKey(0)
三角形形变
#三角形形变
def TRIANGLE(gray,k=0.5) :
height, width = gray.shape[0], gray.shape[1]
resize_gray = np.zeros([height, width], np.uint8)
for i in range (height) :
temp = int( k * i )
for j in range (temp) :
#每行非黑色区域的长度
distance = temp
#缩小的倍率
ratio = distance / width
#取点的步长
stepsize = 1.0/ratio
#将同意行缩小相同倍率
resize_gray[i][j] = gray[i][int((j-temp)*stepsize)]
cv2.imshow("old", gray)
cv2.imshow("Triangle", resize_gray)
cv2.waitKey(0)
S形形变
#S形变
def SSHAPE(gray,RANGE=450) :
height, width = gray.shape[0], gray.shape[1]
resize_gray = np.zeros([height, width], np.uint8)
for i in range(height):
# 得到正弦波的波形，即j对应的起点
temp = float((width - RANGE) / 2 + (width- RANGE) * math.sin((2 * math.pi * i) / height + math.pi) / 2)
for j in range (int(temp+0.5),int(RANGE+temp)) :
#映射关系
m = int(((j-temp) * width / RANGE))
if m >= width :
m=width-1
if m < 0 :
m=0
resize_gray[i,j]=gray[i,m]
cv2.imshow("old", gray)
cv2.imshow("Sshape", resize_gray)
cv2.waitKey(0)
图片旋转
#图片旋转
def ROTATE(gray, ANGLE = 45,center=None, scale=1.0) :
#将角度转化为弧度
""" #特别神奇的图案
ANGLE = math.radians(ANGLE)
height, width = gray.shape[0], gray.shape[1]
resize_gray = np.zeros([800,800], np.uint8)
for i in range (height) :
for j in range (width) :
angle = math.asin( i / width )
ANGLE = angle + ANGLE
x,y = int(width * math.cos(ANGLE)) , int(width * math.sin(ANGLE))
resize_gray[x][y] = gray[i][j]
cv2.imshow("old", gray)
cv2.imshow("Rotate", resize_gray)
cv2.waitKey(0)
"""
(height, width) = gray.shape[:2]
(cX, cY) = (width // 2, height // 2)
M = cv2.getRotationMatrix2D((cX, cY), -ANGLE, 1.0)
cos = np.abs(M[0, 0])
sin = np.abs(M[0, 1])
nW = int((height * sin) + (width * cos))
nH = int((height * cos) + (width * sin))
M[0, 2] += (nW / 2) - cX
M[1, 2] += (nH / 2) - cY
shuchu=cv2.warpAffine(gray, M, (nW, nH))
cv2.imshow("old", gray)
cv2.imshow("Rotate", shuchu)
cv2.waitKey(0)
图像平移
平移很简单，就不多说了
#图片平移
def HORIZONTALMOVE(gray,move_x,move_y) :
height, width = gray.shape[0], gray.shape[1]
resize_gray = np.zeros([height, width], np.uint8)
for i in range (height) :
for j in range (width) :
if i + move_x < height and j + move_y < width :
resize_gray[i][j] = gray[i+move_x][j+move_y]
else :
resize_gray [i][j] = 0
cv2.imshow("old", gray)
cv2.imshow("Horizeontalmove", resize_gray)
cv2.waitKey(0)
主函数
def MAIN() :
image = cv2.imread(r"D:\Code\Python\2.jpg")
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
while True :
print("0: 按比例缩小\n1: 按比例放大\n2: 水平外凹\n3: 水平外凸\n4: 梯形变形\n5: 三角形变形\n6: S形变形\n7: 图片旋转\n8: 图片平移\n")
keyinput = input ("请输入数字0—8，选择你需要的变换(按'Q'或'q'退出)：\n")
if keyinput == "0" :
ratio = float(input("请输入缩小倍数：\n"))
DOWNRESIZE(gray , ratio)
continue
elif keyinput == "1" :
ratio = float(input("请输入放大倍数：\n"))
UPSIZE(gray , ratio)
continue
elif keyinput == "2" :
CONCAVE(gray)
continue
elif keyinput == "3" :
CONVEX(gray)
continue
elif keyinput == "4" :
k = float(input("请输入梯形的斜度：\n"))
TRAPEZOID(gray,k)
continue
elif keyinput == "5" :
k = float(input("请输入三角形的斜度：\n"))
TRIANGLE(gray,k)
continue
elif keyinput == "6" :
RANGE = float(input("请输入变换强度：\n"))
SSHAPE(gray,RANGE)
continue
elif keyinput == "7" :
ANGLE = float(input("请输入旋转角度：\n"))
ROTATE(gray,ANGLE)
continue
elif keyinput == "8" :
move_x = int(input("请输入x轴偏移值：\n"))
move_y = int(input("请输入y轴偏移值：\n"))
HORIZONTALMOVE(gray,move_x,move_y)
continue
elif keyinput == "Q" or "q" :
break
else :
