opencv+python 透视变换

# -*- coding:utf-8 -*-
import cv2
import numpy as np

def rad(x):
    return x * np.pi / 180

def coordinate_transform(img,anglex,angley,anglez,fov):
    z = np.sqrt(w ** 2 + h ** 2) / 2 / np.tan(rad(fov / 2))
    # 齐次变换矩阵
    rx = np.array([[1, 0, 0, 0],
                   [0, np.cos(rad(anglex)), -np.sin(rad(anglex)), 0],
                   [0, -np.sin(rad(anglex)), np.cos(rad(anglex)), 0, ],
                   [0, 0, 0, 1]], np.float32)

    ry = np.array([[np.cos(rad(angley)), 0, np.sin(rad(angley)), 0],
                   [0, 1, 0, 0],
                   [-np.sin(rad(angley)), 0, np.cos(rad(angley)), 0, ],
                   [0, 0, 0, 1]], np.float32)

    rz = np.array([[np.cos(rad(anglez)), np.sin(rad(anglez)), 0, 0],
                   [-np.sin(rad(anglez)), np.cos(rad(anglez)), 0, 0],
                   [0, 0, 1, 0],
                   [0, 0, 0, 1]], np.float32)

    r = rx.dot(ry).dot(rz)

    # 四对点的生成
    pcenter = np.array([h / 2, w / 2, 0, 0], np.float32)

    p1 = np.array([0, 0, 0, 0], np.float32) - pcenter
    p2 = np.array([w, 0, 0, 0], np.float32) - pcenter
    p3 = np.array([0, h, 0, 0], np.float32) - pcenter
    p4 = np.array([w, h, 0, 0], np.float32) - pcenter

    dst1 = r.dot(p1)
    dst2 = r.dot(p2)
    dst3 = r.dot(p3)
    dst4 = r.dot(p4)

    list_dst = [dst1, dst2, dst3, dst4]

    org = np.array([[0, 0],
                    [w, 0],
                    [0, h],
                    [w, h]], np.float32)

    dst = np.zeros((4, 2), np.float32)

    # 投影至成像平面
    for i in range(4):
        dst[i, 0] = list_dst[i][0] * z / (z - list_dst[i][2]) + pcenter[0]
        dst[i, 1] = list_dst[i][1] * z / (z - list_dst[i][2]) + pcenter[1]

    warpR = cv2.getPerspectiveTransform(org, dst)

    result = cv2.warpPerspective(img, warpR, (h, w))

    return result

if __name__ == '__main__':
    base_dir = 'no_connect/'
    imgname = r'167.jpg'
    img=cv2.imread(base_dir+imgname)

    img = cv2.imread(base_dir+imgname)
    h,w,ch = img.shape  # 获取图片大小（长，宽，通道数）
    img = cv2.resize(img, (w * 2, h * 2), cv2.INTER_LINEAR) #放大

    cv2.imshow("original", img)

    # 扩展图像，保证内容不超出可视范围
    img = cv2.copyMakeBorder(img, 20, 20, 20, 20, cv2.BORDER_CONSTANT, value=(100,100,100))
    h,w,ch = img.shape  # 获取图片大小（长，宽，通道数）
    fov = 10

    w,h = img.shape[0:2] #必须要注意，此处不是h,w = img.shape[0:2]，要不然图像会h,w会相反

    print('1',img.shape)
    #沿x轴进行顺时针变换
    anglex = 0
    angley = 0
    anglez = 0
    result=coordinate_transform(img,anglex,angley,anglez,fov)
    cv2.imshow("result1", result)


    #沿y轴进行顺时针变换
    anglex = 0
    angley = -50
    anglez = 0
    result=coordinate_transform(result,anglex,angley,anglez,fov)

    print(result.shape)
    print(h)
    # for i in range(h):
    #     for j in range(w):
    #         for c in range(3):
    #             if result[i,j,c]==0:
    #                 result[i, j, c]=100

    cv2.imshow("result2", result)

    # cv2.imwrite('transform.jpg',result)
    cv2.waitKey(0)
    cv2.destroyAllWindows()