keyinput = input("您输入的字符有误，请输入 0-8 之间的数字：")
完整代码以及展示
import matplotlib.pyplot as plt
from scipy import signal
import numpy as np
import copy as cp
import random
import math
import cv2
import collections
#按比例缩小
def DOWNRESIZE(gray , ratio=0.8) :
height , width = gray.shape[0] , gray.shape[1]
resize_width , resize_height = int(width * ratio) , int(height * ratio)
resize_gray = np.zeros([resize_height,resize_width],np.uint8) #创建一个和原图像 *缩小比例相同像素的空图
stepsize = 1.0/ratio #原图像的采集步长
for i in range (0,resize_height) :
for j in range (0,resize_width) :
if i == 0 and j == 0 : #缩小图(0,0)地方的像素用原图(1,1)的地方代替
resize_gray[i][j] = gray[1][1]
else : #缩小图其他地方的像素用此时原图对应的坐标-1的地方代替
resize_gray[i][j] = gray[int(i*stepsize)-1][int(j*stepsize)-1]
cv2.imshow("old",gray)
cv2.imshow("Downresize",resize_gray)
cv2.waitKey(0)
#按比例放大
def UPSIZE(gray , ratio=1.2) :
height , width = gray.shape[0] , gray.shape[1]
resize_width , resize_height = int(width * ratio) , int(height * ratio)
resize_gray = np.zeros([resize_height,resize_width],np.uint8)
"""
#最邻近插值法
for i in range (0,resize_height) :
for j in range (0,resize_width) :
if i == 0 and j == 0 :
resize_gray[i][j] = gray[int(i/ratio)+1][int(j/ratio)+1]
else :
resize_gray[i][j] = gray[int(i/ratio)-1][int(j/ratio)-1]
"""
#双线性插值
for i in range (0,resize_height) :
for j in range (0,resize_width) :
x = i/ratio
y = j/ratio
p=(i+0.0)/ratio-x
q=(j+0.0)/ratio-y
x=int(x)-1
y=int(y)-1
if x+1<i and y+1<j:
resize_gray[i,j]=int(gray[x,y]*(1-p)*(1-q)+gray[x,y+1]*q*(1-p)+gray[x+1,y]*(1-q)*p+gray[x+1,y+1]*p*q)
cv2.imshow("old",gray)
cv2.imshow("Upresize",resize_gray)
cv2.waitKey(0)
#水平内凹
def CONCAVE(gray) :
RANGE = 400
height, width = gray.shape[0], gray.shape[1]
resize_gray = np.zeros([height, width], np.uint8)
for i in range(height):
# 得到正弦波的波形，即j对应的起点
temp = float((width- RANGE) * math.sin(((2 * math.pi * i) / height) / 2))
for j in range (int(temp+0.5),int(width-temp)) :
#每行非黑色区域的长度
distance = int(width-temp) - int(temp+0.5)
#缩小的倍率
ratio = distance / width
#取点的步长
stepsize = 1.0/ratio
#将同意行缩小相同倍率
resize_gray[i][j] = gray[i][int((j-temp)*stepsize)]
cv2.imshow("old", gray)
cv2.imshow("Concave", resize_gray)
cv2.waitKey(0)
#水平外凸
def CONVEX(gray) :
RANGE = 400
height, width = gray.shape[0], gray.shape[1]
resize_gray = np.zeros([height, width], np.uint8)
temp1 = []
for i in range(height):
# 得到正弦波的波形，即j对应的起点
temp = float((width- RANGE) * math.sin(((2 * math.pi * i) / height) / 2))
temp = 200 - temp
for j in range (int(temp+0.5),int(width-temp)) :
#每行非黑色区域的长度
distance = int(width-temp) - int(temp+0.5)
#缩小的倍率
ratio = distance / width
#取点的步长
stepsize = 1.0/ratio
#将同意行缩小相同倍率
resize_gray[i][j] = gray[i][int((j-temp)*stepsize)]
cv2.imshow("old", gray)
cv2.imshow("Convex", resize_gray)
cv2.waitKey(0)
#梯形形变
def TRAPEZOID(gray,k=0.3) :
height, width = gray.shape[0], gray.shape[1]
value = k*height
resize_gray = np.zeros([height, width], np.uint8)
for i in range (height) :
temp = int( value - k * i )
for j in range (temp,width-temp) :
#每行非黑色区域的长度
distance = int(width-temp) - int(temp+0.5)
#缩小的倍率
ratio = distance / width
#取点的步长
stepsize = 1.0/ratio
#将同意行缩小相同倍率
resize_gray[i][j] = gray[i][int((j-temp)*stepsize)]
cv2.imshow("old", gray)
cv2.imshow("Trapezoid", resize_gray)
cv2.waitKey(0)
#三角形形变
def TRIANGLE(gray,k=0.5) :
height, width = gray.shape[0], gray.shape[1]
resize_gray = np.zeros([height, width], np.uint8)
for i in range (height) :
temp = int( k * i )
for j in range (temp) :
#每行非黑色区域的长度
distance = temp
#缩小的倍率
ratio = distance / width
#取点的步长
stepsize = 1.0/ratio
#将同意行缩小相同倍率
resize_gray[i][j] = gray[i][int((j-temp)*stepsize)]
cv2.imshow("old", gray)
cv2.imshow("Triangle", resize_gray)
cv2.waitKey(0)
#S形变
def SSHAPE(gray,RANGE=450) :
height, width = gray.shape[0], gray.shape[1]
resize_gray = np.zeros([height, width], np.uint8)
for i in range(height):
# 得到正弦波的波形，即j对应的起点
temp = float((width - RANGE) / 2 + (width- RANGE) * math.sin((2 * math.pi * i) / height + math.pi) / 2)
for j in range (int(temp+0.5),int(RANGE+temp)) :
#映射关系
m = int(((j-temp) * width / RANGE))
if m >= width :
m=width-1
if m < 0 :
m=0
resize_gray[i,j]=gray[i,m]
cv2.imshow("old", gray)
cv2.imshow("Sshape", resize_gray)
cv2.waitKey(0)
#图片旋转
def ROTATE(gray, ANGLE = 45,center=None, scale=1.0) :
#将角度转化为弧度
""" #特别神奇的图案
ANGLE = math.radians(ANGLE)
height, width = gray.shape[0], gray.shape[1]
resize_gray = np.zeros([800,800], np.uint8)
for i in range (height) :
for j in range (width) :
angle = math.asin( i / width )
ANGLE = angle + ANGLE
x,y = int(width * math.cos(ANGLE)) , int(width * math.sin(ANGLE))
resize_gray[x][y] = gray[i][j]
cv2.imshow("old", gray)
cv2.imshow("Rotate", resize_gray)
cv2.waitKey(0)
"""
(height, width) = gray.shape[:2]
(cX, cY) = (width // 2, height // 2)
M = cv2.getRotationMatrix2D((cX, cY), -ANGLE, 1.0)
cos = np.abs(M[0, 0])
sin = np.abs(M[0, 1])
nW = int((height * sin) + (width * cos))
nH = int((height * cos) + (width * sin))
M[0, 2] += (nW / 2) - cX
M[1, 2] += (nH / 2) - cY
shuchu=cv2.warpAffine(gray, M, (nW, nH))
cv2.imshow("old", gray)
cv2.imshow("Rotate", shuchu)
cv2.waitKey(0)
#图片平移
def HORIZONTALMOVE(gray,move_x,move_y) :
height, width = gray.shape[0], gray.shape[1]
resize_gray = np.zeros([height, width], np.uint8)
for i in range (height) :
for j in range (width) :
if i + move_x < height and j + move_y < width :
resize_gray[i][j] = gray[i+move_x][j+move_y]
else :
resize_gray [i][j] = 0
cv2.imshow("old", gray)
cv2.imshow("Horizeontalmove", resize_gray)
cv2.waitKey(0)
def MAIN() :
image = cv2.imread(r"D:\Code\Python\2.jpg")
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
while True :
print("0: 按比例缩小\n1: 按比例放大\n2: 水平外凹\n3: 水平外凸\n4: 梯形变形\n5: 三角形变形\n6: S形变形\n7: 图片旋转\n8: 图片平移\n")
keyinput = input ("请输入数字0—8，选择你需要的变换(按'Q'或'q'退出)：\n")
if keyinput == "0" :
ratio = float(input("请输入缩小倍数：\n"))
DOWNRESIZE(gray , ratio)
continue
elif keyinput == "1" :
ratio = float(input("请输入放大倍数：\n"))
UPSIZE(gray , ratio)
continue
elif keyinput == "2" :
CONCAVE(gray)
continue
elif keyinput == "3" :
CONVEX(gray)
continue
elif keyinput == "4" :
k = float(input("请输入梯形的斜度：\n"))
TRAPEZOID(gray,k)
continue
elif keyinput == "5" :
k = float(input("请输入三角形的斜度：\n"))
TRIANGLE(gray,k)
continue
elif keyinput == "6" :
RANGE = float(input("请输入变换强度：\n"))
SSHAPE(gray,RANGE)
continue
elif keyinput == "7" :
ANGLE = float(input("请输入旋转角度：\n"))
ROTATE(gray,ANGLE)
continue
elif keyinput == "8" :
move_x = int(input("请输入x轴偏移值：\n"))
move_y = int(input("请输入y轴偏移值：\n"))
HORIZONTALMOVE(gray,move_x,move_y)
continue
elif keyinput == "Q" or "q" :
break
else :
keyinput = input("您输入的字符有误，请输入 0-8 之间的数字：")
if __name__ == "__main__":
MAIN()
变换结果
缩小
放大
水平内凹
水平外凸
梯形形变
三角形形变
S型形变
图片旋转
图片平移
